<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.144790.2</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Research Article</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>Could Anemia Impact the Severity of Infections? COVID-19 as an Example</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 2; peer review: 2 approved]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>ZainAlAbdin</surname>
                        <given-names>Sham</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Aburuz</surname>
                        <given-names>Salahdein</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-2478-3914</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Akour</surname>
                        <given-names>Amal</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Beiram</surname>
                        <given-names>Rami</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Alnajjar</surname>
                        <given-names>Munther</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-8472-0173</uri>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Abdel-Qader</surname>
                        <given-names>Derar</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a4">4</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Arafat</surname>
                        <given-names>Mosab</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-9297-6745</uri>
                    <xref ref-type="aff" rid="a5">5</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Jarab</surname>
                        <given-names>Anan</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a5">5</xref>
                    <xref ref-type="aff" rid="a6">6</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Aburuz</surname>
                        <given-names>Mohammed</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a7">7</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>AlAshram</surname>
                        <given-names>Sara</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>AlJabi</surname>
                        <given-names>Sara</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>AlSalama</surname>
                        <given-names>Fatima</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0003-1595-3069</uri>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Al Hajjar</surname>
                        <given-names>Mohammed</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a8">8</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Department of Pharmacology and Therapeutics, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, Abu Dhabi, United Arab Emirates</aff>
                <aff id="a2">
                    <label>2</label>Department of Clinical Pharmacy, The University of Jordan, Faculty of Pharmacy, Amman, Jordan</aff>
                <aff id="a3">
                    <label>3</label>Department of Clinical Pharmacy, American University of Madaba, Amman, Amman Governorate, Jordan</aff>
                <aff id="a4">
                    <label>4</label>Pharmacy Department, University of Petra, Amman, Amman Governorate, Jordan</aff>
                <aff id="a5">
                    <label>5</label>College of Pharmacy, Al Ain University, Al Ain, Abu Dhabi, United Arab Emirates</aff>
                <aff id="a6">
                    <label>6</label>Department of Clinical Pharmacy, Faculty of Pharmacy, Jordan University of Science and Technology., Irbid, 22110, Jordan</aff>
                <aff id="a7">
                    <label>7</label>The University of Jordan, Amman, Amman Governorate, Jordan</aff>
                <aff id="a8">
                    <label>8</label>Department of Pharmacy, Al Ain Hospital, Al Ain, Abu Dhabi, United Arab Emirates</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:saburuz@uaeu.ac.ae">saburuz@uaeu.ac.ae</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>5</day>
                <month>11</month>
                <year>2024</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2024</year>
            </pub-date>
            <volume>13</volume>
            <elocation-id>295</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>30</day>
                    <month>10</month>
                    <year>2024</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 ZainAlAbdin S et al.</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/13-295/pdf"/>
            <abstract>
                <sec>
                    <title>Background</title>
                    <p>The association between anemia and severity of infection as well as mortality rates among patients infected with COVID-19 has scarcely been studied. This is the first study from the UAE aimed to assess the influence of anemia on COVID-19 severity, ICU admission, and mortality rate.</p>
                </sec>
                <sec>
                    <title>Methods</title>
                    <p>A retrospective chart review of hospitalized COVID-19 patients was conducted in a large COVID-19 referral hospital in UAE. The study included adult patients with confirmed COVID-19. Clinical and laboratory data, severity of the disease, ICU admissions, and mortality rates were analyzed and correlated to the presence of anemia among the patients.</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>A total of 3092 patients were included. 362 patients (11.7%) were anemic and most of the cases were between asymptomatic and mild COVID-19 (77.4%, n=2393). Among patients with anemia, 30.1% (n=109) had moderate to severe COVID-19. Statistically, anemia was associated significantly with a higher risk for severe COVID-19 outcome compared to nonanemic patients (AOR:1.59, 95% CI:1.24-2.04, p&lt;0.001). Intensive care unit (ICU) admission was almost 3 times higher among anemic patients compared to nonanemic (AOR:2.83,95% CI:1.89-4.25, p&lt;0.001). In addition, the overall mortality rate of 2.8% (n=87) was 2.5-fold higher in anemic than nonanemic patients (OR:2.56, CI: 1.49-4.06, p&lt;0.001). Moreover, older age (&#x2265;48-year-old) and male gender were independent predictors for severe illness (Age: OR=1.26, CI:1.07-1.51, p=0.006; Gender: OR:1.43,CI:1.15-1.78, p&lt;0.001)) and ICU admission (Age: OR:2.08, CI:1.47-2.94, p&lt;0.001; Gender: OR: 1.83, CI:1.12-3.00, p=0.008) whereas only age &#x2265;48 years old contributed to higher mortality rate (OR:1.60, CI:1.04-2.46, p=0.034).</p>
                </sec>
                <sec>
                    <title>Conclusion</title>
                    <p>Anemia was a major risk factor for severe COVID-19, ICU admission and mortality among hospitalized COVID-19 patients. Thus, healthcare providers should be aware of monitoring the hematological parameters among hospitalized patients with COVID-19 and anemia to reduce the risk of disease complications and mortality. This association should also be considered in other infectious diseases.</p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>COVID-19</kwd>
                <kwd>Anemia</kwd>
                <kwd>Severity</kwd>
                <kwd>ICU admission</kwd>
                <kwd>Hospitalization</kwd>
                <kwd>Mortality</kwd>
                <kwd>Hemoglobin</kwd>
                <kwd>Ferritin</kwd>
            </kwd-group>
            <funding-group>
                <funding-statement>The author(s) declared that no grants were involved in supporting this work.</funding-statement>
            </funding-group>
        </article-meta>
        <notes>
            <sec sec-type="version-changes">
                <label>Revised</label>
                <title>Amendments from Version 1</title>
                <p>We are pleased to submit the revised version of our manuscript,&#x00a0;in response to the insightful feedback provided by the reviewers. We have carefully addressed each comment and made substantial revisions to strengthen the overall quality and clarity of our study. &#x00a0; We have also refined the introduction, tables and discussion sections, improving both structure and content to support our findings better and highlight the study&#x2019;s implications. Each revision was made with the goal of enhancing the manuscript's scientific rigor and ensuring a thorough response to all reviewer feedback".</p>
            </sec>
        </notes>
    </front>
    <body>
        <sec id="sec5" sec-type="intro">
            <title>Introduction</title>
            <p>Anemia is a global health concern affecting more than 1.62 billion people worldwide (approximately 24.8%).
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup> The World Health Organization (WHO) defines anemia as a condition in which the number of red blood cells or the hemoglobin concentration within them is lower than normal. Low hemoglobin levels are considered at &lt;120 g/L in females and &lt;130 g/L in males. Based on hemoglobin level, severity of anemia can be categorized as mild (110-119 g/L for females and 110-129 g/L for males), moderate (80-109 g/L) or severe (less than 80 g/L).
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> Studies in the Arab region, assessing the clinical characteristics of COVID-19 patients, have not explored the prevalence of anemia nor tested its association with COVID-19 severity and mortality.</p>
            <p>Coronavirus disease of 2019 (COVID-19) has become a global pandemic since its outbreak in Wuhan (Hubei Province, China) in December 2019.
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> According to the National Emergency Crisis and Disasters Management Authority (NCEMA), more than 700 thousand cases were confirmed, and 2135 deaths were reported in the United Arab Emirates (UAE) until November 4th, 2021. The rate of new cases increased by 67.0% by 2023, despite the majority of the population being vaccinated against COVID-19.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup> Genetic mutations of severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) resulted in the emergence of more contagious variants, hence increasing cases on a daily basis.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup> Severe infections, such as COVID-19, are associated with hyper-inflammatory state, which might cause alteration in iron homeostasis.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> The main suggested mechanism was explained by increased iron acquisition and retention within macrophages and decreased intestinal absorption of iron. Subsequently, this reduces iron availability for erythropoiesis, decreasing the production of hemoglobin. Altogether, the inhibition of erythropoiesis by inflammatory markers, shortened half-life of erythrocytes and decreased biological activity of erythropoietin induce the development of anemia. In contrast to functional iron deficiency, which is associated with low ferritin levels and elevated transferrin levels, the anemia of inflammation is characterized by low levels of iron and transferrin or reduced saturation of transferrin with iron, while ferritin levels are normal or elevated.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> Furthermore, the presence of anemia has been identified as a major risk factor for hospitalization and mortality in several chronic and inflammatory diseases.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup>
            </p>
            <p>Since systemic inflammation is a common manifestation among COVID-19 patients, the presence of anemia in COVID-19 patients may well enhance disease progression and severity.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> However, the exact correlation is unclear, as whether it is a baseline characteristic of patients, or developed secondary to the inflammatory process of COVID-19. In this regard, studies have investigated the association between anemia and COVID-19 severity and mortality. However, there were some limitations in the literature regarding the prevalence and pathogenesis of anemia in COVID-19, as well as its impact on disease severity and mortality.</p>
            <p>Anemia was one of the most common hematologic findings in severe or critically ill COVID-19 patients.
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup> A study showed a severe disease presentation in terms of prolonged hospitalization and the need for ICU admission or mechanical ventilation. Generally, elevated ferritin levels were related to disease severity. However, anemia was not associated with higher mortality rate.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> However, a recent study found that elevated ferritin levels was a predictor for mortality in COVID-19 patients.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup>
            </p>
            <p>Recent data showed that anemia was significantly associated with severe illness and higher mortality rate,
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> especially if anemia was present upon admission.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> Moreover, Tremblay 
                <italic toggle="yes">et al.</italic> found that elevation of red blood cell distribution width (RDW) was a poor prognostic factor in hospitalized patients.
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup> RDW has been validated as a strong predictor of 30-day mortality, reflecting overall inflammation and oxidative stress.
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup> Another study reported that anemia induced the development of severe COVID-19 pneumonia.
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> All these studies concluded that anemia could be a predictive factor of increasing COVID-19 severity and mortality. However, the available data regarding the association between anemia and COVID-19 severity and mortality are scarce and controversial. Moreover, studies evaluating parameters of severe outcomes failed to demonstrate this association in a large sample size.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref17">17</xref>
                </sup>
            </p>
            <p>Remarkably, all the reviewed studies have not clearly classified cases in terms of severity (mild/moderate/severe) or evaluated the actual association between anemia and severity, ICU admission and mortality. Therefore, further studies are required to confirm this association in a larger cohort with definite stratification of severity per se. This is the first study aiming to assess the influence of anemia on COVID-19 severity, ICU admission and mortality rate in hospitalized patients in the UAE.</p>
        </sec>
        <sec id="sec6" sec-type="methods">
            <title>Methods</title>
            <sec id="sec7">
                <title>Study design, participants, and setting</title>
                <p>This is a retrospective observational study carried out on adult patients (&#x2265;18 years old) with a confirmed diagnosis of COVID-19, as measured using polymerase chain reaction (PCR) testing on a nasopharyngeal swab, who were admitted to a large government tertiary care center in Al-Ain city, UAE between March and June 2020. All adult patients diagnosed with COVID-19 during the study period were eligible for inclusion.</p>
                <p>The following were the exclusion criteria
                    <list list-type="order">
                        <list-item>
                            <label>1.</label>
                            <p>Pediatrics (Age &lt;18 years old)</p>
                        </list-item>
                        <list-item>
                            <label>2.</label>
                            <p>Pregnant patients</p>
                        </list-item>
                        <list-item>
                            <label>3.</label>
                            <p>Patients admitted for Surgery</p>
                        </list-item>
                        <list-item>
                            <label>4.</label>
                            <p>Patients with Co-infection with other diseases</p>
                        </list-item>
                        <list-item>
                            <label>5.</label>
                            <p>Patients with Cancer</p>
                        </list-item>
                    </list>
                </p>
            </sec>
            <sec id="sec8">
                <title>Ethical consideration</title>
                <p>This study was approved by Covid-19 IRB committee at the Department of Health in the United Arab Emirates (reference number: DOH/CVDC/2020/1121, 3
                    <sup>rd</sup> of June 2020). Patients&#x2019; information was kept confidential, and the authors did not have access to information that could identify individual participants during or after data collection. The study was performed in accordance with relevant guidelines and regulations. This was a retrospective review of patients&#x2019; files; therefore, a consent form was waived and not required.</p>
            </sec>
            <sec id="sec9">
                <title>Data collection</title>
                <p>During the period from June to July 2020, an IT engineer retrieved all the patients&#x2019; data from the hospital electronic databases for patients admitted from March to June 2020 in an Excel sheet. During the period from July to September 2020, two of the research investigators revised, cleaned, and coded the data independently to check for inter-rater reliability. Any disagreement was discussed between the two investigators. The data was accessed for the purpose of this research during the period from January-June 2022. The collected data encompassed demographic information (age, gender, and BMI) in addition to the death rate (calculated by dividing the number of dead cases by total number of the study sample) and presence of anemia for the purpose of our study. Baseline vital signs upon admission, including heart rate, respiratory rate, oxygen saturation, and systolic and diastolic blood pressure, as well as key laboratory parameters related to anemia (hemoglobin, hematocrit, ferritin, D-dimer, and alkaline phosphatase), were reviewed and analyzed.</p>
                <p>Additionally, clinical manifestations on admission (cough, shortness of breath, fever, sore throat, pain, nausea, vomiting and diarrhea), disease severity (asymptomatic, mild, moderate, severe) related to COVID-19 infection were also presented in this study. The disease severity of COVID-19 was categorized according to the guidelines for diagnosis and treatment of COVID-19 published by the National Institute of Health (NIH) (
                    <italic toggle="yes">Overview of COVID-19</italic>).
                    <sup>
                        <xref ref-type="bibr" rid="ref18">18</xref>
                    </sup> The NIH has categorized the severity of COVID-19 from no symptoms to critically ill cases into 5 categories: asymptomatic, mild, moderate, severe, and critically illness. However, the authors of this study classified the severity of COVID-19 into two categories since the distribution of patients in these categories is inconsistent and for better tabulation of the findings as follows: 1) Asymptomatic/mild illness: those with confirmed COVID-19 with or without the typical symptoms of the disease with no evidence of dyspnea or abnormal chest imaging, and 2) Moderate to severe/critical illness: those with typical symptoms, evidence of dyspnea, PaO
                    <sub>2</sub> of &#x2265;94%, and abnormal chest imaging, with or without respiratory failure/multiple organ dysfunction.</p>
            </sec>
            <sec id="sec10">
                <title>Definitions</title>
                <p>Anemia was defined as hemoglobin (Hgb) levels &lt;12.0 g/dL in females and &lt;13.0 g/dL in males as per the study site reference values. Anemia was further categorized based on hemoglobin levels as follows: mild: 10.0 g/dL to lower limit of normal range (12.0 g/dL in females and 13.0 g/dL in males), moderate: 8.0 to 10.0 g/dL, and severe: below 8 g/dL.
                    <sup>
                        <xref ref-type="bibr" rid="ref14">14</xref>
                    </sup> Anemia diagnosis was also confirmed from the hospital database.</p>
            </sec>
            <sec id="sec11">
                <title>Study outcomes</title>
                <p>The primary outcome of this study was to evaluate the association between anemia and COVID-19 severity, ICU admission and mortality in hospitalized COVID-19 patients. A secondary outcome was to investigate the effect of other demographic factors including age and gender on COVID-19 outcomes (disease severity, ICU admission rate, and mortality rate).</p>
            </sec>
            <sec id="sec12">
                <title>Statistical analysis</title>
                <p>The Statistical Package for the Social Sciences (IBM- SPSS, version 26.0) was used for the statistical analysis of data. Mean and standard deviation (SD) were calculated to present parametric data, while median and interquartile range were calculated for non-parametric data. Categorical variables were described as frequencies and percentages.</p>
                <p>Chi-square test or Fisher&#x2019;s exact test was calculated to assess the association between anemia and severity of symptoms (stratified as asymptomatic/mild and moderate/severe cases for patients with or without anemia). Similarly, the ICU admissions and mortality rate were assessed and compared for and between patients with and without anemia using the abovementioned statistics. The differences in laboratory parameters between patients with or without anemia were analyzed using the independent t-test or Mann-Whitney test. A p-value less than 0.05 indicated a statistically significant difference with a confidence interval of 95.0%. Additionally, multivariable logistic regression analysis was performed to confirm the influence of anemia on disease severity, ICU admission and mortality.</p>
            </sec>
        </sec>
        <sec id="sec13" sec-type="results">
            <title>Results</title>
            <p>
                <xref ref-type="table" rid="T1">Table 1</xref> represents the differences in demographics and clinical characteristics of the patients with and without anemia. The study included a total of 3092 patients. The average age of all patients (including anemic and non-anemic) was 44.29&#x00b1;13.42 years old and majority of them were males (77.8%, n=2407). In addition, 11.7% of total patients were previously diagnosed with anemia (n=362).</p>
            <table-wrap id="T1" orientation="portrait" position="float">
                <label>Table 1. </label>
                <caption>
                    <title>Demographic and clinical characteristics of the patients (n=3092).</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Variables</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Non-anemic (n=2730)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Anemic (n=362)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">p-value</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="4" rowspan="1" valign="top">
                                <bold>Gender, n (%)</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Male (n=2407)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2188 (90.9)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">219 (9.1)</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Female (n=685)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">542 (79.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">143 (20.9)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="4" rowspan="1" valign="top">
                                <bold>Age, n (%)</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">18-47 yo (n=1902)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1733 (91.1)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">169 (8.9)</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2265;48 yo (n=1190)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">997 (83.8)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">193 (16.2)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="4" rowspan="1" valign="top">
                                <bold>BMI, n (%)</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;30 kg/m
                                <sup>2</sup> (n=2442)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2182 (89.4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">260 (10.6)</td>
                            <td align="left" colspan="1" rowspan="2" valign="middle">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2265;30 kg/m
                                <sup>2</sup> (n=650)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">548 (84.3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">102 (15.7)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="4" rowspan="1" valign="top">
                                <bold>Vital Signs (Mean&#x00b1;SD)</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Age (years)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">43.6&#x00b1;12.9</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">49.7&#x00b1;15.9</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Heart rate (beats/min)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">91.25&#x00b1;14.66</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">92.95&#x00b1;14.53</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>0.038</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Respiratory rate (breaths/min)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">19.45&#x00b1;4.74</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">20.72&#x00b1;5.74</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Systolic Blood pressure (mmHg)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">136.18&#x00b1;17.89</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">132.60&#x00b1;20.69</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>0.002</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Diastolic Blood pressure (mmHg)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">82.15&#x00b1;11.61</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">77.09&#x00b1;13.86</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="4" rowspan="1" valign="top">
                                <bold>Lab parameters Mean (SD) or Median (IQ range)</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">D-dimer (&#x03bc;g/mL)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.82&#x00b1;2.44</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.40&#x00b1;2.98</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">HCT (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">M: 0.42 (0.04)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">M: 0.38 (0.06)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">F: 0.37 (0.04)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">F: 0.34 (0.05)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">Hgb (g/dL)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">M: 14.49 (1.46)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">M: 12.60 (2.25)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">F: 12.48 (1.32)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">F: 10.97 (1.86)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Oxygen saturation (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">97.84&#x00b1;3.66</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">96.30&#x00b1;6.39</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">BMI (kg/m
                                <sup>2</sup>)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">27.51&#x00b1;7.56</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">28.51&#x00b1;6.97</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>0.011</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">HBA1c</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.60&#x00b1;2.30</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.02&#x00b1;2.09</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>0.044</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">Ferritin (mg/L)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">M: 416.00 (244.00-745.00)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">M: 630.00 (331.00 &#x2013; 1288.00)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">F: 123.00 (54.00-249.00)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">F: 170.00 (54.00-503.00)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">INR</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.02&#x00b1;0.55</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.16&#x00b1;0.87</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.374</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>Univariate analysis of the biodata showed that anemia was higher among females compared to males (20.9% and 9.1%; respectively, p&lt;0.001). In addition, patients aged 48 years old and older were more likely to present with anemia compared to patients aged between 18 and 47 years old (16.2% and 8.9%; respectively, p&lt;0.001). Furthermore, anemia was more prevalent among patients with BMI &#x2265;30 kg/m
                <sup>2</sup> when compared to patients with lower BMI (15.7% and 10.6%; respectively, p&lt;0.001).</p>
            <p>Upon evaluating the relationship between anemia and certain hematological parameters, it was found that D-dimer and ferritin were significantly higher in patients with anemia compared to the non-anemics (p&lt;0.001). In contrast, hemoglobin and hematocrit levels were remarkably lower in patients with anemia (p&lt;0.001) compared to the non-anemics. Further details of the differences of vital signs and laboratory parameters among patients with and without anemia are illustrated in 
                <xref ref-type="table" rid="T1">Table 1</xref>.</p>
            <p>The majority of patients (77.4%, n=2393) were asymptomatic or had a mild form of the infection. 
                <xref ref-type="fig" rid="f1">Figure 1</xref> shows the clinical presentation of patients with COVID-19. Cough was the most reported symptom by the patients followed by fever, and dyspnea. Other symptoms, such as loss of smell and taste were rarely reported. Regarding the clinical presentation of symptoms among anemic and nonanemic patients, no statistical difference was found.</p>
            <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                <label>Figure 1. </label>
                <caption>
                    <title>Clinical Presentation among anemic and non-anemic COVID-19 patients.</title>
                </caption>
                <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/174189/ed0f3c60-4ba9-47e0-9a4a-445b0535a0b7_figure1.gif"/>
            </fig>
            <p>
                <xref ref-type="table" rid="T2">Table 2</xref> represents the Bivariate analysis of patients&#x2019; characteristics and COVID-19 outcomes (severity of COVID-19, ICU admissions, and mortality rate). The risk of developing moderate to severe symptoms was significantly higher when patients presented with anemia, male gender, and age &#x2265;48 years old. In addition, ICU admission among anemic patients was almost 3 times higher than non-anemic patients, was also more than 2 times higher in patients aged &#x2265;48 years old compared to young-age patients, and 1.5 times higher in males compared to females. Moreover, anemia was significantly associated with over 2.5 times risk of death, as 6.1% of anemic cases died compared to 2.4% of nonanemic cases. Also, patients aged &#x2265;48 years old had almost 2 folds higher risk for mortality compared to younger ages. Further details are illustrated in 
                <xref ref-type="table" rid="T2">Table 2</xref>.</p>
            <table-wrap id="T2" orientation="portrait" position="float">
                <label>Table 2. </label>
                <caption>
                    <title>Bivariate analysis of patients&#x2019; characteristics and COVID-19 outcomes.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">COVID-19 Outcomes</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Independent variables</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">% (n/N)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Adjusted (OR)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Confidence Interval (CI)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">P- value</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="9" valign="middle">
                                <bold>Severity (Moderate to Severe)</bold> 22.6% (669/3092)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>
                                    <italic toggle="yes">Presence of Anemia</italic>
                                </bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Anemic</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">30.1% (109/362)</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Non-anemic</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">21.6% (590/2730)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.56</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.23-1.99</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>
                                    <italic toggle="yes">Gender</italic>
                                </bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Female</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">19.0% (130/685)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top"/>
                            <td align="left" colspan="1" rowspan="1" valign="top"/>
                            <td align="left" colspan="1" rowspan="1" valign="top"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Male</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">23.6% (569/2407)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.32</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.07-1.64</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>0.005</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>
                                    <italic toggle="yes">Age</italic>
                                </bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">18-47 YO</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">20.7% (394/1902)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.32</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.11-157</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2265; 48 YO</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">25.6% (315/1190)</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="9" valign="middle">
                                <bold>ICU Admission</bold> 4.6% (142/3092)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>
                                    <italic toggle="yes">Presence of Anemia</italic>
                                </bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Anemic</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10.2% (37/362)</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Non-anemic</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.8% (105/2730)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.85</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.92-4.21</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>
                                    <italic toggle="yes">Gender</italic>
                                </bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Male</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5.0% (120/2407)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.58</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.01-2.51</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>0.028</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Female</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.2% (22/685)</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Age</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">18-47 YO</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.2% (60/1902)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.27</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.62-3.20</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2265; 48 YO</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6.9% (82/1190)</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="6" valign="middle">
                                <bold>Mortality</bold> 2.8% (87/3092)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>
                                    <italic toggle="yes">Presence of Anemia</italic>
                                </bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Anemic</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6.1% (22/362)</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Non-anemic</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.4% (65/2730)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.65</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.61-4.36</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>
                                    <italic toggle="yes">Age</italic>
                                </bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">18-47 YO</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.2% (42/1902)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.74</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.14-2.67</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>0.007</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2265; 48 YO</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.8% (45/1190)</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>Upon classifying patients anemia into normal, mild and moderate to severe; severity of COVID-19 was higher in anemic compared to normal patients. On the other hand, moderate-to-severe anemia was associated with greater ICU admissions and mortality rates as presented in 
                <xref ref-type="table" rid="T3">Table 3</xref>. The p-value was significant for all comparisons, indicates an overall difference between subgroups and suggest that further post-hoc testing, would be needed to identify specific group differences.</p>
            <table-wrap id="T3" orientation="portrait" position="float">
                <label>Table 3. </label>
                <caption>
                    <title>Association between anemia severity and COVID-19 outcomes (n=3092).</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">COVID-19 outcomes</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Severity of anemia</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">% (n/N)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">P-Value</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="3" valign="top">
                                <bold>
                                    <italic toggle="yes">Moderate to Severe Disease</italic>
                                </bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Normal*</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">21.6% (590/2730)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Mild</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">30.3% (90/297)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Moderate to Severe</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">29.3% (19/65)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="3" valign="top">
                                <bold>
                                    <italic toggle="yes">ICU Admission</italic>
                                </bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Normal*</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.8% (105/2730)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Mild</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">9.1% (27/297)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Moderate to Severe</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">15.4% (10/65)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="3" valign="top">
                                <bold>
                                    <italic toggle="yes">Mortality</italic>
                                </bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Normal*</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.4% (65/2730)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>&lt;0.001</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Mild</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5.4% (16/297)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Moderate to Severe</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">9.2% (6/65)</td>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>Multivariable logistic regression analysis of anemia and health outcomes among hospitalized patients with COVID-19 is shown in 
                <xref ref-type="table" rid="T4">Table 4</xref>. After adjustment of gender, ages, BMI and anemia, anemia was shown to be a significantly independent risk factor for severe symptoms (AOR: 1.59, 95% CI: 1.24-2.04, p &lt;0.001), ICU admission (AOR: 2.83, 95% CI: 1.89-4.25, p &lt;0.001), and higher mortality rate (AOR: 2.46, 95% CI: 1.49-4.06, p &lt;0.001). In addition, male gender and age (&#x2265;48-year-old) were independent risk factors that significantly contributed to developing moderate severe COVID-19 and increasing the rate of ICU admissions. Also, age (&#x2265;48 years old) was an independent risk factor for mortality as well.</p>
            <table-wrap id="T4" orientation="portrait" position="float">
                <label>Table 4. </label>
                <caption>
                    <title>The logistic regression analysis of anemia and health outcomes among hospitalized patients with COVID-19.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Variables</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Adjusted Odds Ratio (AOR)*</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Confidence Interval (CI)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">P-value</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Severity</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Anemia</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.59</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.24-2.04</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Age (&#x2265;48-year-old)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.27</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.07-1.51</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.006</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Gender (male)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.43</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.15-1.78</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>ICU admission</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Anemia</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.83</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.89-4.25</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Age (&#x2265;48 yo)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.08</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.47-2.94</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Gender (male)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.83</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.12-3.00</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.008</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Mortality</bold>
                            </td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Anemia</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.46</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.49-4.06</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Age (&#x2265;48-year-old)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.60</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.04-2.46</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.034</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
        </sec>
        <sec id="sec14" sec-type="discussion">
            <title>Discussion</title>
            <p>To the best of our knowledge, our study is the first comprehensive, decently sized study addressing the potential association between anemia and clinical outcomes in hospitalized COVID-19 patients in the United Arab Emirates. These outcomes included disease severity, risk of ICU admission, and mortality. Additionally, the study explored possible correlation between certain demographic variables and the disease outcomes. Based on the data collected from 3092 hospitalized adult patients in one of the largest hospitals in UAE, the majority of the patients were males, 11.7% of whom were anemic. Compared to findings of previous studies, our findings indicated lower prevalence of anemia in the studied sample (11.4%), whereas other studies reported a higher prevalence of anemia ranging from 24.7%-35.5% among hospitalized COVID-19 patients.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> This could be explained by the predominance of males and young age (&lt;48 years old) patients, who are considered to be at lower risk of suffering from anemia.</p>
            <p>The prevalence of anemia was higher in females. Generally, anemia is reported to be more prevalent in females and lower hemoglobin values are seen among females compared to males even in cases without anemia, which is attributed to low iron intake and reproductive issues such as menstruation, pregnancy, and lactation.
                <sup>
                    <xref ref-type="bibr" rid="ref19">19</xref>
                </sup> Interestingly, studies evaluating anemia in COVID-19 patients found a higher prevalence of anemia within the male population.
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup> On the other hand, other studies found a higher prevalence of anemia within females.
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> Of note, however, these studies failed to demonstrate a significant association between anemia and gender. This variation from the well documented fact about anemia prevalence could be attributed to the lack of distinction between the commonly encountered iron deficiency anemia and anemia of inflammation typically linked to COVID-19.</p>
            <p>Our modelling analysis showed that patients aged &#x2265; 48 years old had higher prevalence of anemia. This is in agreement with many previous studies that demonstrated a higher prevalence of anemia with advancing age.
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup> Interestingly, while Chen et al. demonstrated an increasing anemia prevalence with age, the prevalence then decreased at age of 80 and above years old; however, a small cohort was reported in that study.
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> The relationship between anemia and aging could be explained by common nutritional deficiencies (iron, folate, or vitamin B12), typically encountered with elderly or in cases of anemia of chronic diseases, and sometimes due to unknown reasons. This is mainly because with aging there seems to be a progressive resistance of bone marrow erythroid progenitors to erythropoietin, and a chronic subclinical pro-inflammatory state, resulting in anemia.
                <sup>
                    <xref ref-type="bibr" rid="ref19">19</xref>
                </sup>
            </p>
            <p>Our study showed that most of COVID-19 cases with anemia were associated with high serum ferritin, which is mainly attributed to the fact that ferritin levels elevate dramatically during infection or inflammation.
                <sup>
                    <xref ref-type="bibr" rid="ref22">22</xref>
                </sup> This is because ferritin by itself is a key biomarker in inflammatory and pathological conditions, mainly because it leaks from damaged cells.
                <sup>
                    <xref ref-type="bibr" rid="ref23">23</xref>
                </sup> Basically, males have higher ferritin levels than females throughout their adulthood in which they peak between 30 to 39 years and stay constant until their 70&#x2019;s. Females typically have relatively low ferritin levels, which begin to rise after menopause.
                <sup>
                    <xref ref-type="bibr" rid="ref22">22</xref>
                </sup> Few studies highlighted the correlation between serum ferritin levels and COVID-19 clinical characteristics and disease outcomes. Cheng 
                <italic toggle="yes">et al</italic> found that ferritin levels generally varied based on COVID-19 severity and presence of comorbidities. Ferritin levels were significantly elevated in patients with COVID-19 and other comorbidities -including anemia- rather than COVID-19 alone. This could be probably due to the presence of concurrent inflammatory and pathological reactions.
                <sup>
                    <xref ref-type="bibr" rid="ref24">24</xref>
                </sup> Similarly, this finding was also illustrated in a previous observational study which reported that anemia was highly prevalent among 206 hospitalized COVID-19 patients.
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>
                </sup>
            </p>
            <p>Although COVID-19 is a primary respiratory illness, it also affects multiple organs and results in systemic complications, such as thrombotic disorders and coagulopathies. Several studies reported significant elevation in D-dimer among hospitalized COVID-19 patients, reflecting the remarkable prevalence of thrombotic disorders in this population. Thus, elevation of D-dimer could be a potential biomarker of COVID-19 poor prognosis.
                <sup>
                    <xref ref-type="bibr" rid="ref25">25</xref>
                </sup> A cut-off value of D-dimer has not yet been established to predict mortality in patients with COVID-19, but one study published lately in 2021 described a cut-off point of 1.5&#x03bc;g/ml (sensitivity 70.6%, specificity 78.4%).
                <sup>
                    <xref ref-type="bibr" rid="ref25">25</xref>
                </sup> Yet only one study compared the levels of D-dimer in anemic versus non-anemic COVID-19 patients. They found that D-dimer was higher in patients with moderate/severe anemia compared to mild anemia.
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> This is in line with our findings that D-dimer levels were higher in the anemic patients&#x2019; group (p&lt;0.001). There is a lack of clear justification behind the additional elevation of D-dimer among COVID-19 anemic cases, and further studies are required to understand this finding manifestly.</p>
            <p>The present study reported that majority of COVID-19 patients were asymptomatic or had mild symptoms of COVID-19. However, patients with moderate or severe symptoms presented mainly with cough and fever. Likewise, a systematic review of 152 studies indicated that fever and cough were highly prevalent among COVID-19 patients.
                <sup>
                    <xref ref-type="bibr" rid="ref26">26</xref>
                </sup> However, some reports revealed that in addition to cough and fever, a sudden loss of smell or taste is a common manifestation of the disease.
                <sup>
                    <xref ref-type="bibr" rid="ref27">27</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref28">28</xref>
                </sup>
            </p>
            <p>An interesting finding of this study was the significant association between anemia and the risk of developing moderate to severe symptoms
                <italic toggle="yes">.</italic> This finding is in agreement with previously published studies that found a significant effect of anemia on disease severity related to the severe inflammatory response.
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref29">29</xref>
                </sup> Additionally, several studies that explored the parameters of developing severe disease outcomes failed to demonstrate this association with a considerable sample size.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref17">17</xref>
                </sup> Fan (2020) investigated 69 patients and found that lymphopenia and elevated LDH were associated with higher rates of ICU admissions.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup> In addition, Henry 
                <italic toggle="yes">et al</italic> pooled data into a meta-analysis from 21 studies with small sample sizes; 18 studies of which inspected the severity, and the other 3 assessed the mortality rate of COVID-19 by studying several hematological parameters. Although this analysis reported a significant decline in hemoglobin levels among patients with a severe form of the disease, it did not assess anemia as a determinant factor of COVID-19 severity.
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup>
            </p>
            <p>Besides, findings of this study showed almost 3-fold increase in the risk of ICU admission in COVID-19 patients with anemia compared to their counterparts. This was further supported by the results of a multivariable logistic regression after adjustment for covariates. Our results concurred with a prospective study conducted in the Middle East with a decently sized cohort (n=1274), which supports our finding that anemia is an independent risk factor for ICU admission among patients with COVID-19 (p&lt;0.001).
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup> On the other hand, Cai 
                <italic toggle="yes">et al.</italic> investigated factors associated with ICU admission and failed to find an association between hemoglobin levels and risk of being admitted to the ICU.
                <sup>
                    <xref ref-type="bibr" rid="ref30">30</xref>
                </sup> Such results could be attributed to the small sample size of the study (n=96). In the same manner, Bellman-Weiler 
                <italic toggle="yes">et al.</italic> found no significant relationship between anemia and ICU admission, but concluded that alterations in iron homeostasis -as a higher ferritin/transferrin ratio- reflected further risk of advanced disease and predicted the need for ICU admission.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> However, these findings were limited to those without iron metabolism variability, which resulted in a selection bias and a smaller sample included in the multivariate analysis. Moreover, according to Bellman-Weiler 
                <italic toggle="yes">et al.</italic> hemoglobin -as a variable- was not a significant predictor in their multivariate regression analysis, illustrating a probable residual confounding for anemia classification. Furthermore, similar studies recognized the relationship between the presence of anemia and high mortality rate amongst ICU-admitted COVID-19 patients. However, these studies either did not assess ICU admission as a final outcome due to the rapid turnover (discharge or death)
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>
                </sup> nor tested if the presence of anemia had an effect on admission to the ICU.
                <sup>
                    <xref ref-type="bibr" rid="ref29">29</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref31">31</xref>
                </sup>
            </p>
            <p>According to findings of the current study, anemia was associated with a high mortality rate among hospitalized COVID-19 patients compared to non-anemic cases with COVID-19. This observation was further reaffirmed using a multivariable logistic regression analysis, after adjusting for covariables that could contribute to this finding. The results of this study showed that anemia was an independent predictive risk factor for death in COVID-19 patients. Similarly, most studies investigated the relationship between anemia and mortality in COVID-19 patients, and all of them came to the agreement that anemia significantly contributes to a higher mortality rate. Correspondingly, a single center retrospective study assessed the impact of anemia on mortality rate among 333 hospitalized COVID-19 patients with anemia. The study has found that more than half of these patients were significantly at high risk of all-cause mortality.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> Moreover, AbuRuz, S 
                <italic toggle="yes">et al</italic>, Bellman 
                <italic toggle="yes">et al</italic>., Algassim et al, 
                <ext-link ext-link-type="uri" xlink:href="https://www.ncbi.nlm.nih.gov/pubmed/?term=Faghih%20Dinevari%20M%5BAuthor%5D&amp;cauthor=true&amp;cauthor_uid=33568084">Dinevari</ext-link> 
                <italic toggle="yes">et al</italic>, Tremblay 
                <italic toggle="yes">et al</italic>, and Oh 
                <italic toggle="yes">et al</italic>. showed similar results and further confirmed this association.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref31">31</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref32">32</xref>
                </sup> In addition, Bellman 
                <italic toggle="yes">et al</italic> further analyzed this association and compared the mortality rate between mild and moderate/severe anemia. Accordingly, only moderate/severe anemia was significantly associated with a higher mortality rate. Furthermore, their study examined this association after stratifying the subjects by anemia type, as anemia of functional iron deficiency vs. anemia of inflammation. They concluded that anemia of iron deficiency was not associated with higher mortality rates compared to non-anemic cases.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> On the other hand, Tremblay 
                <italic toggle="yes">et al.</italic> reported that even mild anemia is a predictive risk factor of COVID 19 mortality.
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup>
            </p>
            <p>Multivariable regression analysis revealed that male gender and older age (&#x2265;48 years) significantly increased the severity of COVID-19 and ICU admissions. However, only older age, along with anemia, was found to be an independent risk factor for mortality. Previous studies evaluating the clinical impact of anemia did not evaluate the impact of demographics on the disease outcomes, rather they outlined the relationship between demographic factors and anemia.
                <sup>
                    <xref ref-type="bibr" rid="ref19">19</xref>
                </sup> Available studies simply reported the prevalence of anemia in each demographic group, and tested if a significant difference was observed.
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup>
            </p>
            <sec id="sec15">
                <title>Strength &amp; limitations</title>
                <p>Our study is the first study in the Gulf region that spotted the light on the association between anemia and COVID-19 outcomes in terms of severity, ICU admission and mortality. We included a large sample size of COVID-19 patients in a hospital that was specialized for COVID-19 cases. We studied the association between anemia and COVID-19 severity, ICU admission and mortality by conducting a multivariable regression analysis with adjustment of certain covariables that could affect the association. Another point that highlighted the novelty of our study was that we considered other demographic factors and we tested their impact on disease severity, mortality and ICU admission using a multivariable model analysis. In addition, we measured several hematological parameters including hemoglobin, hematocrit, D-dimer and ferritin which reflected the level and significance of anemia in COVID-19 patients. Finally, our population included patients at younger ages compared to previously presented studies, making the influence of age and other comorbidities on the results less significant, since not all of the patients were elderly.</p>
                <p>The present study had several limitations. First, this was a retrospective observational study; therefore, we were unable to accurately control exposure factors, covariates, and potential confounders. Second, it was a single center study, hence, it would be difficult for the results to be emphasized and generalized amongst other areas in the region. Third, our data were not longitudinal; we had no information about hemoglobin levels before infection and we were unable to track the changes in hematological parameters during hospitalization. Fourth, we did not collect and analyze the clinical interventions and therapeutic information related to anemia in COVID-19 patients. These data could have provided a valuable justification for the normalization of hemoglobin and hematocrit levels among patients. Lastly, we did not classify and clearly define anemia based on severity, and the etiology of anemia was not distinguished, whether it is a functional iron deficiency or anemia of inflammation. This limited our interpretations and was a barrier to assessing the causal association between anemia and COVID-19 outcomes.</p>
            </sec>
        </sec>
        <sec id="sec16" sec-type="conclusion">
            <title>Conclusion</title>
            <p>Anemia was a common clinical manifestation among COVID-19 patients. This study highlighted the association between anemia and COVID-19 clinical outcomes. Analysis of several hematological parameters illustrated that anemia was an independent predictive factor for poor COVID-19 outcomes. Other demographic factors, such as age and gender had an impact on the clinical outcomes in COVID-19 patients. These results could be a guidance for clinicians in triaging hospitalized COVID-19 patients upon admission by considering their clinical parameters, particularly, hemoglobin levels. In turn, this could enhance the healthcare team&#x2019; decision for early, intensive therapeutic interventions for certain patient and tailor a patient-specific treatment plan. Further studies with more comprehensive follow-up of COVID-19 patients with anemia, stringent designs and encompassing multiple centers are needed to confirm causality and support generalizability and possibly develop a guideline for management of anemia in COVID-19 patients. This association should also be considered in other infectious diseases.</p>
        </sec>
        <sec id="sec17">
            <title>Author contribution</title>
            <p>Sham ZainAlAbdin: Conceptualization, Formal Analysis, Investigation, Methodology, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing</p>
            <p>Salahdein AbuRuz: Conceptualization, Formal Analysis, Investigation, Methodology, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing, Supervision</p>
            <p>Amal Akour: Conceptualization, Formal Analysis, Methodology, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing,</p>
            <p>Rami Beiram: Conceptualization, Methodology, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing</p>
            <p>Munther Alnajjar: Conceptualization, Methodology, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing</p>
            <p>Derar Abdel-Qader: Conceptualization, Methodology, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing</p>
            <p>Mosab Arafat: Conceptualization, Methodology, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing</p>
            <p>anan jarab: Conceptualization, Methodology, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing</p>
            <p>Mohammed Aburuz: Data Curation, Writing &#x2013; Original Draft Preparation, Writing &#x2013; Review &amp; Editing</p>
            <p>Sara AlAshram: Conceptualization, Methodology, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing, Data curation</p>
            <p>Sara AlJabi: Conceptualization, Methodology, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing, Data curation</p>
            <p>Fatima AlSalama: Conceptualization, Methodology, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing, Data curation</p>
            <p>Mohammed Al Hajjar: Conceptualization, Methodology, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing, Data curation</p>
        </sec>
    </body>
    <back>
        <sec id="sec20" sec-type="data-availability">
            <title>Data availability statement</title>
            <p>Figshare: Could anemia impact the severity of infections? COVID-19 as an example. 
                <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.24511999.v1">https://doi.org/10.6084/m9.figshare.24511999.v1</ext-link>.
                <sup>

                    <xref ref-type="bibr" rid="ref33">33</xref>
</sup>
            </p>
            <p>The project contains the following underlying data:
                <list list-type="bullet">
                    <list-item>
                        <label>&#x2022;</label>
                        <p>Covid anemia.xlsx</p>
                    </list-item>
                </list>
            </p>
            <p>Data are available under the terms of the 
                <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International license</ext-link> (CC-BY 4.0).</p>
            <sec id="sec21">
                <title>Reporting guidelines</title>
                <p>Repository: STROBE checklist for &#x2018;Could anemia impact the severity of infections? COVID-19 as an example&#x201d;. 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.5281/zenodo.10907120">https://doi.org/10.5281/zenodo.10907120</ext-link>
                </p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/publicdomain/zero/1.0/">Creative Commons Zero &#x201c;No rights reserved&#x201d; data waiver</ext-link> (CC0 1.0 Public domain dedication).</p>
            </sec>
        </sec>
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    </back>
    <sub-article article-type="reviewer-report" id="report337890">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.174189.r337890</article-id>
            <title-group>
                <article-title>Reviewer response for version 2</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Vives-Corrons</surname>
                        <given-names>Joan-Lluis</given-names>
                    </name>
                    <xref ref-type="aff" rid="r337890a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r337890a1">
                    <label>1</label>Red Cell Pathology and Haematopoietic Disorders (Rare Anaemias Unit), Institute for Leukaemia Research Josep Carreras (IJC), Barcelona, Spain</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>27</day>
                <month>11</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Vives-Corrons JL</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport337890" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.144790.2"/>
            <custom-meta-group>
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            </custom-meta-group>
        </front-stub>
        <body>
            <p>In my opinion, the authors have effectively addressed all the comments and suggestions provided, and accordingly, successfully incorporated them into the updated manuscript.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>I cannot comment. A qualified statistician is required.</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>NA</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.</p>
        </body>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report337891">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.174189.r337891</article-id>
            <title-group>
                <article-title>Reviewer response for version 2</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>McDonnell</surname>
                        <given-names>John</given-names>
                    </name>
                    <xref ref-type="aff" rid="r337891a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-7438-5471</uri>
                </contrib>
                <aff id="r337891a1">
                    <label>1</label>Pediatric Allergy and Immunology, Cleveland Clinic Children's Hospital, Cleveland, OH, USA</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>14</day>
                <month>11</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 McDonnell J</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport337891" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.144790.2"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>These changes look good to me.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Partly</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Partly</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Partly</p>
            <p>Reviewer Expertise:</p>
            <p>immunology, statistical methods</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.</p>
        </body>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report280551">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.158636.r280551</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>McDonnell</surname>
                        <given-names>John</given-names>
                    </name>
                    <xref ref-type="aff" rid="r280551a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-7438-5471</uri>
                </contrib>
                <aff id="r280551a1">
                    <label>1</label>Pediatric Allergy and Immunology, Cleveland Clinic Children's Hospital, Cleveland, OH, USA</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>9</day>
                <month>7</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 McDonnell J</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport280551" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.144790.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>This is an interesting study about the role of anemia in COVID-19 infection. It is overall well-written and scientifically important, but there are many small wording issues that if corrected will greatly enhance its clarity and readability.</p>
            <p> </p>
            <p> Additionally, there are a few more substantial statistical issues to consider. Because these affect the science behind the paper, I believe that they are very important for the authors to consider and address, even more so than the minor quibbles I list below about wording and grammar. Therefore, I have put these in bold.</p>
            <p> </p>
            <p> The most substantial statistical issue I have relates to the results section, where table 3 is referenced.</p>
            <p> </p>
            <p> 
                <bold>Author List</bold>:</p>
            <p> </p>
            <p> - The name "anan jarab" is not capitalized.</p>
            <p> - 
                <italic>Recommendation</italic>: Ensure consistent capitalization in the author list, e.g., "Anan Jarab&#x201d;, unless there is a specific reason not to.</p>
            <p> </p>
            <p> 
                <bold>Abstract</bold>:</p>
            <p> 
                <bold>Background</bold>:</p>
            <p> </p>
            <p> - The sentence "This is the first study UAE aimed to assess the influence of anemia on COVID-19 severity, ICU admission, and mortality rate." is unclear.</p>
            <p> - 
                <italic>Recommendation</italic>: Revise to "This is the first study from the UAE aimed to assess the influence of anemia on COVID-19 severity, ICU admission, and mortality rate."</p>
            <p> </p>
            <p> 
                <bold>Methods</bold>:</p>
            <p> - The term "retro-prospective chart review" is confusing.</p>
            <p> - 
                <italic>Recommendation</italic>: Use "retrospective chart review" for clarity.</p>
            <p> </p>
            <p> 
                <bold>Introduction</bold>:</p>
            <p> - this is a run-on sentence and is hard to understand - &#x00a0;"According to the National Emergency Crisis and Disasters Management Authority (NCEMA), more than 700 thousand cases were confirmed, and 2135 deaths were reported in the United Arab Emirates (UAE) until November, 4th 2021 and the rate of developing new cases has increased to 67.0% by 2023 although majority of the people are vaccinated against COVID-19."</p>
            <p> </p>
            <p> - 
                <italic>Recommendation</italic>: Break this into two sentences for clarity: "According to the National Emergency Crisis and Disasters Management Authority (NCEMA), more than 700 thousand cases were confirmed, and 2135 deaths were reported in the United Arab Emirates (UAE) until November 4th, 2021. The rate of new cases increased by 67.0% by 2023, despite the majority of the population being vaccinated against COVID-19."</p>
            <p> </p>
            <p> -This seems to be the wrong &#x201c;basis&#x201d;: "Genetic mutations of severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) resulted in the emergence of more contagious variants; hence, increasing cases on daily bases."</p>
            <p> - 
                <italic>Recommendation</italic>: Correct the word "bases" to "basis": "Genetic mutations of severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) resulted in the emergence of more contagious variants, hence increasing cases on a daily basis."</p>
            <p> </p>
            <p> - There is redundant wording in this sentence: "Moreover, studies evaluating parameters of severe outcomes failed to demonstrate truly this association in a large considerable sample size."</p>
            <p> - 
                <italic>Recommendation</italic>: Simplify to avoid redundancy: "Moreover, studies evaluating parameters of severe outcomes failed to demonstrate this association in a large sample size."</p>
            <p> </p>
            <p> 
                <bold>Ethical Considerations</bold>:</p>
            <p> - The wording here is problematic, as past and present tenses are mixed. The use of contractions is probably best avoided in a scientific paper: "Patients&#x2019; information was kept confidential and authors didn&#x2019;t have access to information that could identify individual participants during or after data collection. Study was performed in accordance with relevant guidelines and regulations. This was a retrospective review patients&#x2019; files and therefore consent form is waived and not required."</p>
            <p> </p>
            <p> - 
                <italic>Recommendation</italic>: Revise for consistent tense and avoid contractions: "Patients&#x2019; information was kept confidential, and the authors did not have access to information that could identify individual participants during or after data collection. The study was performed in accordance with relevant guidelines and regulations. This was a retrospective review of patients&#x2019; files; therefore, a consent form was waived and not required."</p>
            <p> </p>
            <p> 
                <bold>Data Collection</bold>:</p>
            <p> - This sentence is confusing, and the use of parentheses is incorrect: "Baseline vital signs upon admission (heart rate, respiratory rate, oxygen saturation, systolic, and diastolic blood pressure) in addition to the most relevant laboratory parameters to anemia, such as (hemoglobin, hematocrit, ferritin, D-dimer, and alkaline phosphatase) were reviewed and analyzed."</p>
            <p> - 
                <italic>Recommendation</italic>: Clarify and streamline the sentence: "Baseline vital signs upon admission, including heart rate, respiratory rate, oxygen saturation, and systolic and diastolic blood pressure, as well as key laboratory parameters related to anemia (hemoglobin, hematocrit, ferritin, D-dimer, and alkaline phosphatase), were reviewed and analyzed."</p>
            <p> </p>
            <p> 
                <bold>Table 2</bold>:</p>
            <p> - Issue: The row "Male 5.0% (120/2407) 1.58 1.00-2.51 0.028" 
                <bold>indicates a statistically significant adjusted odds ratio (aOR) with a confidence interval that includes 1.00</bold>. This does not make sense to me, as a confidence interval that includes 1 should not be significant by definition. Please correct me if I am wrong or I am missing something about the analysis.</p>
            <p> </p>
            <p> - 
                <italic>Recommendation</italic>: Verify the confidence interval and ensure that it does not include 1.00 if the result is statistically significant. If this is due to rounding, consider providing more precise values to clarify the significance.</p>
            <p> </p>
            <p> 
                <bold>Table 3</bold>:</p>
            <p> - The word "Normal" is followed by asterisks (*) that do not point to anything elsewhere in the table or text.</p>
            <p> - 
                <italic>Recommendation</italic>: Remove the asterisks if they are not referencing any footnotes or additional information or provide a clear explanation if they are meant to reference something.</p>
            <p> </p>
            <p> </p>
            <p> - Inconsistent use of percentages in "Covid 19 outcomes Severity of anemia % (n/N) P-Value Moderate to Severe Disease Normal* 21.6% (590/2730) &lt;0.001 Mild 30.3 (90/297) Moderate to Severe 29.3 (19/65)".</p>
            <p> - 
                <italic>Recommendation</italic>: Ensure percentages are used consistently throughout the table for clarity. For example: "Mild 30.3% (90/297) Moderate to Severe 29.3% (19/65)".</p>
            <p> </p>
            <p> 
                <bold>Results Section</bold> (Referencing Table 3):</p>
            <p> - This sentence is problematic: "Upon classifying patients anemia into normal, mild and moderate to severe; severity of COVID-19 was higher in anemic compared to normal patients (p &lt;0.001). On the other hand, moderate-to-severe anemia was associated with greater ICU admissions and mortality rates (p &lt;0.001) as presented in Table 3."</p>
            <p> -
                <bold>this is because a significant p-value indicates an overall difference in proportions among the groups as a whole (at least one of them is different, but we do not know which one) but does not specify which groups are different from each other</bold>. Which specific group is different cannot be verified without further post-hoc testing which probably should come at the cost of a statistical penalty for repeated comparisons (Bonferroni, etc).</p>
            <p> - 
                <italic>Recommendation</italic>: Clarify that the p-value here indicates an overall difference between subgroups and suggest that further post-hoc testing, such as Tukey's HSD, would be needed to identify specific group differences. Alternately perform such post-hoc testing and put the results in the table.</p>
            <p> </p>
            <p> 
                <bold>Table 4</bold>:</p>
            <p> - The confidence interval for "Gender (male) 1.43 1.15-178 &lt;0.001
                <bold>" appears to be unusually wide</bold>. I am wondering if this was due to a typographical error.</p>
            <p> - 
                <italic>Recommendation</italic>: Verify the correct confidence interval and revise it if necessary. For example: "Gender (male) 1.43 1.15-1.78 &lt;0.001".</p>
            <p> </p>
            <p> 
                <bold>Discussion</bold>:</p>
            <p> - Clarify this sentence: &#x00a0;"Based on the data collected from 3092 hospitalized adult patients in one of the largest hospitals in UAE, majority of the patients were males, 11.7% of whom were anemic."</p>
            <p> - 
                <italic>Recommendation</italic>: Change "majority" to "the majority": "Based on the data collected from 3092 hospitalized adult patients in one of the largest hospitals in the UAE, the majority of the patients were males, 11.7% of whom were anemic."</p>
            <p> </p>
            <p> - Clarify this sentence: "Interestingly, while Chen et al. demonstrated an increasing anemia prevalence with age, the prevalence then decreased at age of 80 and above years old; however, a small number of cohort was reported in that study."</p>
            <p> - 
                <italic>Recommendation</italic>: Change "a small number of cohort" to "a small cohort": "Interestingly, while Chen et al. demonstrated an increasing anemia prevalence with age, the prevalence then decreased at the age of 80 and above; however, a small cohort was reported in that study."</p>
            <p> </p>
            <p> - Clarify this sentence "The relationship between anemia and aging could be explained by common nutritional deficiencies (iron, folate, or vitamin B12), typically encountered with elderly or anemia of chronic diseases, and sometimes due to unknown reason."</p>
            <p> - 
                <italic>Recommendation</italic>: Pluralize "reason" to "reasons": "The relationship between anemia and aging could be explained by common nutritional deficiencies (iron, folate, or vitamin B12), typically encountered in the elderly or in cases of anemia of chronic diseases, and sometimes due to unknown reasons."</p>
            <p> </p>
            <p> - The abrupt start of this sentence is confusing: "Whereas, females have relatively low ferritin levels, beginning to rise after menopause."</p>
            <p> - 
                <italic>Recommendation</italic>: Simplify and clarify: "Females typically have relatively low ferritin levels, which begin to rise after menopause."</p>
            <p> </p>
            <p> - This sentence seems to be too strong. It is hard to say that a statistical model truly 
                <bold>proved</bold> this: "This was further proven by the results of a multivariable logistic regression after adjustment for covariates."</p>
            <p> - 
                <italic>Recommendation</italic>: Use a more appropriate term such as "supported" or "demonstrated": "This was further supported by the results of a multivariable logistic regression after adjustment for covariates."</p>
            <p> </p>
            <p> - Need a citation here: "Correspondingly, a single-center retrospective study assessed the impact of anemia on mortality rate among 333 hospitalized COVID-19 patients with anemia. The study has found that more than half of these patients were significantly at high risk of all-cause mortality."</p>
            <p> - 
                <italic>Recommendation</italic>: Add a citation: "Correspondingly, a single-center retrospective study assessed the impact of anemia on mortality rate among 333 hospitalized COVID-19 patients with anemia. The study found that more than half of these patients were significantly at high risk of all-cause mortality (Citation needed)."</p>
            <p> </p>
            <p> - Wording is awkward here: "Considering other factors, multivariable regression analysis revealed that male gender, older age (&#x2265;48-year-old), significantly increased the severity of COVID-19 and ICU admissions. However, only older age was found to be an independent risk factor in addition to anemia for mortality."</p>
            <p> </p>
            <p> - 
                <italic>Recommendation</italic>: Rework for clarity: "Multivariable regression analysis revealed that male gender and older age (&#x2265;48 years) significantly increased the severity of COVID-19 and ICU admissions. However, only older age, along with anemia, was found to be an independent risk factor for mortality."</p>
            <p> </p>
            <p> - I know what the authors mean here, but the way this sentence is worded is technically inaccurate. Our ability to interpret an association due to limitations in study design or analytic method do not actually affect the causal association itself, merely our ability to detect it: "This limited our interpretations and affected the causal association between anemia and COVID-19 outcomes."</p>
            <p> </p>
            <p> - 
                <italic>Recommendation</italic>: Clarify that the limitations were a barrier to assessing causality: "This limited our interpretations and were a barrier to assessing the causal association between anemia and COVID-19 outcomes."</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Partly</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Partly</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Partly</p>
            <p>Reviewer Expertise:</p>
            <p>immunology, statistical methods</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
        <sub-article article-type="response" id="comment12736-280551">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>aburuz</surname>
                            <given-names>salahdein</given-names>
                        </name>
                        <aff>College of Medicine, United Arab Emirates University, Al Ain, Abu Dhabi, United Arab Emirates</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>29</day>
                    <month>10</month>
                    <year>2024</year>
                </pub-date>
            </front-stub>
            <body>
                <p>
                    <bold>We truly appreciate the time and efforts you dedicated to reviewing our research work. Please note that all of your valuable comments have been addressed, and changes have been made in the manuscript accordingly. Many thanks</bold>
                </p>
                <p>
                    <bold> </bold>
                </p>
                <p>
                    <bold> Response to comments:</bold>
                </p>
                <p>
                    <bold> </bold>
                </p>
                <p>
                    <bold> 
                        <italic>Author List:</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>- The name "anan jarab" is not capitalized.</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Ensure consistent capitalization in the author list, e.g., "Anan Jarab&#x201d;, unless there is a specific reason not to.</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Modified the name to: &#x201c;Anan Jarab&#x201d; as recommended.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>Abstract:</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>Background:</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>- The sentence "This is the first study UAE aimed to assess the influence of anemia on COVID-19 severity, ICU admission, and mortality rate." is unclear.</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Revise to "This is the first study from the UAE aimed to assess the influence of anemia on COVID-19 severity, ICU admission, and mortality rate."</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Modified as recommended.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>Methods:</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- The term "retro-prospective chart review" is confusing.</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Use "retrospective chart review" for clarity.</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Modified as recommended.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>Introduction:</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- this is a run-on sentence and is hard to understand -&#x00a0; "According to the National Emergency Crisis and Disasters Management Authority (NCEMA), more than 700 thousand cases were confirmed, and 2135 deaths were reported in the United Arab Emirates (UAE) until November, 4th 2021 and the rate of developing new cases has increased to 67.0% by 2023 although majority of the people are vaccinated against COVID-19."</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Break this into two sentences for clarity: "According to the National Emergency Crisis and Disasters Management Authority (NCEMA), more than 700 thousand cases were confirmed, and 2135 deaths were reported in the United Arab Emirates (UAE) until November 4th, 2021. The rate of new cases increased by 67.0% by 2023, despite the majority of the population being vaccinated against COVID-19."</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Modified as recommended.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>-This seems to be the wrong &#x201c;basis&#x201d;: "Genetic mutations of severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) resulted in the emergence of more contagious variants; hence, increasing cases on daily bases."</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Correct the word "bases" to "basis": "Genetic mutations of severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) resulted in the emergence of more contagious variants, hence increasing cases on a daily basis."</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Modified as recommended.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>- There is redundant wording in this sentence: "Moreover, studies evaluating parameters of severe outcomes failed to demonstrate truly this association in a large considerable sample size."</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Simplify to avoid redundancy: "Moreover, studies evaluating parameters of severe outcomes failed to demonstrate this association in a large sample size."</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Modified as recommended.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>Ethical Considerations:</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- The wording here is problematic, as past and present tenses are mixed. The use of contractions is probably best avoided in a scientific paper: "Patients&#x2019; information was kept confidential and authors didn&#x2019;t have access to information that could identify individual participants during or after data collection. Study was performed in accordance with relevant guidelines and regulations. This was a retrospective review patients&#x2019; files and therefore consent form is waived and not required."</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Revise for consistent tense and avoid contractions: "Patients&#x2019; information was kept confidential, and the authors did not have access to information that could identify individual participants during or after data collection. The study was performed in accordance with relevant guidelines and regulations. This was a retrospective review of patients&#x2019; files; therefore, a consent form was waived and not required."</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Modified as recommended.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>Data Collection:</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- This sentence is confusing, and the use of parentheses is incorrect: "Baseline vital signs upon admission (heart rate, respiratory rate, oxygen saturation, systolic, and diastolic blood pressure) in addition to the most relevant laboratory parameters to anemia, such as (hemoglobin, hematocrit, ferritin, D-dimer, and alkaline phosphatase) were reviewed and analyzed."</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Clarify and streamline the sentence: "Baseline vital signs upon admission, including heart rate, respiratory rate, oxygen saturation, and systolic and diastolic blood pressure, as well as key laboratory parameters related to anemia (hemoglobin, hematocrit, ferritin, D-dimer, and alkaline phosphatase), were reviewed and analyzed."</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Modified as recommended.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>Table 2:</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Issue: The row "Male 5.0% (120/2407) 1.58 1.00-2.51 0.028" indicates a statistically significant adjusted odds ratio (aOR) with a confidence interval that includes 1.00. This does not make sense to me, as a confidence interval that includes 1 should not be significant by definition. Please correct me if I am wrong or I am missing something about the analysis.</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Verify the confidence interval and ensure that it does not include 1.00 if the result is statistically significant. If this is due to rounding, consider providing more precise values to clarify the significance.</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response: This was a system error, where all ORs were approximated to 2 decimal points. In this case, the value was 1.00095, that&#x2019;s why, it was presented as 1.00.</italic>
                </p>
                <p> 
                    <italic>So, we have modified it to be more precise.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>Table 3:</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- The word "Normal" is followed by asterisks (*) that do not point to anything elsewhere in the table or text.</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Remove the asterisks if they are not referencing any footnotes or additional information or provide a clear explanation if they are meant to reference something.</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Removed the asterisks (*) as recommended.</italic>
                </p>
                <p> </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>- Inconsistent use of percentages in "Covid 19 outcomes Severity of anemia % (n/N) P-Value Moderate to Severe Disease Normal* 21.6% (590/2730) &lt;0.001 Mild 30.3 (90/297) Moderate to Severe 29.3 (19/65)".</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Ensure percentages are used consistently throughout the table for clarity. For example: "Mild 30.3% (90/297) Moderate to Severe 29.3% (19/65)".</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Percentages (%) has been modified to be consistent throughout the table as recommended.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>Results Section (Referencing Table 3):</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- This sentence is problematic: "Upon classifying patients anemia into normal, mild and moderate to severe; severity of COVID-19 was higher in anemic compared to normal patients (p &lt;0.001). On the other hand, moderate-to-severe anemia was associated with greater ICU admissions and mortality rates (p &lt;0.001) as presented in Table 3."</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>-this is because a significant p-value indicates an overall difference in proportions among the groups as a whole (at least one of them is different, but we do not know which one) but does not specify which groups are different from each other. Which specific group is different cannot be verified without further post-hoc testing which probably should come at the cost of a statistical penalty for repeated comparisons (Bonferroni, etc).</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Clarify that the p-value here indicates an overall difference between subgroups and suggest that further post-hoc testing, such as Tukey's HSD, would be needed to identify specific group differences. Alternately perform such post-hoc testing and put the results in the table.</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Modified as recommended.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>Table 4:</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- The confidence interval for "Gender (male) 1.43 1.15-178 &lt;0.001" appears to be unusually wide. I am wondering if this was due to a typographical error.</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Verify the correct confidence interval and revise it if necessary. For example: "Gender (male) 1.43 1.15-1.78 &lt;0.001".</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response: Corrected as recommended.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>Discussion:</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Clarify this sentence:&#x00a0; "Based on the data collected from 3092 hospitalized adult patients in one of the largest hospitals in UAE, majority of the patients were males, 11.7% of whom were anemic."</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Change "majority" to "the majority": "Based on the data collected from 3092 hospitalized adult patients in one of the largest hospitals in the UAE, the majority of the patients were males, 11.7% of whom were anemic."</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Modified as recommended.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>- Clarify this sentence: "Interestingly, while Chen et al. demonstrated an increasing anemia prevalence with age, the prevalence then decreased at age of 80 and above years old; however, a small number of cohort was reported in that study."</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Change "a small number of cohort" to "a small cohort": "Interestingly, while Chen et al. demonstrated an increasing anemia prevalence with age, the prevalence then decreased at the age of 80 and above; however, a small cohort was reported in that study."</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Modified as recommended.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>- Clarify this sentence "The relationship between anemia and aging could be explained by common nutritional deficiencies (iron, folate, or vitamin B12), typically encountered with elderly or anemia of chronic diseases, and sometimes due to unknown reason."</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Pluralize "reason" to "reasons": "The relationship between anemia and aging could be explained by common nutritional deficiencies (iron, folate, or vitamin B12), typically encountered in the elderly or in cases of anemia of chronic diseases, and sometimes due to unknown reasons."</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Modified as recommended.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>- The abrupt start of this sentence is confusing: "Whereas, females have relatively low ferritin levels, beginning to rise after menopause."</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Simplify and clarify: "Females typically have relatively low ferritin levels, which begin to rise after menopause."</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Modified as recommended.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>- This sentence seems to be too strong. It is hard to say that a statistical model truly proved this: "This was further proven by the results of a multivariable logistic regression after adjustment for covariates."</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Use a more appropriate term such as "supported" or "demonstrated": "This was further supported by the results of a multivariable logistic regression after adjustment for covariates."</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Modified &#x201c;proven&#x201d; to &#x201c;supported&#x201d; as recommended.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>- Need a citation here: "Correspondingly, a single-center retrospective study assessed the impact of anemia on mortality rate among 333 hospitalized COVID-19 patients with anemia. The study has found that more than half of these patients were significantly at high risk of all-cause mortality."</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Add a citation: "Correspondingly, a single-center retrospective study assessed the impact of anemia on mortality rate among 333 hospitalized COVID-19 patients with anemia. The study found that more than half of these patients were significantly at high risk of all-cause mortality (Citation needed)."</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response: Added citation number &#x201c;8&#x201d; for "Correspondingly, a single-center retrospective study assessed the impact of anemia on mortality rate among 333 hospitalized COVID-19 patients with anemia. The study found that more than half of these patients were significantly at high risk of all-cause mortality (Citation needed)."</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>- Wording is awkward here: "Considering other factors, multivariable regression analysis revealed that male gender, older age (&#x2265;48-year-old), significantly increased the severity of COVID-19 and ICU admissions. However, only older age was found to be an independent risk factor in addition to anemia for mortality."</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Rework for clarity: "Multivariable regression analysis revealed that male gender and older age (&#x2265;48 years) significantly increased the severity of COVID-19 and ICU admissions. However, only older age, along with anemia, was found to be an independent risk factor for mortality."</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Modified as recommended.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>- I know what the authors mean here, but the way this sentence is worded is technically inaccurate. Our ability to interpret an association due to limitations in study design or analytic method do not actually affect the causal association itself, merely our ability to detect it: "This limited our interpretations and affected the causal association between anemia and COVID-19 outcomes."</italic>
                    </bold>
                </p>
                <p> 
                    <bold>
                        <italic>- Recommendation: Clarify that the limitations were a barrier to assessing causality: "This limited our interpretations and was a barrier to assessing the causal association between anemia and COVID-19 outcomes."</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Response:&#x00a0;Modified as recommended.</italic>
                </p>
            </body>
        </sub-article>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report272010">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.158636.r272010</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Vives-Corrons</surname>
                        <given-names>Joan-Lluis</given-names>
                    </name>
                    <xref ref-type="aff" rid="r272010a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r272010a1">
                    <label>1</label>Red Cell Pathology and Haematopoietic Disorders (Rare Anaemias Unit), Institute for Leukaemia Research Josep Carreras (IJC), Barcelona, Spain</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>24</day>
                <month>5</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Vives-Corrons JL</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport272010" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.144790.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>The manuscript provides valuable insights into the association between anemia and COVID-19 outcomes, supported by a large and well-characterized patient cohort. However, the limitations inherent in its retrospective, single-center design, and the lack of longitudinal and interventional data, suggest that further research is needed to confirm these findings and expand upon them. Future studies should aim for a prospective, multi-center approach, include longitudinal data, and consider the etiology of anemia to provide a more comprehensive understanding of this important health issue.</p>
            <p> Comments:</p>
            <p> 1. The retrospective observational design limits the ability to control for all possible confounding variables and to establish a causal relationship. Prospective studies or randomized controlled trials would provide stronger evidence</p>
            <p> 2. The study is conducted in a single center, which may limit the generalizability of the findings to other regions or healthcare settings. Multi-center studies would be more representative and enhance the external validity</p>
            <p> 3.The study does not track changes in hematological parameters over time during hospitalization. Longitudinal data would provide insights into the dynamics of anemia and its potential evolution in response to COVID-19.</p>
            <p> 4. The manuscript does not detail the clinical interventions and treatments related to anemia, which could influence patient outcomes. Understanding how anemia was managed during hospitalization would add depth to the analysis</p>
            <p> 5. The study does not differentiate between types of anemia (e.g., iron deficiency vs. anemia of inflammation). This distinction could impact the interpretation of the findings, as different types of anemia might have different effects on COVID-19 outcomes</p>
            <p> 6. While the study includes a diverse population in terms of gender and age, it does not address potential ethnic or socioeconomic factors that could influence both the prevalence of anemia and COVID-19 outcomes.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>I cannot comment. A qualified statistician is required.</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Rare Anemias</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
        <sub-article article-type="response" id="comment12735-272010">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>aburuz</surname>
                            <given-names>salahdein</given-names>
                        </name>
                        <aff>College of Medicine, United Arab Emirates University, Al Ain, Abu Dhabi, United Arab Emirates</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>29</day>
                    <month>10</month>
                    <year>2024</year>
                </pub-date>
            </front-stub>
            <body>
                <p>
                    <bold>We truly appreciate the time and efforts you dedicated to reviewing our research work. Please note that all of your valuable comments have been addressed, and changes have been made in the manuscript accordingly. Many thanks</bold>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>1. The retrospective observational design limits the ability to control for all possible confounding variables and to establish a causal relationship. Prospective studies or randomized controlled trials would provide stronger evidence</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Noted. This has been discussed in the limitations of the study, as the authors were unable to conduct this research prospectively since the pandemic was an emergency crisis for all COVID-19 patients as well as healthcare providers.</italic>
                    <bold>
                        <italic> </italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>2. The study is conducted in a single center, which may limit the generalizability of the findings to other regions or healthcare settings. Multi-center studies would be more representative and enhance the external validity.</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Noted. Since all COVID-19 patients that were included in this study were admitted to the ICU, it was a challenge that limited healthcare facilities treated such patients in the area, and all patients were sent to one center at the beginning of the crisis. We have also included this in the study limitation section.</italic>
                    <bold>
                        <italic> </italic>
                    </bold>
                </p>
                <p> </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>3.The study does not track changes in hematological parameters over time during hospitalization. Longitudinal data would provide insights into the dynamics of anemia and its potential evolution in response to COVID-19.</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Noted. This has been discussed in the limitations of the study, as the authors were unable to conduct this research prospectively since the pandemic was an emergency crisis for all COVID-19 patients as well as healthcare providers. Additionally, Hospital stay wasn&#x2019;t long enough to track changes. On the other hand, our goal was to see the impact of admission anemia on clinical outcomes.</italic>
                    <bold>
                        <italic> </italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>4. The manuscript does not detail the clinical interventions and treatments related to anemia, which could influence patient outcomes. Understanding how anemia was managed during hospitalization would add depth to the analysis.</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>During hospitalization, the treatment focused on the management of COVID-19, anemic patients were referred to specialists/consultants for further workup after their discharge. In case of severe anemia (HG &lt;7), patients have received blood transfusions as per the guidelines, however, this information was not part of the data collection.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>5. The study does not differentiate between types of anemia (e.g., iron deficiency vs. anemia of inflammation). This distinction could impact the interpretation of the findings, as different types of anemia might have different effects on COVID-19 outcomes</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>Noted. It was hard to differentiate the types of anemia as some patients may originally have had iron deficiency anemia and the condition worsened after the COVID-19 infection.</italic>
                </p>
                <p> </p>
                <p> 
                    <bold>
                        <italic>6. While the study includes a diverse population in terms of gender and age, it does not address potential ethnic or socioeconomic factors that could influence both the prevalence of anemia and COVID-19 outcomes.</italic>
                    </bold>
                </p>
                <p> </p>
                <p> 
                    <italic>This was the aim that has been discussed in another previously published study. It is also cited in this paper the discussion, Reference number 32.</italic>
                </p>
                <p> </p>
                <p> 
                    <italic>AbuRuz S, Al-Azayzih A, ZainAlAbdin S, et al.: Clinical characteristics and risk factors for mortality among COVID-19 hospitalized patients in UAE: Does ethnic origin have an impact. PLoS One. 2022;17(3):e0264547. 35235580 10.1371/journal.pone.0264547 PMC8890645</italic>
                </p>
            </body>
        </sub-article>
    </sub-article>
</article>
