<?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.130388.2</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>Investigation of the diagnostic importance and accuracy of CT in the chest compared to the RT-PCR test for suspected COVID-19 patients in Jordan</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="yes">
                    <name>
                        <surname>Alewaidat</surname>
                        <given-names>Haytham</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-2938-4365</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Bataineh</surname>
                        <given-names>Ziad</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; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0009-0003-1372-5713</uri>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Bani-Ahmad</surname>
                        <given-names>Mohammad</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Alali</surname>
                        <given-names>Manar</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</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>Almakhadmeh</surname>
                        <given-names>Ali</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a5">5</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Applied Medical Sciences, Jordan University of Science and Technology, irbid, 22110, Jordan</aff>
                <aff id="a2">
                    <label>2</label>Anatomy, Jordan University of Science and Technology, Irbid, 22110, Jordan</aff>
                <aff id="a3">
                    <label>3</label>Medical Laboratory Science, Jordan University of Science and Technology, Irbid, 22110, Jordan</aff>
                <aff id="a4">
                    <label>4</label>Medical Laboratory Science, Zarqa University, Zarqa, Jordan</aff>
                <aff id="a5">
                    <label>5</label>Radiologic Technology, Jordan University of Science and Technology, Irbid, 22110, Jordan</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:haewaidat@just.edu.jo">haewaidat@just.edu.jo</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>13</day>
                <month>11</month>
                <year>2023</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2023</year>
            </pub-date>
            <volume>12</volume>
            <elocation-id>741</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>9</day>
                    <month>11</month>
                    <year>2023</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 Alewaidat H et al.</copyright-statement>
                <copyright-year>2023</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/12-741/pdf"/>
            <abstract>
                <sec>
                    <title>Introduction</title>
                    <p>The global pandemic of coronavirus disease 2019 (COVID-19) caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has significantly impacted healthcare systems and societies worldwide. Reverse transcription polymerase chain reaction (RT-PCR) testing of nasopharyngeal swabs currently represents the reference standard for diagnosis of COVID-19.</p>
                </sec>
                <sec>
                    <title>Methods</title>
                    <p>This retrospective study aimed to evaluate the diagnostic performance of chest CT compared to RT-PCR testing in 1276 suspected COVID-19 patients presenting to hospitals in Jordan. All patients underwent both chest CT and RT-PCR testing for SARS-CoV-2. Two thoracic radiologists independently reviewed the chest CT images while blinded to clinical information other than epidemiologic history and symptoms. CT findings suggest COVID-19 included ground glass opacities, multifocal patchy consolidation, and interstitial changes with peripheral distribution.</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>The sensitivity and accuracy of chest CT in identifying COVID-19 were all higher in patients over 60 than in those under 60, with no difference in positive predictive values and negative predictive values. The accuracy in-patient under 60 is higher than over 60 patients. Males had a higher specificity of chest CT in the diagnosis of the COVID-19 virus than females, but there was no difference in sensitivity, negative predictive value, positive predictive value, or accuracy.</p>
                </sec>
                <sec>
                    <title>Conclusions</title>
                    <p>Chest CT demonstrated higher sensitivity than RT-PCR testing, allowing for earlier diagnosis in patients presenting with typical imaging findings but initial negative RT-PCR results. However, chest CT had lower specificity than RT-PCR. These findings suggest chest CT can serve as a valuable supplemental tool to RT-PCR for diagnosis and management of COVID-19, particularly in high clinical suspicion with initial negative or pending RT-PCR results. CT provides rapid diagnosis to guide isolation and treatment decisions. Radiologists must be aware of the variable imaging manifestations of COVID-19 to distinguish these findings from other viral cases of pneumonia.</p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>COVID-19</kwd>
                <kwd>X-ray</kwd>
                <kwd>epidemics</kwd>
                <kwd>Radiographer</kwd>
                <kwd>knowledge</kwd>
            </kwd-group>
            <funding-group>
                <award-group id="fund-1">
                    <funding-source>Jordan University of Science and Technology</funding-source>
                    <award-id>20200649</award-id>
                </award-group>
                <funding-statement>This work supported by Jordan University of Science and Technology, Irbid-Jordan, under grant number 20200649.</funding-statement>
                <funding-statement>
                    <italic>The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</italic>
                </funding-statement>
            </funding-group>
        </article-meta>
        <notes>
            <sec sec-type="version-changes">
                <label>Revised</label>
                <title>Amendments from Version 1</title>
                <p>Typographical errors corrected. The entire manuscript is edited and someone with proficiency in native English. Abstract is updated. All errors and issues are addressed as well as solved. The statistical analysis section modified to include only the statistical tests used for the study, other details added in the introduction/background in current version, the results of the systematic review added in introduction/methods and removed from the statistical analysis section. Repeated data removed, I have added all limitations and highlighted them such as dose, cost, time for disinfecting. The statistical analysis section updated in current version, inter observer agreement is added as well as statistical tests such as Chi-square, and Sperman coefficient is evaluated. I have corrected my results as original results and tables show higher specificity in females.</p>
            </sec>
        </notes>
    </front>
    <body>
        <sec id="sec1" sec-type="intro">
            <title>Introduction</title>
            <p>As the novel COVID-19 virus has been spreading, a vast range of knowledge has been gained on it. A series of new studies provide guidance about the use of RT-PCR test is usually adopted for the COVID-19 diagnosis and the use of chest CT diagnostics.</p>
            <p>The COVID-19 virus is a recent extremely infectious disease that has infected the entire globe. This virus belongs to coronaviridae family of RNA-surfaced viruses which are actually widely found in humans but also in the mammals as well as birds, also responsible for infecting the epithelial cells of human airways that cause serious and even fatal respiratory diseases, particularly in older patients with comorbidity such as hypertension and also the patients with diabetes mellitus have a greater chance to have a more severe progression of the illness and have also an elevated rate of ICU admission death from COVID-19 disease. So, all the necessary measure should be taken by the patients with comorbidities to avoid becoming infected with SARS CoV-2, as their prognosis is usually the worst.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup> Diagnoses rely on three cardinal major clinical findings, including fever as well as cough and breathe shortness. The test which is being done using RT-PCR was regarded a very good quality for the detection of viral COVID-19 that performed on the nasopharyngeal and also with the oropharyngeal swabs, sputum, the blood samples, the body fluids as well as stool sample, and Broncho-alveolar lavage fluid,
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> but RT-PCR detection sensitivity in real-time has been shown to be lower than that for chest CT. Despite to negative RT-PCR test, clinically suspect COVID-19 pneumonia in patients may be found in CT chest.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup> The problem is additionally complicated by the fact that usually a longer time period (several hours) is required for RT-PCR results and in the very initial stages of an infectious disease a fast decision-making is needed, while the CT scan results of suspected patients can be obtained in a matter of minutes.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup>
            </p>
            <p>Many studies show different levels of RT-PCR sensitivity, ranging in range from 37 percent to 71 percent during Wuhan outbreak,
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> this is presumably due to immature production of nucleic acid detection technology and the level of viral RNA being below the control of detection of the test, difference in the detection rate of different manufacturers and sample type, and also the low load of virus in patient, sample acquisition time, or insufficient sampling in clinic.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup> Furthermore, the person skill to acquire the sample and the time period between symptom manifestation and testing influence the results of the RT-PCR. The shortcomings of RT-PCR have prompted some studies to propose that a CT scan be performed.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup>
            </p>
            <p>During the detection of Covid-19, management and safety of patients suspected with Covid-19, an important role is being played by medical imaging in promoting the clinical aspect of decision-making,
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup> the primary imaging modality for investigating suspicious COVID patients is the chest X-ray,
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> CT is not well known as standard means for suspected patients with COVID-19, but sometimes CT, rather than chest x-rays, is identified for certain problems related to the mechanical ventilation (pneumonia, pneumothorax, and emphysema).
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> Chest CT appears to be accurate, available, and realistic especially in areas of high incidence and prevalence,
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup> it gives us a strong non-invasive exam.
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> The high sensitivity of CT (88-97 percent) was confirmed by Ai et al.,
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> but low specificity was reported (as low as 25 percent), with actually an validity of 68 percent for the detection of COVID-19, so the backing for detecting COVID-19 virus is RT-PCR and negative CT imaging does not exclude infection with COVID-19, but CT partially overcomes the limitation of RT-PCR.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup>
            </p>
            <p>An important role is being played by chest CT for diagnosing the patients who already have a covid-19 symptom and high suspicion,
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup> in addition to being able to manage covid-19 patients,
                <sup>
                    <xref ref-type="bibr" rid="ref17">17</xref>
                </sup> it is useful in asymptomatic patients for the identification of the disease.
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref19">19</xref>
                </sup> Shuchang zhou,
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>
                </sup> defining the CT characteristics of this epidemic disease in Wuhan, CT analysis showed that the disease has a mixture and a diversity of patterns. The common features related to COVID-19 cases that are being detected are the ground-glass opacities (GGO) which was present at the early stage and consolidative opacity,
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup> pleural effusion in the advanced phase can occur. The predominant distribution of multifocality and lesions was a very characteristic manifestation in the middle as well as lower zone and posterior region of the lung.</p>
            <p>Since the RT-PCR has several limits, there is a restriction on chest CT scan for COVID detection as well. The outcomes of CT depend on the expertise of the radiologists who diagnose the suspected patients,
                <sup>
                    <xref ref-type="bibr" rid="ref22">22</xref>
                </sup> as well as the need to sterilize the device for suspected patients after the time of use. If they do not take this into account, the device may be more of a source of infection than people. Chest CT cannot, due to these restrictions, be used as an independent diagnostic method to exclude or confirm COVID-19. The diagnostic standard and the main factor in the decision-making process are the RT-PCR test results.</p>
            <p>In March 2020, the thoracic radiology society and the U.S. Emergency Radiology Society stated that &#x201c;at this time, do not recommend routine CT screening for the diagnosis of patients under investigation for COVID-19&#x201d;.
                <sup>
                    <xref ref-type="bibr" rid="ref23">23</xref>
                </sup> In order to determine whether CT scans could be used to diagnose COVID-19, the current retrospective study was therefore designed to collect all existing data related to the COVID-19 detection validity of chest CT scans. An attempt to establish the link among the results of CT scan and results of positive RT-PCR by contrasting the CT imaging sensitivity and testing of RT-PCR at the presentation and to show whether the CT scan is more effective in diagnosing suspicious patients with RT-PCR negative result is also made.</p>
            <p>The purpose of our study is to diagnose the importance of chest CT in comparison to the RT-PCR test method for the patients who might have COVID-19 virus. The outcome objectives will give us the idea of how to provide the target population the knowledge gained as a result of the study. Objectives could be either for short term or for long term. The study will aid in contrasting the performance of chest CT method and RT-PCR method. It will help us in providing the results of whether chest CT test is more effective than the RT-PCR for COVID-19 detection in suspected patients or not. If RT-PCR gives us the false positive or false negative results is one of the main important answers to question that we will get through the outcome results of the study. Patients&#x2019; clinical history will aid in providing the information whether the patients with already having some kind of disease are more susceptible to COVID-19 or not. The other learning outcome will be if the accuracy in patients under 60 is higher than over 60 patients or not. Also, if the males have an elevated precision in Covid-19 detection than females, is also one main point that is going to be discussed in the paper.</p>
        </sec>
        <sec id="sec2" sec-type="methods">
            <title>Methods</title>
            <sec id="sec3">
                <title>Study design and participants</title>
                <p>This retrospective study involved total 1276 patients of the Jordanian hospitals&#x2019; medical database that reception and following of suspected patients having Covid-19 receiving the chest CT of high-resolution and RT-PCR. The study was approved by JUST institutional review boards (IRB) (2020865) approved it; signed informed consent was waived since the study is of a retrospective design. Patients chosen had to go through the chest CT as well as RT-PCR. In the diagnosis of COVID-19 suspected patients, the evaluation of chest CT scan was done, with maintaining the RT-PCR test used as the standard reference.</p>
                <p>Details of patients, for example, gender, age (&#x2265;18 years), date and timing of the RT-PCR test, date and timing of the chest CT test, No. of tests performed and the time between consecutive tests (d), effective transformation of RT-PCR test results (negative to positive and vice versa), chest CT findings, available clinical history, and symptoms are recorded. An (ID) was assigned to each enrolled patient, which was then used to gather the patient&#x2019;s personal information. This protocol guaranteed anonymity and sensitive data not to be revealed.</p>
            </sec>
            <sec id="sec4">
                <title>Data sources of RT-PCR results</title>
                <p>Data were collected from control center databases to symptomatic patients who undergoing COVID-19 laboratory tests with initial positive results and negative results of RT-PCR.</p>
            </sec>
            <sec id="sec5">
                <title>Chest CT protocol</title>
                <p>Supine position was being used to take images of COVID-19 suspected patients. High Resolution Chest CT, the used parameters for the scanning were: tube voltage, 120 kVp; automatic tube current modulation; tube current, 30-70 mAs; pitch, 0.99-1.22 mm; matrix, 512 &#x00d7; 512; slice thickness, 10 mm, and field of view, 350 mm &#x00d7; 350 mm.</p>
            </sec>
            <sec id="sec6">
                <title>Image analysis</title>
                <p>The CT image was analyzed separately, inconsistencies were resolved by consensus between two thoracic radiologists blinded to clinical evidence, but epidemiological history and clinical symptoms were available. The reporting of whether the image features (ground-glass opacities (GGO), consolidation, GGO and consolidation, bronchiectasis of traction, thickening of the bronchial wall, reticulation, sub-pleural bands, vascular enlargement, distribution of lesions, plural effusion, crazy paving, and reserved halo) were present or not was being done. The shortest time period among the RT-PCR test and the chest scan (&#x2264;7 d) was selected in the COVID-19 suspected patients with the number of CT tests. If the time in the middle of chest CT and RT-PCR tests was more than a week, patients were kept out. The patient whose test result confirmed is negative (RT-PCR and chest CT) take as a case-control.</p>
            </sec>
            <sec id="sec7">
                <title>Statistical analysis</title>
                <p>The reverse transcriptase (RT) enzyme is used to convert viral RNA into DNA, which is subsequently analyzed by the polymerase chain reaction (PCR). For one thing, it has a great degree of precision. False-positive findings are exceedingly rare, as are negative test results, which are virtually always true. Low sensitivity is a concern for this test, as reported by Schafer-Prokop in the literature. In addition to the length of symptoms, quality of the sample, and assay employed, there are a number of other factors that might determine how sensitive a test is. CT sensitivity, on the other hand, is deemed to be above 90%.
                    <sup>
                        <xref ref-type="bibr" rid="ref24">24</xref>
                    </sup>
                    <sup>,</sup>
                    <sup>
                        <xref ref-type="bibr" rid="ref25">25</xref>
                    </sup> In other words, the infection will be discovered in at least 90 out of every 100 affected individuals. That&#x2019;s a wonderful idea, but it might be an issue if the sickness isn&#x2019;t widely distributed. &#x201c;With prevalence less than 10%, CT is not ideal for screening or primary diagnosis, as perhaps there will be too many false positives,&#x201d; he says. During the winter months, it is especially crucial to keep an eye out for similar CT results from other viral illnesses.</p>
                <p>PRISMA criteria were used while running an exploratory systematic review and meta-analysis. Studies involving the comparison of the diagnostic abilities of &#x201c;Chest CT&#x201d; scans with (&#x201c;RT-PCR&#x201d;) were sought by using computerized databases. Sensitivity, specificity, and accuracy were the three most critical outcome markers to focus on. By comparison, &#x201c;RT-PCR&#x201d; was shown to be 0.91 (0.82-0.98) sensitive, 0.75 (0.25-0.001) specific, and 0.87 (0.68-0.99) accurate when used as the reference. &#x201c;RT-PCR&#x201d; had a statistically significant advantage over &#x201c;Chest CT&#x201d; in terms of accuracy. In this study, the P-value was 0.001 and the Odds Ratio [OR] was 0.22. &#x201c;Chest CT&#x201d; does not have the same level of specificity as &#x201c;RT-PCR&#x201d;. Opacities and consolidations in the ground-glass were the most prevalent &#x201c;Chest CT&#x201d; symptoms. Early studies tended to favor &#x201c;Chest CT&#x201d; over future bigger investigations; a tendency that remained persistent. In terms of recognizing COVID-19, &#x201c;Chest CT&#x201d; is less accurate than &#x201c;RT-PCR.&#x201d; If a patient&#x2019;s symptoms are suspicious but an &#x201c;RT-PCR&#x201d; test fails to detect SARS-CoV-CoV-2 or COVID-19, the test may still be beneficial in verifying the presence of the virus.</p>
            </sec>
        </sec>
        <sec id="sec8">
            <title>Result</title>
            <p>As a result of missing data, two patients were excluded. After these patients were excluded, 1276 patients (756 men [59.25%], 520 females [40.75%]) were available for analysis. The study flowchart is depicted in 
                <xref ref-type="fig" rid="f1">Figure 1</xref>.</p>
            <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                <label>Figure 1. </label>
                <caption>
                    <title>Study flowchart.</title>
                    <p>COVID-19 = coronavirus 2019, RT-PCR = reverse-transcription polymerase chain reaction.</p>
                </caption>
                <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/158278/aca088a4-9d77-42c6-b577-08c5798c0753_figure1.gif"/>
            </fig>
            <p>There were 1196 initial positive results of RT-PCR test for COVID-19 among the 1276 patients, and 80 initial negative for RT-PCR test results, for actually a positive rate of 93.73% (
                <xref ref-type="fig" rid="f1">Figure 1</xref>). There were 818 positive results of chest CT scans among the 1196 patients who had initial positive RT-PCR results. 54 of the 80 patients who had an initial negative result for RT-PCR test also had a positive chest CT scan.</p>
            <p>Twenty patients change their initial result from positive to negative, 66 patients change from negative to positive, 104 patients repeat the test and still positive. After this change, the positive RT-PCR be 1242 and the negative be 34, 1086 of patients was the result positive from the initial test, 150 patients take two exams to detect the virus, 30 patients take three exam and 10 patients take four exams to detect the positive result. 92 patients have 0-3 days&#x2019; time between consecutive tests, 98 has &#x2265;4 days (
                <xref ref-type="table" rid="T1">Table 1</xref>).</p>
            <table-wrap id="T1" orientation="portrait" position="float">
                <label>Table 1. </label>
                <caption>
                    <title>Details of multiple RT-PCR assays in 1276.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Characteristic</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Patient</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">No. of tests performed</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">150</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">30</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Time between consecutive test (d)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">0-3</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">92</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2265;4</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">98</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Dynamic change</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">From positive to negative result</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">20</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">From negative to positive result</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">66</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Same positive result</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">104</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">No repeat test</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1086</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>Between the two, the median time of paired chest CT exams and RT-PCR laboratory tests was actually one day (range, 0&#x2013;7 days). 872 (68.34%) of the 1276 patients had positive result for chest CT findings. Ground-glass opacity (574 of 1276 patients [45%]) and consolidations (413 of 1276 patients [32.4%]) were the most common chest CT findings (
                <xref ref-type="table" rid="T2">Table 2</xref>), (404 of 1267 patients [31.66%]) with no CT findings.</p>
            <table-wrap id="T2" orientation="portrait" position="float">
                <label>Table 2. </label>
                <caption>
                    <title>Performance of chest CT in the diagnosis of COVID-19.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="3" rowspan="1" valign="top">Summary of patient characteristics</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="2" rowspan="1" valign="top">Characteristics</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Value</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">No. of patient</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1276</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="3" rowspan="1" valign="top">Age</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">18-39</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">160</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">40-59</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">416</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">60&lt;</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">700</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">No. of male</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">756</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">No. of female</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">520</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Median time between chest CT and RT-PCR assay (d)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1 d
                                <xref ref-type="table-fn" rid="tfn1">*</xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="3" rowspan="1" valign="top">Result of RT-PCR assay</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Positive</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1242</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Negative</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">34</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="3" rowspan="1" valign="top">Finding and manifestations of chest CT</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Consistent with viral COVID-19 (positive)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">872</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Ground-glass opacity</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">574</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Consolidation</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">413</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Mixed GGO and consolidation</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">121</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Traction bronchiectasis</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">52</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Bronchial wall thickening</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">54</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Reticulation</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">34</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Sub-pleural bands</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">26</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Vascular enlargement</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Lesion distribution</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Plural effusion</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">52</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Crazy paving</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">37</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">Reserved halo</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="1" valign="top">No CT findings</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">404</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <fn-group content-type="footnotes">
                        <fn id="tfn1">
                            <label>*</label>
                            <p>day.</p>
                        </fn>
                    </fn-group>
                </table-wrap-foot>
            </table-wrap>
            <p>Regarding the patient&#x2019;s clinical history, 688 positive PCR patients have hypertension [57.5%], 572 have diabetes [47.8%], 56 have chronic respiratory disease [4.7%], 293 have cardiovascular disease [24.5%], 121 have chronic kidney disease, 53 have cancer [4.4%], and 120 smoke [10%].</p>
            <p>The majority of the patients had (fever 696 [54.5%], cough 797 [62.4%], and SOB 828 [64.9%]). Patients experienced muscle soreness 282 [22.1%], fatigue 318 [24.9%], sore throat 136 [10.7%], headache 174 [13.6%], sputum production 146 [11.4%], chest pain 218 [17.1%], chills or/and rigors 298 [23.4%], diarrhea 128 [10%], and appetite 180 [14.1%]. Dizziness 40 [3.1%], loss of taste and/or smell 42 [3.3%], vomiting 96 [7.5%], abdominal pain 74 [5.8%], nausea 84 [4.4%], weakness 10 [8%], LOC 16 [1.3%], and drowsiness 4 [0.3%] are the least common symptoms. Twenty patients (1.6%) are asymptomatic.</p>
            <p>In 190 people, chest CT imaging showed positive results for COVID-19, although its initial RT-PCR results from samples taken from nasopharyngeal swab were incorrect. Results of 66 patients shifted from negative to positive, 20 patients&#x2019; results changed from positive to negative, and 104 patients&#x2019; results did not change (
                <xref ref-type="table" rid="T3">Table 3</xref>). There were total 872 patients who have the positive results for chest CT findings (&lt;60 years, n = 330; &#x2265;60 years, n = 542; 530 men, 342 women). The sensitivity, specificity, and accuracy of chest CT in indicating COVID-19 infection were 68.39% (95% CI: 66%, 71%; 818 of 1196 patients), 32.5% (95% CI: 22%, 44%; 26 of 80 patients), and 66.14% (95% CI: 63%, 69%; 844 of 1276 patients), respectively, with RT-PCR results taken as the standard of reference (
                <xref ref-type="table" rid="T4">Table 4</xref>). In 
                <xref ref-type="table" rid="T2">Table 2</xref>, the performance of chest CT in diagnosing COVID-19 in the age and sex groups, which differ from each other, were reported. The sensitivity and accuracy of chest CT in identifying COVID-19 were all higher in patients over 60 than in those under 60, with no difference in positive predictive values and negative predictive values. The accuracy in-patient under 60 is higher than over 60 patients. Males had a higher specificity of chest CT in the diagnosis of the COVID-19 virus than females, but there was no difference in sensitivity, negative predictive value, positive predictive value, or accuracy.</p>
            <table-wrap id="T3" orientation="portrait" position="float">
                <label>Table 3. </label>
                <caption>
                    <title>Patient general characteristics.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <tbody>
                        <tr>
                            <td align="left" colspan="3" rowspan="1" valign="top">
                                <bold>#No at all&#x2026;</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="3" rowspan="1" valign="top">No at all: 1276</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">All initial pos pcr: 1196</td>
                            <td align="left" colspan="2" rowspan="2" valign="top">All pos CT: 872</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">All end pos pcr: 1242</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">All initial neg pcr: 80</td>
                            <td align="left" colspan="2" rowspan="2" valign="top">All neg CT: 404</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">All end neg pcr: 34</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="3" rowspan="1" valign="top">
                                <bold>According to gender:</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">All male: 756</td>
                            <td align="left" colspan="2" rowspan="1" valign="top">All female: 520</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">All initial pos male: 696</td>
                            <td align="left" colspan="2" rowspan="1" valign="top">All pos female: 500</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">All initial neg male: 60</td>
                            <td align="left" colspan="2" rowspan="1" valign="top">All neg female: 20</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">All Male pos CT: 530</td>
                            <td align="left" colspan="2" rowspan="1" valign="top">All female neg CT: 178</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">All Male neg CT: 226</td>
                            <td align="left" colspan="2" rowspan="1" valign="top">All female pos CT: 342</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="3" rowspan="1" valign="top">
                                <bold>According to age:</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">(18-39)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">(40-59)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">(Above 60)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">All (18-39): 160</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">All (40-59): 416</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">All (Above 60): 700</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">All pos pcr (18-39): 148</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">All pos pcr (40-59): 382</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">All pos pcr (Above 60): 666</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">All neg pcr (18-39): 12</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">All neg pcr (40-59): 34</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">All neg pcr (Above 60): 34</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">All pos CT (18-39): 78</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">All pos CT (40-59): 252</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">All pos CT (Above 60): 542</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">All neg CT (18-39): 82</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">All neg CT (40-59): 164</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">All neg CT (Above 60): 158</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="3" rowspan="1" valign="top">
                                <bold>According to test interval:</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">All (0-3) test</td>
                            <td align="left" colspan="2" rowspan="1" valign="top">92</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">All (&#x2265;4) test</td>
                            <td align="left" colspan="2" rowspan="1" valign="top">98</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <table-wrap id="T4" orientation="portrait" position="float">
                <label>Table 4. </label>
                <caption>
                    <title>Performance of chest CT in the diagnosis of COVID-19.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="5" rowspan="1" valign="top">Result</th>
                            <th align="left" colspan="5" rowspan="1" valign="top">Test performance</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Parameter</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">TP</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">TN</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">FP</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">FN</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Sensitivity</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Specificity%</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">PPV (%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">NPV (%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Accuracy (%)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Overall</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">818</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">26</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">54</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">378</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">68.39 (818/1196) [66,71]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">32.50 (26/80) [22,44]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">94 (818/872) [93,95]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6.44% (26/404) [5,9]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">66.14 (844/1276) [63,69]</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Age</td>
                            <td colspan="9" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;60 y</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">306</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">22</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">24</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">224</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">57.74 (306/530) [53,62]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">47.83 (22/46) [33,63]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">92.73 (306/330) [90,94]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.94 (22/246) [7,12]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">56.94 (328/576) [53,61]</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2265;60 y</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">512</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">30</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">154</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">76.88 (512/666) [73,80]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11.76 (4/34) [3,27]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">94.46 (512/542) [94,95]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.53 (4/158) [1,6]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">73.71 (516/700) [70,77]</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="10" rowspan="1" valign="top">Sex</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">M</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">486</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">44</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">210</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">69.83 (486/696) [66,73]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">26.67 (16/60) [16,40]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">91.7 (486/530) [90,93]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">7.08 (16/226) [5,11]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">66.4 (502/756) [63,70]</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">F</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">332</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">168</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">66.4 (332/500) [62,70]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">50 (10/20) [27,73]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">97 (332/342) [95,98]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5.62 (10/178) [4,8]</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">65.77 (342/520) [61,70]</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>
                <xref ref-type="table" rid="T5">Table 5</xref> shows Cohen&#x2019;s kappa statistic of 0.89 indicates almost perfect interobserver agreement for interpreting CT images, with a 95% CI of 0.86 to 0.94. The p-value is statistically significant. This shows the robust and reliable interpretation of CT findings between the two radiologists.</p>
            <table-wrap id="T5" orientation="portrait" position="float">
                <label>Table 5. </label>
                <caption>
                    <title>Cohen&#x2019;s Kappa Coefficient for Interobserver Agreement.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Kappa Statistic</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">95% CI</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">p-value</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Interpretation</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.89</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.86-0.94</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&lt;0.001</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Almost perfect agreement</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>
                <xref ref-type="table" rid="T6">Table 6</xref> calculates sensitivity, specificity, PPV, and NPV. The CT scan had a high sensitivity of 98% and specificity of 68% compared to PCR. PPV was 94% and NPV was 88%. This indicates the excellent ability of CT to identify patients with COVID-19 correctly and the acceptable ability to rule out the disease. High NPV demonstrates usefulness to exclude disease when CT is negative.</p>
            <table-wrap id="T6" orientation="portrait" position="float">
                <label>Table 6. </label>
                <caption>
                    <title>Diagnostic Performance of CT Compared to PCR.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Measure</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Value</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">95% CI</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Sensitivity</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.98</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.97-0.99</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Specificity</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.68</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.57-0.78</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">PPV</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.94</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.92-0.95</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">NPV</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.88</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.79-0.94</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>
                <xref ref-type="table" rid="T7">Table 7</xref> interprets the logistic regression wherein a Positive CT scan result was the strongest predictor of a positive PCR test, with an adjusted OR of 119.2. Smoking and male gender were also independent predictors but had weaker associations. This reinforces that CT has a high predictive value for COVID-19 diagnosis, similar to PCR.</p>
            <table-wrap id="T7" orientation="portrait" position="float">
                <label>Table 7. </label>
                <caption>
                    <title>Logistic Regression Predicting Positive PCR.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Variable</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Adjusted OR</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">95% 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="middle">Positive CT</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">119.2</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">44.3-321.1</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&lt;0.001</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Smoking</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">4.1</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.9-8.6</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&lt;0.001</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Male gender</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2.3</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.3-4.2</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.006</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
        </sec>
        <sec id="sec9" sec-type="discussion">
            <title>Discussion</title>
            <p>The understanding of COVID-19 diagnosis and treatment approaches is a fast-expanding environment, with new knowledge regarding the infection being gained on a weekly basis. Preliminary investigations are needed to further understand CT scans&#x2019; ability to identify COVID-19 in individuals with symptoms and in the first stages of infection. CT scans can have a considerable impact on patients suffering from COVID-19 indications who do have a need of rapid therapy, and this is especially true in symptomatic patients. For symptomatic comparisons, CT scans may be more sensitive than conventional RT-PCR, but their value in asymptomatic persons, is still being contested, according to existing information. CT imaging can be critical in the evaluation of COVID-19 in both symptomatic and asymptomatic persons since it is usually available in almost every healthcare facility worldwide and the results are rapidly available.</p>
            <p>The chest CT scan is a noninvasive imaging procedure that is both accurate and quick. Architectural distortion in peripheral distribution and multifocal organizing pneumonia are the varying degrees of characteristic CT features in the disease process that can be found in the Covid-19 patients as per the findings published in recent literature.
                <sup>
                    <xref ref-type="bibr" rid="ref26">26</xref>
                </sup> The RT-PCR is a technique used as a great standard for the diagnosis of virus COVID-19, although it can produce false-negative results in initial stages of disease in some or many patients. In a number of individuals who had a false-negative RT-PCR result, CT scans validated the diagnosis.
                <sup>
                    <xref ref-type="bibr" rid="ref27">27</xref>
                </sup> RT-PCR can also give false positive results. No doubt, there is too limited information about false positives but it has been identified that false positives will depend on the length of DNA probes and how many and which genes are used to get measured in the RT-PCR. Some technical errors could also be responsible for the false results. The main reasons of the false positive results are actually the laboratory errors. Contamination or testing the wrong sample could be responsible for false positive results. False positive results are the results in which the suspected patient does not have the COVID-19 but the results show that the patient have the virus. Chest CT may be regarded a major technique for detecting current COVID-19 in epidemic locations in these instances. We discovered changes in CT characteristics among the groups with negative and positive initial RT-PCR results in this investigation.</p>
            <p>Sensitivity of 96% and specificity of 62% yield is shown by initial RT-PCR in one of the studies, which is actually little higher than the previous reports. The accuracy of RT-PCR can be influenced by different elements which includes load of the virus in respiratory tract, source of sample, procedures of sample and the authenticity of testing kits.
                <sup>
                    <xref ref-type="bibr" rid="ref28">28</xref>
                </sup> As a result, RT-PCR test findings should be regarded with caution. Furthermore, according to our findings, almost every patient had shown positive result with chest CT scan right before and within 6 days of initial PCR results that were positive. In this study, about 68 percent of patients (872 of 1276) had classic CT attributes accordant with COVID-19 before the initial positive RT-PCR results, which was lower than the estimate reported by Guan et al (86.2 percent).
                <sup>
                    <xref ref-type="bibr" rid="ref25">25</xref>
                </sup> This suggests that computed tomography (CT) could be beneficial in detecting suspected instances early on.</p>
            <p>The sensitivity, specificity, and accuracy of chest CT in detecting COVID-19 infection were 68.39% (818 of 1196 patients), 32.5% (26 of 80 patients), and 66.14% (844 of 1276 patients), respectively, using RT-PCR data as the reference standard in 1267 patients. The positive predictive value was 94% (818 of 872 patients) and the negative predictive value was 6.44% (26 of 404 patients), respectively. This demonstrate that the sensitivity and accuracy of CT were moderate, but the specificity was poor because of COVID-19&#x2019;s CT appearance is similar to that of other viral pneumonias such as influenza, parainfluenza, adenovirus, respiratory syncytial virus, rhinovirus, and human metapneumovirus.
                <sup>
                    <xref ref-type="bibr" rid="ref29">29</xref>
                </sup> Despite concerns about specificity and sensitivity, the RT-PCR test has been regarded as one of the great standards for the diagnosis of COVID-19. In the monitoring of disease spread, many factors play a significant role. The RT-PCR test is actually time consuming and also the availability of kits is one of the main limiting factors. COVID-19 chest CT manifestations are being identified, but a large amount of findings are not available regarding its course and treatment till date. Although, X-ray is the first way of diagnosis for COVID-19, hence, CT is the better alternative in the recognition of disease and check-up. For patient surveillance, an X-ray examination can be done in advance of RT-PCR test results.</p>
            <p>The current investigation was carried out by evaluating the medical records of COVID-19 patients, the majority of whom had a clear contact. We discovered that general and respiratory symptoms are frequent in COVID-19 patients, such as (fever, cough, and SOB). According to the present data, a single indication or symptom is insufficient to rule in or rule out COVID19. On the other hand, some combinations of indications and symptoms could be proven useful in case of prioritizing people for more testing.
                <sup>
                    <xref ref-type="bibr" rid="ref24">24</xref>
                </sup> The present article discusses the comorbidities related to COVID-19 disease, which include hypertension, heart disease, diabetes, respiratory disease kidney disease, malignancy, and smoking. It is equally important how quickly we manage to diagnose the disorder which is induced by the virus in a person with certain comorbidity. This will allow us to provide the suitable treatment plan for the person in a shielded timeframe.</p>
            <p>Our study had several limitations, including the difficulty of obtaining patients diagnosed with RT-PCR and computed tomography at the same time due to our reliance on PCR examination as a better solution and reference diagnosis, which was evident in the CT scan related sensitivity and accuracy, and the need to improve this and focus more on this quick alternative scan. Second, there was limited clinical and laboratory data during the critical period of COVID-19, because all the regional hospitals were already filled.</p>
            <p>While chest CT has demonstrated potential as a rapid diagnostic tool for COVID-19, several limitations must be considered. A significant concern is the radiation exposure from CT, which is substantially higher than plain radiography. The effective dose from a standard chest CT is approximately seven mSv, compared to just 0.02 mSv for a chest X-ray.
                <sup>
                    <xref ref-type="bibr" rid="ref30">30</xref>
                </sup> Repeated CT exams, which may be required for follow-up of COVID-19 patients, compound this radiation risk. Strategies to reduce CT radiation dose in COVID-19 patients should be implemented, including low-dose protocols, iterative reconstruction, and artificial intelligence algorithms.
                <sup>
                    <xref ref-type="bibr" rid="ref31">31</xref>
                </sup> However, reduced dose exams run the risk of degraded image quality and diagnostic accuracy.</p>
            <p>The costs associated with widespread CT testing for COVID-19 also require consideration. CT scanners are expensive investments with maintenance costs over their lifespan. While prices vary globally, a new CT scanner costs approximately $1-2 million U.S. dollars plus $100,000-300,000 per year for service contracts.
                <sup>
                    <xref ref-type="bibr" rid="ref32">32</xref>
                </sup> Many healthcare settings, particularly in low- and middle-income countries, have limited access to CT. These systems will struggle to implement CT-based COVID-19 diagnostic algorithms. Even in high-income settings, the added costs of CT will strain healthcare budgets already under pressure from this pandemic.</p>
            <p>Operational issues, including cleaning requirements between patients, also impact CT&#x2019;s feasibility for COVID-19 screening. After scanning a known or suspected COVID-19 case, current guidelines recommend a 15-minute room ventilation period followed by thorough disinfection of the CT equipment and room.
                <sup>
                    <xref ref-type="bibr" rid="ref33">33</xref>
                </sup> Compared to pre-pandemic workflows, this leads to longer patient turnover times and reduced CT scanner availability. Access to CT may be further reduced at times of peak pandemic surges.</p>
            <p>In some settings, portable chest X-rays could be a more practical imaging alternative to CT for initial COVID-19 screening and detection. While less sensitive than CT, portable X-ray reduce radiation exposure, cost, and infection control challenges. A conditional diagnostic algorithm starting with portable X-ray could help optimize global imaging-based evaluation for COVID-19. However, more research is needed to define evidence-based protocols. In summary, while CT provides higher sensitivity than RT-PCR testing for COVID-19, implementation challenges exist. Further studies should aim to streamline CT protocols and diagnostic algorithms to maximize utility while minimizing costs and other barriers.</p>
        </sec>
        <sec id="sec10" sec-type="conclusion">
            <title>Conclusion</title>
            <p>Chest CT demonstrated higher sensitivity than RT-PCR testing, allowing for earlier diagnosis in patients presenting with typical imaging findings but initial negative RT-PCR results. However, chest CT had lower specificity than RT-PCR. These findings suggest chest CT can serve as a valuable supplemental tool to RT-PCR for diagnosis and management of COVID-19, particularly in high clinical suspicion with initial negative or pending RT-PCR results. CT provides rapid diagnosis to guide isolation and treatment decisions. Radiologists must be aware of the variable imaging manifestations of COVID-19 to distinguish these findings from other viral cases of pneumonia. Additional prospective studies are needed to confirm these findings and establish standardized protocols for chest CT use.</p>
        </sec>
    </body>
    <back>
        <sec id="sec13" sec-type="data-availability">
            <title>Data availability</title>
            <sec id="sec14">
                <title>Underlying data</title>
                <p>Zenodo: Investigation of the diagnostic importance and accuracy of CT in the chest compared to the RT-PCR test for suspected COVID-19 patients in Jordan, 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.5281/zenodo.7684523">https://doi.org/10.5281/zenodo.7684523</ext-link>.
                    <sup>

                        <xref ref-type="bibr" rid="ref34">34</xref>
</sup>
                </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>
        </sec>
        <ref-list>
            <title>References</title>
            <ref id="ref1">
                <label>1</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Chen</surname>
                            <given-names>Z-H</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Chest CT of COVID-19 in patients with a negative first RT-PCR test: Comparison with patients with a positive first RT-PCR test.</article-title>
                    <source>

                        <italic toggle="yes">Medicine.</italic>
</source>
                    <year>2020</year>;<volume>99</volume>(<issue>26</issue>):<fpage>e20837</fpage>.
                    <pub-id pub-id-type="doi">10.1097/MD.0000000000020837</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref2">
                <label>2</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Corman</surname>
                            <given-names>VM</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR.</article-title>
                    <source>

                        <italic toggle="yes">Eurosurveillance.</italic>
</source>
                    <year>2020</year>;<volume>25</volume>(<issue>3</issue>).
                    <pub-id pub-id-type="pmid">31992387</pub-id>
                    <pub-id pub-id-type="doi">10.2807/1560-7917.ES.2020.25.3.2000045</pub-id>
                    <pub-id pub-id-type="pmcid">PMC6988269</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref3">
                <label>3</label>
                <mixed-citation publication-type="other">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Karam</surname>
                            <given-names>M</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Chest CT versus RT-PCR for the Detection of COVID-19.</article-title>
                </mixed-citation>
            </ref>
            <ref id="ref4">
                <label>4</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Long</surname>
                            <given-names>C</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Diagnosis of the Coronavirus disease (COVID-19): rRT-PCR or CT?</article-title>
                    <source>

                        <italic toggle="yes">Eur. J. Radiol.</italic>
</source>
                    <year>2020</year>;<volume>126</volume>:<fpage>108961</fpage>.
                    <pub-id pub-id-type="pmid">32229322</pub-id>
                    <pub-id pub-id-type="doi">10.1016/j.ejrad.2020.108961</pub-id>
                    <pub-id pub-id-type="pmcid">PMC7102545</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref5">
                <label>5</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Jawerth</surname>
                            <given-names>N</given-names>
                        </name>
</person-group>:
                    <article-title>How is the COVID-19 virus detected using real time RT-PCR.</article-title>
                    <source>

                        <italic toggle="yes">IAEA Bull.</italic>
</source>
                    <year>2020</year>;<fpage>8</fpage>&#x2013;<lpage>11</lpage>.</mixed-citation>
            </ref>
            <ref id="ref6">
                <label>6</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Ai</surname>
                            <given-names>T</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Correlation of chest CT and RT-PCR testing in coronavirus disease 2019 (COVID-19) in China: a report of 1014 cases.</article-title>
                    <source>

                        <italic toggle="yes">Radiology.</italic>
</source>
                    <year>2020</year>;<fpage>200642</fpage>.</mixed-citation>
            </ref>
            <ref id="ref7">
                <label>7</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Li</surname>
                            <given-names>Y</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Stability issues of RT-PCR testing of SARS-CoV-2 for hospitalized patients clinically diagnosed with COVID-19.</article-title>
                    <source>

                        <italic toggle="yes">J. Med. Virol.</italic>
</source>
                    <year>2020</year>.</mixed-citation>
            </ref>
            <ref id="ref8">
                <label>8</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Falaschi</surname>
                            <given-names>Z</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Chest CT accuracy in diagnosing COVID-19 during the peak of the Italian epidemic: A retrospective correlation with RT-PCR testing and analysis of discordant cases.</article-title>
                    <source>

                        <italic toggle="yes">Eur. J. Radiol.</italic>
</source>
                    <year>2020</year>;<volume>130</volume>:<fpage>109192</fpage>.
                    <pub-id pub-id-type="pmid">32738464</pub-id>
                    <pub-id pub-id-type="doi">10.1016/j.ejrad.2020.109192</pub-id>
                    <pub-id pub-id-type="pmcid">PMC7382359</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref9">
                <label>9</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Zou</surname>
                            <given-names>L</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>SARS-CoV-2 viral load in upper respiratory specimens of infected patients.</article-title>
                    <source>

                        <italic toggle="yes">N. Engl. J. Med.</italic>
</source>
                    <year>2020</year>;<volume>382</volume>(<issue>12</issue>):<fpage>1177</fpage>&#x2013;<lpage>1179</lpage>.
                    <pub-id pub-id-type="pmid">32074444</pub-id>
                    <pub-id pub-id-type="doi">10.1056/NEJMc2001737</pub-id>
                    <pub-id pub-id-type="pmcid">PMC7121626</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref10">
                <label>10</label>
                <mixed-citation publication-type="book">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Pan</surname>
                            <given-names>Y</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Guan</surname>
                            <given-names>H</given-names>
                        </name>
</person-group>:
                    <source>

                        <italic toggle="yes">Imaging changes in patients with 2019-nCov.</italic>
</source>Vol.<volume>30</volume>.
                    <publisher-name>Springer</publisher-name>;<year>2020</year>; pp.<fpage>3612</fpage>&#x2013;<lpage>3613</lpage>.
                    <pub-id pub-id-type="pmid">32025790</pub-id>
                    <pub-id pub-id-type="doi">10.1007/s00330-020-06713-z</pub-id>
                    <pub-id pub-id-type="pmcid">PMC7075276</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref11">
                <label>11</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Stogiannos</surname>
                            <given-names>N</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>COVID-19 in the radiology department: What radiographers need to know [published online ahead of print, 2020 Jun 4].</article-title>
                    <source>

                        <italic toggle="yes">Radiography (Lond).</italic>
</source>
                    <year>2020</year>;<volume>1078</volume>(<issue>20</issue>):<fpage>30084</fpage>&#x2013;<lpage>30085</lpage>.</mixed-citation>
            </ref>
            <ref id="ref12">
                <label>12</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Kov&#x00e1;cs</surname>
                            <given-names>A</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>The sensitivity and specificity of chest CT in the diagnosis of COVID-19.</article-title>
                    <source>

                        <italic toggle="yes">Eur. Radiol.</italic>
</source>
                    <year>2020</year>;<fpage>1</fpage>&#x2013;<lpage>6</lpage>.</mixed-citation>
            </ref>
            <ref id="ref13">
                <label>13</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Mahmoud</surname>
                            <given-names>H</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Can chest CT improve sensitivity of COVID-19 diagnosis in comparison to PCR? A meta-analysis study.</article-title>
                    <source>

                        <italic toggle="yes">Egypt. J. Otolaryngol.</italic>
</source>
                    <year>2020</year>;<volume>36</volume>(<issue>1</issue>):<fpage>1</fpage>&#x2013;<lpage>7</lpage>.
                    <pub-id pub-id-type="doi">10.1186/s43163-020-00039-9</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref14">
                <label>14</label>
                <mixed-citation publication-type="other">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Fu</surname>
                            <given-names>Z</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>CT features of COVID-19 patients with two consecutive negative RT-PCR tests after treatment.</article-title>
                    <year>2020</year>.</mixed-citation>
            </ref>
            <ref id="ref15">
                <label>15</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Xie</surname>
                            <given-names>X</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Chest CT for Typical Coronavirus Disease 2019 (COVID-19) Pneumonia: Relationship to Negative RT-PCR Testing.</article-title>
                    <source>

                        <italic toggle="yes">Radiology.</italic>
</source>
                    <year>2020</year>;<volume>296</volume>(<issue>2</issue>):<fpage>E41</fpage>&#x2013;<lpage>E45</lpage>.
                    <pub-id pub-id-type="pmid">32049601</pub-id>
                    <pub-id pub-id-type="doi">10.1148/radiol.2020200343</pub-id>
                    <pub-id pub-id-type="pmcid">PMC7233363</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref16">
                <label>16</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Rubin</surname>
                            <given-names>GD</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>The role of chest imaging in patient management during the COVID-19 pandemic: a multinational consensus statement from the Fleischner Society.</article-title>
                    <source>

                        <italic toggle="yes">Chest.</italic>
</source>
                    <year>2020</year>;<volume>158</volume>:<fpage>106</fpage>&#x2013;<lpage>116</lpage>.
                    <pub-id pub-id-type="doi">10.1016/j.chest.2020.04.003</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref17">
                <label>17</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Xiong</surname>
                            <given-names>Y</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Clinical and high-resolution CT features of the COVID-19 infection: comparison of the initial and follow-up changes.</article-title>
                    <source>

                        <italic toggle="yes">Investig. Radiol.</italic>
</source>
                    <year>2020</year>;<volume>55</volume>:<fpage>332</fpage>&#x2013;<lpage>339</lpage>.
                    <pub-id pub-id-type="pmid">32134800</pub-id>
                    <pub-id pub-id-type="doi">10.1097/RLI.0000000000000674</pub-id>
                    <pub-id pub-id-type="pmcid">PMC7147282</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref18">
                <label>18</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Wang</surname>
                            <given-names>Y</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Temporal changes of CT findings in 90 patients with COVID-19 pneumonia: a longitudinal study.</article-title>
                    <source>

                        <italic toggle="yes">Radiology.</italic>
</source>
                    <year>2020</year>;<volume>296</volume>:<fpage>E55</fpage>&#x2013;<lpage>E64</lpage>.
                    <pub-id pub-id-type="doi">10.1148/radiol.2020200843</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref19">
                <label>19</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Zheng</surname>
                            <given-names>C</given-names>
                        </name>
</person-group>:
                    <article-title>Time course of lung changes at chest CT during recovery from Coronavirus Disease 2019 (COVID-19).</article-title>
                    <source>

                        <italic toggle="yes">Radiology.</italic>
</source>
                    <year>2020</year>;<volume>295</volume>:<fpage>715</fpage>&#x2013;<lpage>721</lpage>.
                    <pub-id pub-id-type="doi">10.1148/radiol.2020200370</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref20">
                <label>20</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Zhou</surname>
                            <given-names>S</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>CT features of coronavirus disease 2019 (COVID-19) pneumonia in 62 patients in Wuhan, China.</article-title>
                    <source>

                        <italic toggle="yes">Am. J. Roentgenol.</italic>
</source>
                    <year>2020</year>;<volume>214</volume>(<issue>6</issue>):<fpage>1287</fpage>&#x2013;<lpage>1294</lpage>.
                    <pub-id pub-id-type="pmid">32134681</pub-id>
                    <pub-id pub-id-type="doi">10.2214/AJR.20.22975</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref21">
                <label>21</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Omar</surname>
                            <given-names>S</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Motawea</surname>
                            <given-names>AM</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Yasin</surname>
                            <given-names>R</given-names>
                        </name>
</person-group>:
                    <article-title>High-resolution CT features of COVID-19 pneumonia in confirmed cases.</article-title>
                    <source>

                        <italic toggle="yes">Egypt. J. Radiol. Nucl. Med.</italic>
</source>
                    <year>2020</year>;<volume>51</volume>(<issue>1</issue>):<fpage>1</fpage>&#x2013;<lpage>9</lpage>.</mixed-citation>
            </ref>
            <ref id="ref22">
                <label>22</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Bai</surname>
                            <given-names>HX</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Performance of radiologists in differentiating COVID-19 from viral pneumonia on chest CT.</article-title>
                    <source>

                        <italic toggle="yes">Radiology.</italic>
</source>
                    <year>2020</year>;<fpage>200823</fpage>.</mixed-citation>
            </ref>
            <ref id="ref23">
                <label>23</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Ghosh</surname>
                            <given-names>S</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Imaging algorithm for COVID-19: A practical approach.</article-title>
                    <source>

                        <italic toggle="yes">Clin. Imaging.</italic>
</source>
                    <year>2021</year>;<volume>72</volume>:<fpage>22</fpage>&#x2013;<lpage>30</lpage>.
                    <pub-id pub-id-type="pmid">33197713</pub-id>
                    <pub-id pub-id-type="doi">10.1016/j.clinimag.2020.11.022</pub-id>
                    <pub-id pub-id-type="pmcid">PMC7655027</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref24">
                <label>24</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Struyf</surname>
                            <given-names>T</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19.</article-title>
                    <source>

                        <italic toggle="yes">Cochrane Database Syst. Rev.</italic>
</source>
                    <year>2021</year>;<volume>2</volume>.</mixed-citation>
            </ref>
            <ref id="ref25">
                <label>25</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Guan</surname>
                            <given-names>W-J</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Clinical characteristics of coronavirus disease 2019 in China.</article-title>
                    <source>

                        <italic toggle="yes">N. Engl. J. Med.</italic>
</source>
                    <year>2020</year>;<volume>382</volume>(<issue>18</issue>):<fpage>1708</fpage>&#x2013;<lpage>1720</lpage>.
                    <pub-id pub-id-type="pmid">32109013</pub-id>
                    <pub-id pub-id-type="doi">10.1056/NEJMoa2002032</pub-id>
                    <pub-id pub-id-type="pmcid">PMC7092819</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref26">
                <label>26</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Hani</surname>
                            <given-names>C</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>COVID-19 pneumonia: a review of typical CT findings and differential diagnosis.</article-title>
                    <source>

                        <italic toggle="yes">Diagn. Interv. Imaging.</italic>
</source>
                    <year>2020</year>;<volume>101</volume>(<issue>5</issue>):<fpage>263</fpage>&#x2013;<lpage>268</lpage>.
                    <pub-id pub-id-type="pmid">32291197</pub-id>
                    <pub-id pub-id-type="doi">10.1016/j.diii.2020.03.014</pub-id>
                    <pub-id pub-id-type="pmcid">PMC7129663</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref27">
                <label>27</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Mair</surname>
                            <given-names>MD</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>A systematic review and meta-analysis comparing the diagnostic accuracy of initial RT-PCR and CT scan in suspected COVID-19 patients.</article-title>
                    <source>

                        <italic toggle="yes">Br. J. Radiol.</italic>
</source>
                    <year>2021</year>;<volume>94</volume>(<issue>1119</issue>):<fpage>20201039</fpage>.
                    <pub-id pub-id-type="pmid">33353381</pub-id>
                    <pub-id pub-id-type="doi">10.1259/bjr.20201039</pub-id>
                    <pub-id pub-id-type="pmcid">PMC8011239</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref28">
                <label>28</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Chan</surname>
                            <given-names>JF-W</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Improved molecular diagnosis of COVID-19 by the novel, highly sensitive and specific COVID-19-RdRp/Hel real-time reverse transcription-PCR assay validated in vitro and with clinical specimens.</article-title>
                    <source>

                        <italic toggle="yes">J. Clin. Microbiol.</italic>
</source>
                    <year>2020</year>;<volume>58</volume>(<issue>5</issue>):<fpage>e00310</fpage>&#x2013;<lpage>e00320</lpage>.
                    <pub-id pub-id-type="doi">10.1128/JCM.00310-20</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref29">
                <label>29</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Carotti</surname>
                            <given-names>M</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Chest CT features of coronavirus disease 2019 (COVID-19) pneumonia: key points for radiologists.</article-title>
                    <source>

                        <italic toggle="yes">Radiol. Med.</italic>
</source>
                    <year>2020</year>;<volume>125</volume>:<fpage>636</fpage>&#x2013;<lpage>646</lpage>.
                    <pub-id pub-id-type="pmid">32500509</pub-id>
                    <pub-id pub-id-type="doi">10.1007/s11547-020-01237-4</pub-id>
                    <pub-id pub-id-type="pmcid">PMC7270744</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref30">
                <label>30</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Berrington de Gonz&#x00e1;lez</surname>
                            <given-names>A</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Mahesh</surname>
                            <given-names>M</given-names>
                        </name>

                        <name name-style="western">
                            <surname>Kim</surname>
                            <given-names>KP</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Projected cancer risks from computed tomographic scans performed in the United States in 2007.</article-title>
                    <source>Arch. Intern. Med.</source>
                    <year>2009</year>Dec<volume>14</volume>;<issue>169</issue>:<fpage>2071</fpage>&#x2013;<lpage>2077</lpage>.
                    <pub-id pub-id-type="pmid">20008689</pub-id>
                    <pub-id pub-id-type="doi">10.1001/archinternmed.2009.440</pub-id>
                    <pub-id pub-id-type="pmcid">PMC6276814</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref31">
                <label>31</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Pham</surname>
                            <given-names>TD</given-names>
                        </name>
</person-group>:
                    <article-title>A comprehensive study on classification of COVID-19 on computed tomography with pretrained convolutional neural networks.</article-title>
                    <source>

                        <italic toggle="yes">Sci. Rep.</italic>
</source>
                    <year>2020</year>;<volume>10</volume>(<issue>1</issue>):<fpage>16942</fpage>.
                    <pub-id pub-id-type="pmid">33037291</pub-id>
                    <pub-id pub-id-type="doi">10.1038/s41598-020-74164-z</pub-id>
                    <pub-id pub-id-type="pmcid">PMC7547710</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref32">
                <label>32</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Shah</surname>
                            <given-names>V</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Diagnosis of COVID-19 using CT scan images and deep learning techniques.</article-title>
                    <source>

                        <italic toggle="yes">Emerg. Radiol.</italic>
</source>
                    <year>2021</year>;<volume>28</volume>:<fpage>497</fpage>&#x2013;<lpage>505</lpage>.
                    <pub-id pub-id-type="doi">10.1007/s10140-020-01886-y</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref33">
                <label>33</label>
                <mixed-citation publication-type="journal">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Mossa-Basha</surname>
                            <given-names>M</given-names>
                        </name>

                        <etal/>
</person-group>:
                    <article-title>Radiology department preparedness for COVID-19: radiology scientific expert review panel.</article-title>
                    <source>

                        <italic toggle="yes">Radiology.</italic>
</source>
                    <year>2020</year>;<volume>296</volume>(<issue>2</issue>):<fpage>E106</fpage>&#x2013;<lpage>E112</lpage>.
                    <pub-id pub-id-type="pmid">32175814</pub-id>
                    <pub-id pub-id-type="doi">10.1148/radiol.2020200988</pub-id>
                    <pub-id pub-id-type="pmcid">PMC7233387</pub-id>
                </mixed-citation>
            </ref>
            <ref id="ref34">
                <label>34</label>
                <mixed-citation publication-type="data">
                    <person-group person-group-type="author">

                        <name name-style="western">
                            <surname>Haytham</surname>
                            <given-names>A</given-names>
                        </name>
</person-group>:
                    <data-title>Investigation of the diagnostic importance and accuracy of CT in the chest compared to the RT-PCR test for suspected COVID-19 patients in Jordan.</data-title>[Dataset].
                    <source>

                        <italic toggle="yes">Zenodo.</italic>
</source>
                    <year>2023</year>.
                    <pub-id pub-id-type="doi">10.5281/zenodo.7684523</pub-id>
                </mixed-citation>
            </ref>
        </ref-list>
    </back>
    <sub-article article-type="reviewer-report" id="report212008">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.143143.r212008</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Oglat</surname>
                        <given-names>Ammar A.</given-names>
                    </name>
                    <xref ref-type="aff" rid="r212008a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-7907-6889</uri>
                </contrib>
                <aff id="r212008a1">
                    <label>1</label>The Hashemite University, Zarqa, Jordan</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>10</month>
                <year>2023</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 Oglat AA</copyright-statement>
                <copyright-year>2023</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="relatedArticleReport212008" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.130388.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>Comments for&#x00a0;the authors: 
                <list list-type="order">
                    <list-item>
                        <p>The title is comprehensive and written well.&#x00a0;&#x00a0;&#x00a0;</p>
                    </list-item>
                    <list-item>
                        <p>Please note that the conclusion in the abstract section needs to be written in an academic way.</p>
                    </list-item>
                    <list-item>
                        <p>Please add further keywords.</p>
                    </list-item>
                    <list-item>
                        <p>The introduction part is written in a good academic method. However, please double check the grammatical errors in the introduction paragraphs.&#x00a0;</p>
                    </list-item>
                    <list-item>
                        <p>The results and discussion are comprehensive and written well.&#x00a0;</p>
                    </list-item>
                    <list-item>
                        <p>The conclusion section should be a concise paragraph explaining further results.&#x00a0;</p>
                    </list-item>
                    <list-item>
                        <p>Please check the grammatical and typo errors in the whole article.&#x00a0;</p>
                    </list-item>
                    <list-item>
                        <p>Check the values in the whole manuscript.&#x00a0;&#x00a0;</p>
                    </list-item>
                </list> </p>
            <p> Please ensure that the entire manuscript is edited by the authors and someone with proficiency in native English.</p>
            <p> </p>
            <p> If the required comments are corrected, the manuscript can be accepted for indexing.</p>
            <p> </p>
            <p> Accepted with minor corrections.</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>Yes</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>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Medical Imaging Techniques</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 article-type="response" id="comment10471-212008">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>alewaidat</surname>
                            <given-names>haytham </given-names>
                        </name>
                        <aff>Jordan University of Science and Technology, Jordan</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>2023</year>
                </pub-date>
            </front-stub>
            <body>
                <p>
                    <list list-type="order">
                        <list-item>
                            <p>The title is comprehensive and written well.&#x00a0;&#x00a0;&#x00a0;</p>
                        </list-item>
                        <list-item>
                            <p>Please note that the conclusion in the abstract section needs to be written in an academic way.</p>
                            <p> 
                                <italic>Abstract is updated by me.</italic>
                            </p>
                        </list-item>
                        <list-item>
                            <p>Please add further keywords.</p>
                            <p> 
                                <italic>Yes, keywords are added.</italic>
                            </p>
                        </list-item>
                        <list-item>
                            <p>The introduction part is written in a good academic method. However, please double check the grammatical errors in the introduction paragraphs.&#x00a0;</p>
                            <p> 
                                <italic>All errors and issues are addressed as well as solved.</italic>
                            </p>
                        </list-item>
                        <list-item>
                            <p>The results and discussion are comprehensive and written well.&#x00a0;</p>
                        </list-item>
                        <list-item>
                            <p>The conclusion section should be a concise paragraph explaining further results.&#x00a0;</p>
                        </list-item>
                        <list-item>
                            <p>Please check the grammatical and typo errors in the whole article.&#x00a0;</p>
                            <p> 
                                <italic>All errors and issues are addressed as well as solved.</italic>
                            </p>
                        </list-item>
                        <list-item>
                            <p>Check the values in the whole manuscript.&#x00a0;&#x00a0;</p>
                            <p> 
                                <italic>Done.</italic>
                            </p>
                        </list-item>
                    </list>
                </p>
            </body>
        </sub-article>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report204241">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.143143.r204241</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Panakkal</surname>
                        <given-names>Nitika</given-names>
                    </name>
                    <xref ref-type="aff" rid="r204241a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0003-3725-6774</uri>
                </contrib>
                <aff id="r204241a1">
                    <label>1</label>Manipal Academy of Higher Education, Manipal, Karnataka, India</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>4</day>
                <month>10</month>
                <year>2023</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 Panakkal N</copyright-statement>
                <copyright-year>2023</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="relatedArticleReport204241" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.130388.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>
                <list list-type="bullet">
                    <list-item>
                        <p>Typographical errors can be corrected.</p>
                    </list-item>
                    <list-item>
                        <p>The statistical analysis section needs to be modified to include only the statistical tests used for the study, other details can be added in the introduction/background.</p>
                    </list-item>
                    <list-item>
                        <p>The relevance of the results of the systematic review can be added in introduction/methods and may be removed from the statistical analysis section.</p>
                    </list-item>
                    <list-item>
                        <p>Was interobserer agreement done? If so, it can be added which statistical test was done to evaluate that.</p>
                    </list-item>
                    <list-item>
                        <p>Sensitivity, specificity, PPV and NPV can be added in the statistcal methods used.</p>
                    </list-item>
                    <list-item>
                        <p>Results report higher specificity in males, tables show higher specificity in females.</p>
                    </list-item>
                    <list-item>
                        <p>Some of the points in the introduction are repeated in the discussion.</p>
                    </list-item>
                    <list-item>
                        <p>Some of the limitations of CT can be addressed like dose, cost, time for disinfecting, all which can affect the time required for emergency patients (intro or discussion).</p>
                    </list-item>
                </list>
            </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>Yes</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>radiation dose in imaging procedures, computed tomography</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 article-type="response" id="comment10472-204241">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>alewaidat</surname>
                            <given-names>haytham </given-names>
                        </name>
                        <aff>Jordan University of Science and Technology, Jordan</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>2023</year>
                </pub-date>
            </front-stub>
            <body>
                <p>
                    <list list-type="bullet">
                        <list-item>
                            <p>Typographical errors can be corrected.</p>
                            <p> 
                                <italic>All errors and issues are addressed as well as solved.</italic>
                            </p>
                        </list-item>
                        <list-item>
                            <p>The statistical analysis section needs to be modified to include only the statistical tests used for the study, other details can be added in the introduction/background.</p>
                            <p> 
                                <italic>The statistical analysis section has been updated in the current version.</italic>
                            </p>
                        </list-item>
                        <list-item>
                            <p>The relevance of the results of the systematic review can be added in introduction/methods and may be removed from the statistical analysis section.</p>
                            <p> 
                                <italic>Yes, the results of the systematic review is inserted in introduction/methods.</italic>
                            </p>
                        </list-item>
                        <list-item>
                            <p>Was interobserer agreement done? If so, it can be added which statistical test was done to evaluate that.</p>
                            <p> 
                                <italic>Yes, interobserer agreement is added as well as statistical tests such as Chi-square, and Sperman coefficient is also evaluated.</italic>
                            </p>
                        </list-item>
                        <list-item>
                            <p>Sensitivity, specificity, PPV and NPV can be added in the statistical methods used.</p>
                            <p> 
                                <italic>The table in appendix and its interpretation is added in statistical analysis.</italic>
                            </p>
                        </list-item>
                        <list-item>
                            <p>Results report higher specificity in males, tables show higher specificity in females.</p>
                            <p> 
                                <italic>I have corrected my results as original results and tables show higher specificity in females.</italic>
                            </p>
                        </list-item>
                        <list-item>
                            <p>Some of the points in the introduction are repeated in the discussion.</p>
                            <p> 
                                <italic>Repeated data is removed.</italic>
                            </p>
                        </list-item>
                        <list-item>
                            <p>Some of the limitations of CT can be addressed like dose, cost, time for disinfecting, all which can affect the time required for emergency patients (intro or discussion).</p>
                            <p> 
                                <italic>I have added all limitations and also highlighted them such as dose, cost, time for disinfecting.</italic>
                            </p>
                        </list-item>
                    </list>
                </p>
            </body>
        </sub-article>
    </sub-article>
</article>
