<?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.137447.1</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>Impact of pulmonary hypertension on outcomes of influenza pneumonia patients: A nationwide analysis</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: 1 approved with reservations]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="no" equal-contrib="yes">
                    <name>
                        <surname>Jain</surname>
                        <given-names>Akhil</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <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/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Software</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="yes" equal-contrib="yes">
                    <name>
                        <surname>Raval</surname>
                        <given-names>Maharshi</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <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/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Software</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-3016-0078</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no" equal-contrib="yes">
                    <name>
                        <surname>Modi</surname>
                        <given-names>Karnav</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <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; Original Draft Preparation</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>Kumawat</surname>
                        <given-names>Sunita</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <xref ref-type="aff" rid="a4">4</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Patel</surname>
                        <given-names>Kunal</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <xref ref-type="aff" rid="a5">5</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Kavathia</surname>
                        <given-names>Shrenil</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <xref ref-type="aff" rid="a6">6</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Kataria</surname>
                        <given-names>Sharvilkumar</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <xref ref-type="aff" rid="a6">6</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Kataria</surname>
                        <given-names>Deeti</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <xref ref-type="aff" rid="a7">7</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Garg</surname>
                        <given-names>Monika</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <xref ref-type="aff" rid="a8">8</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Desai</surname>
                        <given-names>Rupak</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <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/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a9">9</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Dani</surname>
                        <given-names>Sourabha S.</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a10">10</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Internal Medicine, Mercy Catholic Medical Center, Darby, Pennsylvania, 19023, USA</aff>
                <aff id="a2">
                    <label>2</label>Internal Medicine, New York Medical College/Landmark Medical Center, Woonsocket, Rhode Island, 02895, USA</aff>
                <aff id="a3">
                    <label>3</label>Division of Cancer Treatment and Research, Moffitt Cancer Center and Research Institute, Tampa, Florida, 33612, USA</aff>
                <aff id="a4">
                    <label>4</label>Internal Medicine, Hackensack Ocean University Medical Center, Brick Township, New Jersey, 08724, USA</aff>
                <aff id="a5">
                    <label>5</label>Internal Medicine, Saint Peter's University Hospital, New Brunswick, New Jersey, 08901, USA</aff>
                <aff id="a6">
                    <label>6</label>Internal Medicine, BJ Medical College and Civil Hospital, Ahmedabad, Gujarat, 380016, India</aff>
                <aff id="a7">
                    <label>7</label>Internal Medicine, GMERS Sola Medical College, Ahmedabad, Gujarat, 380060, India</aff>
                <aff id="a8">
                    <label>8</label>Independent Researcher, Darby, Pennsylvania, 19023, USA</aff>
                <aff id="a9">
                    <label>9</label>Independent Researcher, Atlanta, Georgia, 30033, USA</aff>
                <aff id="a10">
                    <label>10</label>Division of Cardiology, Lahey Hospital and Medical Center, Burlington, Massachusetts, 01805, USA</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:maharshiraval5897@gmail.com">maharshiraval5897@gmail.com</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>11</day>
                <month>10</month>
                <year>2023</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2023</year>
            </pub-date>
            <volume>12</volume>
            <elocation-id>1303</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>1</day>
                    <month>9</month>
                    <year>2023</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2023 Jain A 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/12-1303/pdf"/>
            <abstract>
                <p>
                    <bold>Background:</bold> Pulmonary hypertension can be a significant cause of morbidity and mortality for influenza pneumonia (IP) patients. We performed analysis from the multicentric National Inpatient Sample (NIS) datasets to study the influence of disorders of pulmonary hypertension on the outcomes in IP patients.</p>
                <p>
                    <bold>Methods:</bold> We used NIS 2016&#x2013;2019 to identify IP hospitalizations (between 22&#x2013;90 years of age) and divided them into with and without pulmonary hypertension (herein PHDPC). We analyzed for differences in demographics, primary (all-cause mortality) and other secondary outcomes.</p>
                <p>
                    <bold>Results:</bold> Of 353,460 IP hospitalizations, 6.5% had PHDPC. The PHDPC cohort had more elderly, females, African Americans, and Medicare enrollees predominantly with more hospitalizations to large bed sizes and urban teaching hospitals, and higher cardiovascular comorbidities than non-PHDPC cohort. PHDPC had higher primary outcomes for in-hospital mortality (8.9% vs. 5.8%, adjusted OR 1.4, 95% CI: 1.21&#x2013;1.61). PHDPC also had higher secondary outcomes for sepsis, septic shock, cardiogenic shock and need for mechanical ventilation, prolonged ventilation, hospital resource utilization for longer mean length of stay, mean hospitalization cost, transfer to other facilities or need for home health care, and high risk for 30-day readmission than the non-PHDPC cohort.</p>
                <p>
                    <bold>Conclusions:</bold> With our study, we provide contemporary data for the outcomes of IP inpatients with pulmonary hypertension and depict worse outcomes for mortality, complications, and hospital resource utilization. Although our study does not include stratification for vaccination status for the outcome, primary care physicians, cardiologists, and pulmonologists should pro-actively educate patients on preventive strategies during the flu season.</p>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>influenza</kwd>
                <kwd>influenza pneumonia</kwd>
                <kwd>pulmonary hypertension</kwd>
                <kwd>national inpatient sample</kwd>
                <kwd>outcomes</kwd>
                <kwd>outcomes research</kwd>
            </kwd-group>
            <funding-group>
                <funding-statement>The author(s) declared that no grants were involved in supporting this work.</funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <sec id="sec1" sec-type="intro">
            <title>Introduction</title>
            <p>Despite many significant medical advances, community-acquired pneumonia (CAP) significantly contributes to global morbidity and mortality.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup> The influenza virus accounts for 15&#x2013;20% of CAP cases,
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> and severe influenza infections cause pneumonia in &gt;50% of affected patients, leading to multiple organ dysfunction.
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> Influenza pneumonia (IP) has mortality rates similar to that of patients with pneumonia caused by bacterial or other viral pathogens.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup> Between September 2018 and February 2019, the Centers for Disease Control and Prevention in the United States reported a weekly mortality rate of 5.5% to 7.4% attributed to pneumonia and influenza infection, indicating the significant impact on the population and resources every season.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup> IP patients frequently develop complications during hospitalization and can rapidly develop acute lung injuries requiring mechanical ventilation.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> Pulmonary heart disease and diseases of the pulmonary circulation (PHDPC) encompasses a wide range of conditions, including pulmonary embolism, various types of pulmonary hypertension, and diseases of pulmonary vessels.
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> They can be a significant cause of morbidity and mortality for IP patients and the utilization of resources. However, in IP patients, there is a lack of data on the role of PHDPC on mortality and other outcomes, including the need for mechanical ventilation and infectious complications. Hence, we used the multicentric national inpatient sample database for those admitted for IP to compare all-cause in-hospital mortality, in-hospital complications, and resource utilization between patients with and without PHDPC.</p>
        </sec>
        <sec id="sec2" sec-type="methods">
            <title>Methods</title>
            <sec id="sec3">
                <title>Data overview and source</title>
                <p>We utilized National Inpatient Sample (NIS) datasets from 2016 to 2019 for the United States to extract our study sample population and define cohorts. NIS is sponsored by the Agency for Healthcare Research and Quality Healthcare Cost and Utilization Projects.
                    <sup>
                        <xref ref-type="bibr" rid="ref8">8</xref>
                    </sup> Diagnoses and procedures are reported using the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes, and International Classification of Diseases, Tenth Revision, Procedure Coding System (ICD-10-PCS) codes in the primary and secondary diagnosis fields. All datasets are publicly available and are de-identified; therefore, institutional review board approval was not obtained for our study.</p>
            </sec>
            <sec id="sec4">
                <title>Data selection and study population</title>
                <p>We extracted influenza pneumonia (IP) hospitalizations using the ICD-10-CM codes (Extended data: Supplementary Table 1
                    <sup>
                        <xref ref-type="bibr" rid="ref9">9</xref>
                    </sup>) in any disease diagnosis field. We used relevant ICD-10-CM codes in the secondary diagnosis fields to extract patients with PHDPC (Extended data: Supplementary Table 1
                    <sup>
                        <xref ref-type="bibr" rid="ref9">9</xref>
                    </sup>). Next, we evaluated the IP hospitalizations for the 1st and 99th percentile distribution, which included hospitalizations for patients aged 22 to 90 years. Our two cohorts (
                    <xref ref-type="fig" rid="f1">Figure 1</xref>) comprised the study arm, which included patients with PHDPC, and a control arm with patients without underlying pulmonary heart disease and diseases of the pulmonary circulation (non-PHDPC).</p>
                <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                    <label>Figure 1. </label>
                    <caption>
                        <title>Patient selection and study design.</title>
                    </caption>
                    <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/150609/37489dae-267e-4978-b78e-d9465b754168_figure1.gif"/>
                </fig>
            </sec>
            <sec id="sec5">
                <title>Baseline variables</title>
                <p>Demographic characteristics, including age and sex; hospital characteristics, including size and teaching status; and patient-specific characteristics, such as the median household income category in their zip code, the primary payer source, the type of admission, and the day of admission, were identified using the NIS variables. Elixhauser comorbidity software (v2021.1)
                    <sup>
                        <xref ref-type="bibr" rid="ref10">10</xref>
                    </sup> generated comorbidities to compare the prevalence of comorbidities between the two cohorts (Extended data: Supplementary Table 2
                    <sup>
                        <xref ref-type="bibr" rid="ref9">9</xref>
                    </sup>). These comorbidities were hypertension, diabetes mellitus, heart failure, valvular disease, peripheral vascular disease, cerebrovascular disease, paralysis, obesity, severe renal failure, chronic pulmonary disease, liver disease, hypothyroidism, other thyroid disorders, dementia, depression, acquired immune deficiency syndrome, autoimmune conditions, lymphoma, leukemia, cancer, alcohol abuse, and drug abuse. Besides these software-generated comorbidities, we included atrial fibrillation/flutter, dyslipidemia, prior myocardial infarction, prior percutaneous coronary intervention, prior coronary artery bypass graft, obstructive sleep apnea, tobacco use, cocaine, and cannabis use as the other comorbidity binary variables in our study by utilizing the corresponding ICD-10-CM codes in the secondary diagnosis fields (Extended data: Supplementary Table 2
                    <sup>
                        <xref ref-type="bibr" rid="ref9">9</xref>
                    </sup>). Moreover, we used entropy balancing (EB) as the reweighting method to adjust for covariate imbalances between the two cohorts. Originally, Hainmueller 
                    <italic toggle="yes">et al</italic>.
                    <sup>
                        <xref ref-type="bibr" rid="ref11">11</xref>
                    </sup> described EB as a generalization of the conventional propensity score method, directly estimating the unit weights from the balanced constraints and matching the two cohorts for mean, variance, and skewness.</p>
            </sec>
            <sec id="sec6">
                <title>Outcomes</title>
                <p>Our primary outcome was all-cause in-hospital mortality. Secondary outcomes included secondary pneumonia, sepsis, septic shock, cardiogenic shock, need for mechanical ventilation (MV), duration of the requirement of MV and complications related to MV, length of stay (LOS), cost of hospitalization, and disposition at discharge. The cost of hospitalization was generated after matching the variable &#x201c;TOTCHG,&#x201d; representing the edited total charges of hospitalization for the hospital services for March 2022 provided by the US Bureau of Labor Statistics as a consumer price index
                    <sup>
                        <xref ref-type="bibr" rid="ref12">12</xref>
                    </sup> (Extended data: Supplementary Table 3
                    <sup>
                        <xref ref-type="bibr" rid="ref9">9</xref>
                    </sup>). Moreover, after adjusting for covariate imbalances using EB, we performed multivariate logistic regression to obtain adjusted odds ratio (aOR) for categorical outcomes and poisson regression for incidence rate ratio (IRR) for continuous outcomes.</p>
            </sec>
            <sec id="sec7">
                <title>Statistical analyses</title>
                <p>
                    <ext-link ext-link-type="uri" xlink:href="https://www.stata.com/stata16/">Stata</ext-link> (version 16) MP edition (StataCorp. 2019. Stata Statistical Software: Release 16. College Station, TX: StataCorp LLC) was used for the statistical analyses. Survey data analysis was performed using Pearson&#x2019;s chi-square test for categorical variables and Student&#x2019;s t-test for continuous variables to measure the differences between the PHDPC and non-PHDPC cohorts. Next, we used univariate and multivariate analysis to calculate the odds ratio (OR) of primary and secondary outcomes in the PHDPC cohort. We used baseline demographics, patient- and hospital-specific admitting characteristics, and comorbidities in 
                    <xref ref-type="table" rid="T1">Table 1</xref> as adjusting variables for multivariate regression analysis. Elixhauser comorbidity index and risk of 30-day all-cause readmission, generated via Elixhauser comorbidity software, were also compared between the two cohorts.
                    <sup>
                        <xref ref-type="bibr" rid="ref13">13</xref>
                    </sup>
                </p>
                <table-wrap id="T1" orientation="portrait" position="float">
                    <label>Table 1. </label>
                    <caption>
                        <title>Baseline characteristics of influenza pneumonia patients stratified by pulmonary heart disease and diseases of pulmonary circulation (PHDPC).</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Characteristics of influenza pneumonia patients (n = 353460, weighted)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">PHDPC absent (n = 330460, 93.49%)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">PHDPC present (n = 23000, 6.51%)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Significance value (p)</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="4" rowspan="1" valign="middle">
                                    <bold>Demographics</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Age at admission (mean, 22&#x2013;90 years)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">67.5</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">72.3</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">Sex</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Males</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">47.8</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">41</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Females</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">52.2</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">59</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Race</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">White</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">72.1</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">70.5</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">African American</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">13.3</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">16.2</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Hispanics</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">10.8</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">9.5</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Asian/Pacific Islanders</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.03</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.03</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Native Americans</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.8</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.6</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Median household income
                                    <xref ref-type="table-fn" rid="tfn1">
                                        <sup>#</sup>
                                    </xref>
                                </td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.160</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0&#x2013;25th</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">30.4</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">28.8</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">26&#x2013;50th</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">26.5</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">26.7</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">51&#x2013;75th</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">23.7</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">24.4</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">76&#x2013;100th</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">19.2</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">19.9</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Primary expected payer</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Medicare</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">65.4</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">77.4</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Medicaid</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">11.8</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">8.6</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Private</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">18.8</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">12.2</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Self-pay</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.5</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.6</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="4" rowspan="1" valign="middle">
                                    <bold>Hospital-specific admitting characteristics</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Type of admission</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Non-elective</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">96.2</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">97.4</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Elective</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.7</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.5</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Bed size of hospital
                                    <xref ref-type="table-fn" rid="tfn2">
                                        <sup>&#x00a7;</sup>
                                    </xref>
                                </td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.016</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Small</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">24.1</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">22.6</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Medium</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">29.3</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">28.7</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Large</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">46.4</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">48.6</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Location and teaching status of hospital
                                    <xref ref-type="table-fn" rid="tfn3">~</xref>
                                </td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Rural</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">12.2</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">8.8</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Urban non-teaching</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">23.7</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">21.4</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Urban teaching</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">64.1</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">69.6</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Region of hospital</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="middle">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Northeast</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">17.1</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">16.3</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Midwest</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">22.8</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">26.2</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">South</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">38.5</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">34.1</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">West</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">21.4</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">23.2</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="4" rowspan="1" valign="middle">
                                    <bold>Comorbidities</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">HTN complicated
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">29.9</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">55</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">HTN uncomplicated
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">35.4</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">19.5</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">DM with chronic complications
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">20.1</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">28.5</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">DM without chronic complications
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">12.9</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">11.3</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Heart failure
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.02</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.1</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">Atrial Fibrillation/Flutter
                                    <xref ref-type="table-fn" rid="tfn5">*</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">22.7</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">46.6</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">Valvular disease
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.7</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.8</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">Peripheral vascular disease
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">5.9</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">11.0</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">Dyslipidemia
                                    <xref ref-type="table-fn" rid="tfn5">*</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">37.9</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">45.3</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">Cerebrovascular disease
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.6</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.3</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.342</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Paralysis
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.0</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.6</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.075</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Obesity
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">17.0</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">23.4</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">OSA
                                    <xref ref-type="table-fn" rid="tfn5">*</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">8.8</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">16.9</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Chronic pulmonary disease
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">41.8</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">55.8</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">Renal failure
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.8</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">6.8</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">Liver disease, moderate to severe
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.2</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.1</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.057</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Hypothyroidism
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">15.9</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">17.7</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.002</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Dementia
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">11.2</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">10.0</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.016</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Depression
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">12.7</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">12.9</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.627</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">AIDS
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.0</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.6</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.006</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Autoimmune conditions
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">5.0</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">6.5</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Lymphoma
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.0</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.6</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.034</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Leukemia
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.3</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.0</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.150</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Malignant solid tumor without metastasis
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.7</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.7</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.717</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Metastatic cancer
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.8</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.2</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Solid tumor without metastasis, in situ
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.02</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.07</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.047</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Tobacco use
                                    <xref ref-type="table-fn" rid="tfn5">*</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">27.4</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">29.3</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.003</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Alcohol
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.3</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.9</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.118</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Cocaine
                                    <xref ref-type="table-fn" rid="tfn5">*</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.6</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.5</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.790</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Cannabis
                                    <xref ref-type="table-fn" rid="tfn5">*</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.1</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.7</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.022</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Drug abuse
                                    <xref ref-type="table-fn" rid="tfn4">^</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.2</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.9</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.154</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Elixhauser comorbidity index (mean)
                                    <xref ref-type="table-fn" rid="tfn6">
                                        <sup>1</sup>
                                    </xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">4.1</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">6.7</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">&lt;0.001</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>Values are percentages unless specified.</p>
                        <p>PHDPC = Pulmonary heart disease and diseases of pulmonary circulation, HTN = Hypertension, DM = Diabetes mellitus, OSA = Obstructive sleep apnea, AIDS = Acquired Immune Deficiency Syndrome.</p>
                        <fn-group content-type="footnotes">
                            <fn id="tfn1">
                                <label>
                                    <sup>#</sup>
                                </label>
                                <p>Represents a quartile classification of the estimated median household income of residents within the patients&#x2019; zip code, 
                                    <ext-link ext-link-type="uri" xlink:href="https://www.hcup-us.ahrq.gov/db/vars/zipinc_qrtl/nrdnote.jsp">https://www.hcup-us.ahrq.gov/db/vars/zipinc_qrtl/nrdnote.jsp</ext-link>.</p>
                            </fn>
                            <fn id="tfn2">
                                <label>
                                    <sup>&#x00a7;</sup>
                                </label>
                                <p>The bed size cutoff points divided into small, medium, and large have been done so that approximately one-third of the hospitals in a given region, location, and teaching status combination would fall within each bed size category. 
                                    <ext-link ext-link-type="uri" xlink:href="https://www.hcup-us.ahrq.gov/db/vars/hosp_bedsize/nrdnote.jsp">https://www.hcup-us.ahrq.gov/db/vars/hosp_bedsize/nrdnote.jsp</ext-link>.</p>
                            </fn>
                            <fn id="tfn3">
                                <label>~</label>
                                <p>A hospital is considered to be a teaching hospital if it has an American Medical Association-approved residency program. 
                                    <ext-link ext-link-type="uri" xlink:href="https://www.hcup-us.ahrq.gov/db/vars/hosp_ur_teach/nrdnote.jsp">https://www.hcup-us.ahrq.gov/db/vars/hosp_ur_teach/nrdnote.jsp</ext-link>.</p>
                            </fn>
                            <fn id="tfn4">
                                <label>^</label>
                                <p>Comorbidities generated using Elixhauser comorbidity software (Supplementary Table 2).</p>
                            </fn>
                            <fn id="tfn5">
                                <label>*</label>
                                <p>Comorbidities generated separately using relevant ICD-10-CM diagnosis codes (Supplementary Table 2).</p>
                            </fn>
                            <fn id="tfn6">
                                <label>
                                    <sup>1</sup>
                                </label>
                                <p>Moore BJ, White S, Washington R, Coenen N, Elixhauser A. Identifying Increased Risk of Readmission and In-hospital Mortality Using Hospital Administrative Data: The AHRQ Elixhauser Comorbidity Index. Med Care. 2017 Jul;55(7):698-705.</p>
                            </fn>
                        </fn-group>
                    </table-wrap-foot>
                </table-wrap>
            </sec>
        </sec>
        <sec id="sec8" sec-type="results">
            <title>Results</title>
            <p>Of the 121,097,410 weighted discharges in the NIS datasets 2016&#x2013;2019, 353,460 influenza pneumonia-related hospitalizations were found between 2016 and 2019 for ages 22 years to 90 years based on the 1st and 99th percentile age distribution of IP. Of these, 6.5% (n = 23,000) had PHDPC. 
                <xref ref-type="table" rid="T1">Table 1</xref> details the baseline characteristics between the two cohorts. The PHDPC cohort was older (mean age, 72.3 years vs. 67.5 years), had more females (59.0% vs. 52.2%) and patients of African American (AA) race (16.2% vs. 13.3%). Medicare was the primary expected payer in both cohorts, and Medicare enrollees were significantly higher in the PHDPC cohort (77.4.% vs. 65.4%). IP patients with PHDPC were more likely to be admitted to large bed-size hospitals (48.6% vs. 46.4%) and urban teaching hospitals (69.6% vs. 64.1%) than the non-PHDPC cohort. Amongst comorbidities, complicated hypertension, diabetes with chronic complications, heart failure, atrial fibrillation or flutter, valvular heart disease, peripheral vascular disease, dyslipidemia, obesity, obstructive sleep apnea, chronic pulmonary disease, renal failure, hypothyroidism, autoimmune conditions, non-metastatic solid tumors, and tobacco use was significantly more frequent within the PHDPC cohort.</p>
            <p>Rates of outcomes and regression analysis (before and after matching by EB) are depicted in 
                <xref ref-type="table" rid="T2">Table 2</xref>. The PHDPC cohort had a significantly higher rate of in-hospital mortality (8.9% vs. 5.8%; P &lt;0.00, in-hospital complications that included sepsis (4.8% vs 3.9%, P = 0.004), septic shock (11.3% vs 8.8%, P &lt;0.001), cardiogenic shock (1.9 vs 0.8%, P &lt;0.001) and need for mechanical ventilation (18.6% vs 12.7%, P &lt;0.001). Moreover, patients with PHDPC had a higher need of mechanical ventilation for 24 to 96 hours (7.6% vs 4.9%, P &lt;0.001) and more than 96 hours (9.5% vs 6.6%, P &lt;0.001). However, although the need for MV for less than 24 hours, secondary pneumonia, and complications of mechanical ventilation showed a higher trend in PHDPC, there were no statistically significant differences between the two cohorts. After matching by EB and multivariate regression analysis, the PHDPC cohort had higher adjusted odds of in-hospital mortality (aOR 1.4, 95% CI: 1.21&#x2013;1.61; P &lt;0.001), sepsis (aOR 1.3, 95% CI: 1.08&#x2013;1.57), septic shock (aOR 1.3, 95% CI: 1.11&#x2013;1.44), cardiogenic shock (aOR 1.7, 95% CI: 1.25&#x2013;2.31), need for mechanical ventilation in overall (aOR 1.4, 95% CI: 1.27&#x2013;1.58), need for mechanical ventilation for 24&#x2013;96 hours (aOR 1.3, 95% CI: 1.14&#x2013;1.56) and need for mechanical ventilation for more than 96 hours (aOR 1.4, 95% CI: 1.19&#x2013;1.60). The PHDPC cohort had a higher comorbidity index for the risk of all-cause 30-day readmission (5.0 vs. 4.1, P &lt;0.001) than the non-PHDPC cohort. In addition, the mean length of hospital stay was longer in the PHDPC cohort (8.7 days vs. 6.8 days, IRR 1.2, 95% CI: 1.12&#x2013;1.20; P &lt;0.001), with a higher associated mean cost of stay (113501.7 USD vs. 87530.4 USD, IRR 1.2, 95% CI: 1.13&#x2013;1.25; P &lt;0.001). In addition, statistically significant differences in hospital disposition were also appreciated, with PHDPC patients requiring frequent transfers to other facilities or needing home health care (54.5% vs. 40.8%, P &lt;0.001).</p>
            <table-wrap id="T2" orientation="portrait" position="float">
                <label>Table 2. </label>
                <caption>
                    <title>Outcomes of influenza pneumonia patients stratified by pulmonary heart disease and diseases of pulmonary circulation.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Outcomes</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">PHDPC absent (n = 330460, 93.49%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">PHDPC present (n = 23000, 6.51%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Significance value (p)</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="4" rowspan="1" valign="top">2A. Outcomes with Pearson coefficient p-values</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">All-cause In-hospital Mortality (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">5.8</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">8.9</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">Secondary pneumonia</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">39.4</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">40.7</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.066</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Sepsis</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">3.9</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">4.8</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.004</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Septic shock</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">8.8</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">11.3</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">Cardiogenic shock</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.8</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.9</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">Need for Mechanical ventilation</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">12.7</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">18.6</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">&#x2003;Mechanically ventilated for 24 hours</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.8</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2.2</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.029</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;Mechanically ventilated for 24&#x2013;96 hours</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">4.9</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">7.6</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">&#x2003;Mechanically ventilated for 96 hours</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">6.6</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">9.5</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">Complications of Mechanical ventilation</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.3</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.3</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.759</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Disposition pattern</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;Routine</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">52.4</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">35.7</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">&#x2003;Transfer to short term hospitals</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2.3</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2.4</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">&#x2003;Other transfers including SNF, ICF, etc.</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">22.6</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">30.5</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">&#x2003;Home health care</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">15.8</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">21.6</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">Length of hospital stay (mean, days)</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">6.8</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">8.7</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">Total cost of hospitalization (mean, USD)
                                <xref ref-type="table-fn" rid="tfn7">*</xref>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">87530.4</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">113501.7</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&lt;0.001</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Comorbidity index for risk of 30-day all-cause readmission</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.1</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5.0</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                        </tr>
                    </tbody>
                </table>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="4" rowspan="1" valign="top">2B. Regression analysis for outcomes</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Univariate regression analysis</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Unadjusted OR</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">95% CI (LL&#x2013;UL)</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">All-cause in-hospital Mortality</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.6</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.44&#x2013;1.77</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">Secondary pneumonia</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.1</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.00&#x2013;1.13</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.067</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Sepsis</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.2</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.06&#x2013;1.40</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.005</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Septic shock</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.3</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.21&#x2013;1.46</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">Cardiogenic shock</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">2.2</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.77&#x2013;2.84</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">Mechanical ventilation</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;Mechanically ventilated for 24 hours</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;Mechanically ventilated for 24&#x2013;96 hours</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;Mechanically ventilated for 96 hours</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Complications of mechanical ventilation</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.1</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.62-1.93</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.760</td>
                        </tr>
                    </tbody>
                </table>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Multivariate regression analysis - before matching by EB
                                <xref ref-type="table-fn" rid="tfn8">**</xref>
                            </th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Adjusted OR
                                <xref ref-type="table-fn" rid="tfn9">^</xref>
                            </th>
                            <th align="left" colspan="1" rowspan="1" valign="top">95% CI (LL-UL)</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">All-cause in-hospital Mortality</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.4</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.12&#x2013;1.59</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">Sepsis</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.3</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.06&#x2013;1.53</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.010</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Septic shock</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.2</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.08&#x2013;1.40</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.002</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Cardiogenic shock</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.6</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.17&#x2013;2.24</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.004</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Mechanical ventilation</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.4</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.25&#x2013;1.57</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">&#x2003;Mechanically ventilated for 24 hours</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.3</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.99&#x2013;1.69</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.059</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;Mechanically ventilated for 24&#x2013;96 hours</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.3</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.13&#x2013;1.56</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.001</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;Mechanically ventilated for 96 hours</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.3</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.16&#x2013;1.56</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&lt;0.001</td>
                        </tr>
                    </tbody>
                </table>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Multivariate regression analysis - after matching by EB</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Adjusted OR
                                <xref ref-type="table-fn" rid="tfn9">^</xref>/IRR
                                <xref ref-type="table-fn" rid="tfn10">~</xref>
                            </th>
                            <th align="left" colspan="1" rowspan="1" valign="top">95% CI (LL-UL)</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">All-cause in-hospital Mortality</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.4</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.21&#x2013;1.61</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">Sepsis</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.3</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.08&#x2013;1.57</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.007</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Septic shock</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.3</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.11&#x2013;1.44</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">Cardiogenic shock</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.7</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.25&#x2013;2.31</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.001</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">Mechanical ventilation</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.4</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.27&#x2013;1.58</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">&#x2003;Mechanically ventilated for 24 hours</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.3</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.98&#x2013;1.67</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">0.072</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&#x2003;Mechanically ventilated for 24&#x2013;96 hours</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.3</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.14&#x2013;1.56</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">&#x2003;Mechanically ventilated for 96 hours</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.4</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.19&#x2013;1.60</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">Length of hospital stay
                                <xref ref-type="table-fn" rid="tfn10">~</xref>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.2</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.12&#x2013;1.20</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">Total cost of hospitalization
                                <xref ref-type="table-fn" rid="tfn10">~</xref>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.2</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">1.13&#x2013;1.25</td>
                            <td align="left" colspan="1" rowspan="1" valign="middle">&lt;0.001</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <p>Multivariate Regression Analysis: adjusted for patient demographics, hospital-admitting characteristics, and comorbidities as in 
                        <xref ref-type="table" rid="T1">Table 1</xref>.</p>
                    <p>PHDPC= Pulmonary Heart Disease and Diseases of Pulmonary Circulation; SNF-Skilled Nursing Facility; ICF-Intermediate Care Facilities;</p>
                    <fn-group content-type="footnotes">
                        <fn id="tfn7">
                            <label>*</label>
                            <p>NIS variable "TOTCHG" depicting total charges of hospitalization converted to total cost of hospitalization in accordance to Consumer Price Index Hospital Expenditure adjustments to March 2022 (Supplementary Table 3).</p>
                        </fn>
                        <fn id="tfn8">
                            <label>**</label>
                            <p>EB - Entropy Balancing used the variables of patient demographics, hospital-admitting characteristics, and comorbidities as mentioned in 
                                <xref ref-type="table" rid="T1">Table 1</xref>.</p>
                        </fn>
                        <fn id="tfn9">
                            <label>^</label>
                            <p>OR-Odds Ratio;</p>
                        </fn>
                        <fn id="tfn10">
                            <label>
                                <sup>~</sup>
                            </label>
                            <p>IRR-Incidence Rate Ratio; CI-Confidence Interval, LL-Lower Limit of CI, UL-Upper Limit of CI.</p>
                        </fn>
                    </fn-group>
                </table-wrap-foot>
            </table-wrap>
        </sec>
        <sec id="sec9" sec-type="discussion">
            <title>Discussion</title>
            <p>In this multicentric retrospective cohort study of IP patients comparing patients with and without PHDPC, we derived the following significant findings, which were found to be significant both before and after matching by EB: 1) Patients with PHDPC had a 38% higher risk of in-hospital mortality as compared with non-PHDPC patients; 2) PHDPC was associated with a higher risk of in-hospital complications including sepsis, septic shock, cardiogenic shock, and need for mechanical ventilation for more than 24 hours compared with non-PHDPC; 3) the comorbidity index for the risk of all-cause 30-day readmission was higher in PHDPC than in non-PHDPC patients; 4) PHDPC was associated with higher resource utilization (longer LOS, higher cost of hospital stay, higher transfers to skilled nursing facilities or Intermediate Care Facilities, higher need of home health care) compared with non-PHDPC.</p>
            <p>Influenza is most common in the young,
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> the elderly, the pediatric population, and those with underlying medical conditions and they are most at risk for hospitalization and severe complications of pneumonia due to influenza.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup> We included only adult hospitalized IP patients in our study and had a higher proportion of female and AA patients in the PHDPC cohort. AA patients and females are a relatively vulnerable population for venous thromboembolism
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup> and pulmonary embolism due to hypercoagulable conditions like pregnancy, hereditary factor V Leiden and hormone replacement therapy, and predominance of disorders like idiopathic pulmonary hypertension in females.
                <sup>
                    <xref ref-type="bibr" rid="ref17">17</xref>
                </sup> Hence, consistent with the findings in our study, females, and AA make up a relatively higher proportion of the PHDPC cohort. The PHDPC cohort has a higher burden of comorbidities, a higher Elixhauser comorbidity index, and higher adjusted odds of several complications than the non-PHDPC cohort. As evident in our study and reported by previous studies, the risk of hospitalization, poorer outcomes, and death due to IP increases in the presence of other comorbidities.
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref19">19</xref>
                </sup> Hence, these comorbidities do predict poorer outcomes; still, even after adjusting the comorbidities and demographics on multivariate regression analysis, PHDPC was an independent predictor for worse outcomes.</p>
            <p>Influenza pneumonia is a notorious disease with poorer outcomes in patients with comorbidities.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup> We found significantly higher rates and odds of mortality in PHDPC patients compared to the ones who did not have PHDPC. Influenza infection has a detrimental effect on pulmonary circulation by causing pulmonary parenchymal inflammation and edema, interfering with alveolar gas exchange, resulting in ventilation/perfusion imbalance and hypoxemia. This hypoxia and carbon dioxide retention will cause the reflex spasm of pulmonary blood vessels and increase pulmonary circulation pressure.
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>
                </sup> However, in patients with preexisting resistance to flow due to pulmonary hypertension
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup> or chronic thromboembolism,
                <sup>
                    <xref ref-type="bibr" rid="ref22">22</xref>
                </sup> the pulmonary and systemic circulation is already compromised, and a superimposed influenza infection will burden the already compromised pulmonary circulation and increase RV overload. In addition, multiple studies reported that influenza infection is independently associated with increased atherosclerosis and acute cardiovascular events.
                <sup>
                    <xref ref-type="bibr" rid="ref23">23</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref25">25</xref>
                </sup> Therefore, various mechanisms cumulatively result in higher mortality and complications associated with influenza pneumonia.</p>
            <p>Infection and pneumonia due to the influenza virus significantly interact with the immune system, and this can result in sepsis directly or indirectly secondary to a bacterial infection.
                <sup>
                    <xref ref-type="bibr" rid="ref26">26</xref>
                </sup> Sepsis has been previously reported with influenza infection.
                <sup>
                    <xref ref-type="bibr" rid="ref27">27</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref28">28</xref>
                </sup> A 2009 national study by Jain 
                <italic toggle="yes">et al</italic>.
                <sup>
                    <xref ref-type="bibr" rid="ref29">29</xref>
                </sup> reported a rate of 18% sepsis on admission in patients with influenza pneumonia. In our study, we report sepsis at a rate of 4.8% vs. 3.9% and septic shock at 11.3% vs. 8.8% among the two cohorts. The difference in rates can be due to multiple reasons, as sepsis is recorded according to clinical judgment and may not have adhered to strict definitions written in critical care guidelines
                <sup>
                    <xref ref-type="bibr" rid="ref30">30</xref>
                </sup> and the coding errors with sepsis and septic shock. Sepsis is a broader term for life-threatening organ dysfunction caused by a dysregulated host response to infection.
                <sup>
                    <xref ref-type="bibr" rid="ref30">30</xref>
                </sup> At the same time, septic shock is a subset of sepsis in which particularly profound circulatory, cellular, and metabolic abnormalities are associated with a greater mortality risk than with sepsis alone.
                <sup>
                    <xref ref-type="bibr" rid="ref30">30</xref>
                </sup> We found that the PHDPC cohort has significantly higher odds of sepsis and septic shock (both before and after PS matching), which compromised pulmonary circulation can explain. In our study, the rate of septic shock reported is more than double the rate of sepsis, suggesting the significantly high degree of severity and influence of the virus on the immune system and inflammatory response of the body.</p>
            <p>In addition, Influenza virus infection is highly associated with acute myocarditis and pericarditis.
                <sup>
                    <xref ref-type="bibr" rid="ref31">31</xref>
                </sup> Persistent inflammation, as in the case of sepsis, causes depression in myocardial function and increases myocardial oxygen demand.
                <sup>
                    <xref ref-type="bibr" rid="ref32">32</xref>
                </sup> The endotoxins and cytokines from infection and inflammation cause left ventricular dilatation and depressed ejection fraction, causing sepsis-induced cardiomyopathy.
                <sup>
                    <xref ref-type="bibr" rid="ref33">33</xref>
                </sup> Furthermore, an increase in sympathetic nervous system activity, which is a primary response to inflammation, causes increased heart rate and vascular resistance; this causes a decrease in cardiac output and coronary perfusion of the heart.
                <sup>
                    <xref ref-type="bibr" rid="ref32">32</xref>
                </sup> Together, these mechanisms lead to the development of cardiogenic shock in IP patients, although rare but previously reported.
                <sup>
                    <xref ref-type="bibr" rid="ref34">34</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref35">35</xref>
                </sup> To the best of our knowledge, our study is the first to report the rate of cardiogenic shock in IP hospitalizations. We found a meager percentage of IP patients developing cardiogenic shock, 1.9% in PHDPC vs. 0.8% in non-PHDPC. We also found that those with PHDPC have significantly higher odds of developing cardiogenic shock, both before and after matching by EB.</p>
            <p>IP patients frequently require admission to the intensive care unit (ICU), and most need mechanical ventilation.
                <sup>
                    <xref ref-type="bibr" rid="ref36">36</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref38">38</xref>
                </sup> Moreover, acute respiratory distress syndrome can develop in severe influenza infection, leading to developing or exacerbating pulmonary hypertension due to vessel obliteration, pulmonary vasoconstriction, and microthrombosis due to hypoxia, hypercapnia, and an imbalance in vasoactive mediators.
                <sup>
                    <xref ref-type="bibr" rid="ref39">39</xref>
                </sup> In our study, the rate of mechanical ventilation was 18.6% vs. 12.7% in patients with and without PHDPC. Previous studies by Piroth 
                <italic toggle="yes">et al</italic>.
                <sup>
                    <xref ref-type="bibr" rid="ref40">40</xref>
                </sup> and Ludwig 
                <italic toggle="yes">et al</italic>.
                <sup>
                    <xref ref-type="bibr" rid="ref37">37</xref>
                </sup> have reported rates of 4% and 6%, respectively. However, our study&#x2019;s higher rates of mechanical ventilation could be because the above studies have included the pediatric population. In contrast, our study has an adult population only and a higher comorbidity burden among them. In addition, we found significantly higher odds of need for mechanical ventilation for more than 24 hours in the PHDPC cohort. However, there was no significant difference in the need for mechanical ventilation for less than 24 hours between the two cohorts in our study, and this can be explained as IP admission in the ICU requires much longer mechanical ventilation for eight days with an additional two days needed for cleaning, maintenance, and other such functions for a total of 10 days.
                <sup>
                    <xref ref-type="bibr" rid="ref41">41</xref>
                </sup>
            </p>
            <p>Our study reported higher resource utilization with a higher risk of all-cause 30-day readmission, longer LOS, and higher cost of hospital stay and discharge or transfer to skilled facilities for patients with PHDPC. Given the burden of pneumonia in our population,
                <sup>
                    <xref ref-type="bibr" rid="ref42">42</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref44">44</xref>
                </sup> our findings have important implications. Clinicians need to realize the importance of pre-existing PHDPC in patients with IP and exercise appropriate clinical alertness for their timely recognition of complications. Moreover, health officials need to increase efforts to optimize influenza vaccination rates among the elderly and those with chronic pulmonary conditions to reduce the incidence of pneumonia in these high-risk groups, ultimately reducing the healthcare facility burden. The prevention and optimal management of these patients may significantly reduce the burden of death associated with IP.</p>
            <sec id="sec10">
                <title>Limitations</title>
                <p>Our study has several limitations, mainly from its retrospective observational nature and administrative database. First, NIS is an administrative database that introduces miscoding bias. Second, this was a retrospective study, thus susceptible to selection bias despite our large sample size. Third, even after adjusting for multiple variables in multivariate regression analysis, there is a possibility of residual confounding bias. Finally, we could not access the information about various types of PHDPC and its severity and types and severity of influenza, owing to limitations of the database. Despite these limitations, the study&#x2019;s strength comes from its large sample size and multi-center cohort.</p>
            </sec>
        </sec>
        <sec id="sec11" sec-type="conclusions">
            <title>Conclusions</title>
            <p>In a retrospective cohort study of IP patients from NIS, patients with PHDPC had a higher risk of in-hospital mortality and in-hospital complications, including sepsis, septic shock, cardiogenic shock, and need for mechanical ventilation for more than 24 hours compared with non-PHDPC patients. Moreover, PHDPC was associated with a higher comorbidity index for the risk of all-cause 30-day readmission and higher resource utilization than non-PHDPC. Although our study does not include stratification for vaccination status for the outcome, primary care physicians, cardiologists, and pulmonologists should pro-actively educate such patients on preventive strategies during the flu season.</p>
        </sec>
    </body>
    <back>
        <sec id="sec14" sec-type="data-availability">
            <title>Data availability</title>
            <sec id="sec15">
                <title>Underlying data</title>
                <p>The data used for this study was obtained from the National Inpatient Sample (NIS) datasets. It has data on over seven million hospital stays in the United States. The datasets from 2016&#x2013;2019 used for this study are over 100 GB in size and are not feasible to provide. The datasets can be obtained from the Agency for Healthcare Research and Quality&#x2019;s official website (
                    <ext-link ext-link-type="uri" xlink:href="https://hcup-us.ahrq.gov">https://hcup-us.ahrq.gov</ext-link>), and we have provided codes used to extract data of our study in supplementary tables.</p>
            </sec>
            <sec id="sec16">
                <title>Extended data</title>
                <p>Zenodo: Extended data for &#x2018;Impact of pulmonary hypertension on outcomes of influenza pneumonia patients: A nationwide analysis&#x2019;: Influenza PHDPC extended data, 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.5281/zenodo.8213283">https://doi.org/10.5281/zenodo.8213283</ext-link>.
                    <sup>

                        <xref ref-type="bibr" rid="ref9">9</xref>
</sup>
                </p>
                <p>This project contains the following extended data:
                    <list list-type="bullet">
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Supplementary Table 1 &#x2013; ICD-10-CM/PCS Codes used in our study</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Supplementary Table 2 - Comorbidities</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Supplementary Table 3 - Adjusting total cost of hospitalization</p>
                        </list-item>
                    </list>
                </p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International license</ext-link> (CC-BY 4.0)</p>
            </sec>
        </sec>
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    <sub-article article-type="reviewer-report" id="report260915">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.150609.r260915</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Yan</surname>
                        <given-names>Yi</given-names>
                    </name>
                    <xref ref-type="aff" rid="r260915a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r260915a1">
                    <label>1</label>Shanghai Jiao Tong University, Shanghai, Shanghai, China</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>22</day>
                <month>5</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Yan Y</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport260915" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.137447.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>The article by Akhil Jain et al. aims to investigate the impact of pulmonary hypertension (PH) on outcomes of influenza pneumonia patients with a nationwide analysis. However, there are some issues needed to be addressed before further consideration. 
                <list list-type="order">
                    <list-item>
                        <p>The definition of PHDPC is confusing, as in the abstract it refers to the patients with PH, while PHDPC in the introduction section is defined as pulmonary heart disease and diseases of the pulmonary circulation, including pulmonary embolism (PE), various types of pulmonary hypertension, and diseases of pulmonary vessels. According to guideline, clinical classification of PH recognizes 5 groups that are categorized based on pathogenesis or comorbidity: group 1&#x2014;pulmonary arterial hypertension (PAH); group 2&#x2014;PH associated with left heart disease; group 3&#x2014;PH associated with lung diseases or hypoxia; group 4&#x2014;PH due to pulmonary artery obstructions (chronic thromboembolic pulmonary hypertension); and group 5&#x2014;PH with unclear or multifactorial mechanisms. Apparently, acute PE is not considered as PH. It would be much better to select PH patients according to right heart catheterization or at least echocardiography.</p>
                    </list-item>
                    <list-item>
                        <p>I was also wondering whether the drug information could be retrieved from the NIS.</p>
                    </list-item>
                    <list-item>
                        <p>In terms of regression analysis for outcomes, age and gender were not included for analysis.</p>
                    </list-item>
                    <list-item>
                        <p>According to the data, around 75% PHDPC cohort had hypertension and 46.6% PHDPC had atrial fibrillation/flutter, which is much higher than in PH patients. Therefore, I think PHDPC cohort in this study overrepresented PH population and the data would be biased even with large sample size and from multi-centers. Therefore I think it would be much better to rephrase the title of the manuscript.</p>
                    </list-item>
                </list> </p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Partly</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>Partly</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>NA</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
    </sub-article>
</article>
