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<?covid-19-tdm?>
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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Cardiovasc. Med.</journal-id>
<journal-title>Frontiers in Cardiovascular Medicine</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Cardiovasc. Med.</abbrev-journal-title>
<issn pub-type="epub">2297-055X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fcvm.2021.684528</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Cardiovascular Medicine</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Prognostic Value of Coronary Artery Calcium Score in Hospitalized COVID-19 Patients</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Luchian</surname> <given-names>Maria-Luiza</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="author-notes" rid="fn002"><sup>&#x02020;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1325751/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Lochy</surname> <given-names>Stijn</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="author-notes" rid="fn002"><sup>&#x02020;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1246593/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Motoc</surname> <given-names>Andreea</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x0002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1278377/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Belsack</surname> <given-names>Dries</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Magne</surname> <given-names>Julien</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Roosens</surname> <given-names>Bram</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>de Mey</surname> <given-names>Johan</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Tanaka</surname> <given-names>Kaoru</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Scheirlynck</surname> <given-names>Esther</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Boeckstaens</surname> <given-names>Sven</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Van den Bussche</surname> <given-names>Karen</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1159899/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>De Potter</surname> <given-names>Tom</given-names></name>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>von Kemp</surname> <given-names>Berlinde</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Galloo</surname> <given-names>Xavier</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Fran&#x000E7;ois</surname> <given-names>Clara</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Weytjens</surname> <given-names>Caroline</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Droogmans</surname> <given-names>Steven</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Cosyns</surname> <given-names>Bernard</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Department of Cardiology, University Hospital of Brussels (Centrum voor Hart-en Vaat ziekten, Universitair Ziekenhuis Brussel)</institution>, <addr-line>Brussels</addr-line>, <country>Belgium</country></aff>
<aff id="aff2"><sup>2</sup><institution>Department of Radiology, University Hospital of Brussels</institution>, <addr-line>Brussels</addr-line>, <country>Belgium</country></aff>
<aff id="aff3"><sup>3</sup><institution>CHU Limoges, H&#x000F4;pital Dupuytren, Service Cardiologie</institution>, <addr-line>Limoges</addr-line>, <country>France</country></aff>
<aff id="aff4"><sup>4</sup><institution>INSERM 1094, Facult&#x000E9; de m&#x000E9;decine de Limoges, 2, rue Marcland</institution>, <addr-line>Limoges</addr-line>, <country>France</country></aff>
<aff id="aff5"><sup>5</sup><institution>Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel</institution>, <addr-line>Brussels</addr-line>, <country>Belgium</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: Ranil De Silva, Imperial College London, United Kingdom</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Tarun Mittal, Harefield Hospital, United Kingdom; Richard Nethononda, Chris Hani Baragwanath Hospital, South Africa</p></fn>
<corresp id="c001">&#x0002A;Correspondence: Andreea Motoc <email>andreea.motoc&#x00040;gmail.com</email></corresp>
<fn fn-type="other" id="fn001"><p>This article was submitted to Cardiovascular Imaging, a section of the journal Frontiers in Cardiovascular Medicine</p></fn>
<fn fn-type="other" id="fn002"><p>&#x02020;These authors have contributed equally to this work</p></fn></author-notes>
<pub-date pub-type="epub">
<day>09</day>
<month>07</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>8</volume>
<elocation-id>684528</elocation-id>
<history>
<date date-type="received">
<day>23</day>
<month>03</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>10</day>
<month>06</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x000A9; 2021 Luchian, Lochy, Motoc, Belsack, Magne, Roosens, de Mey, Tanaka, Scheirlynck, Boeckstaens, Van den Bussche, De Potter, von Kemp, Galloo, Fran&#x000E7;ois, Weytjens, Droogmans and Cosyns.</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Luchian, Lochy, Motoc, Belsack, Magne, Roosens, de Mey, Tanaka, Scheirlynck, Boeckstaens, Van den Bussche, De Potter, von Kemp, Galloo, Fran&#x000E7;ois, Weytjens, Droogmans and Cosyns</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p></license>
</permissions>
<abstract><p><bold>Background:</bold> The association of known cardiovascular risk factors with poor prognosis of coronavirus disease 2019 (COVID-19) has been recently emphasized. Coronary artery calcium (CAC) score is considered a risk modifier in the primary prevention of cardiovascular disease. We hypothesized that the absence of CAC might have an additional predictive value for an improved cardiovascular outcome of hospitalized COVID-19 patients.</p>
<p><bold>Materials and methods:</bold> We prospectively included 310 consecutive hospitalized patients with COVID-19. Thirty patients with history of coronary artery disease were excluded. Chest computed tomography (CT) was performed in all patients. Demographics, medical history, clinical characteristics, laboratory findings, imaging data, in-hospital treatment, and outcomes were retrospectively analyzed. A composite endpoint of major adverse cardiovascular events (MACE) was defined.</p>
<p><bold>Results:</bold> Two hundred eighty patients (63.2 &#x000B1; 16.7 years old, 57.5% male) were included in the analysis. 46.7% patients had a CAC score of 0. MACE rate was 21.8% (61 patients). The absence of CAC was inversely associated with MACE (OR 0.209, 95% CI 0.052&#x02013;0.833, <italic>p</italic> = 0.027), with a negative predictive value of 84.5%.</p>
<p><bold>Conclusion:</bold> The absence of CAC had a high negative predictive value for MACE in patients hospitalized with COVID-19, even in the presence of cardiac risk factors. A semi-qualitative assessment of CAC is a simple, reproducible, and non-invasive measure that may be useful to identify COVID-19 patients at a low risk for developing cardiovascular complications.</p></abstract>
<kwd-group>
<kwd>Corona virus</kwd>
<kwd>coronary artery calcium score</kwd>
<kwd>major adverse cardiac and cerebral event</kwd>
<kwd>chest computed tomography</kwd>
<kwd>risk stratification</kwd>
</kwd-group>
<counts>
<fig-count count="1"/>
<table-count count="2"/>
<equation-count count="0"/>
<ref-count count="39"/>
<page-count count="7"/>
<word-count count="4713"/>
</counts>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="s1">
<title>Introduction</title>
<p>Coronavirus disease 2019 (COVID-19) has significantly impacted the healthcare system, due to the rapid spread of infection and unpredictable disease course. Studies have shown that advanced age and comorbidities including hypertension, diabetes mellitus, cardiovascular diseases, and cerebrovascular diseases are predictors of an unfavorable prognosis and mortality in COVID-19 infection (<xref ref-type="bibr" rid="B1">1</xref>&#x02013;<xref ref-type="bibr" rid="B4">4</xref>). Coronary artery calcium (CAC) score assessed by computed tomography (CT) is considered a risk modifier in primary prevention of cardiovascular disease (<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B6">6</xref>).</p>
<p>The CAC score offers two main assets: (<xref ref-type="bibr" rid="B1">1</xref>) it has an independent additional value in the prediction of all-cause mortality and mortality due to coronary artery disease in asymptomatic individuals; (<xref ref-type="bibr" rid="B2">2</xref>) it may reclassify patients considered as being at low or intermediate risk according to the clinical risk scores at high risk of atherosclerotic coronary events (<xref ref-type="bibr" rid="B6">6</xref>&#x02013;<xref ref-type="bibr" rid="B9">9</xref>).</p>
<p>However, data regarding the role of CAC score in the prediction of cardiovascular events and outcome in COVID-19 patients are still scarce.</p>
<p>We hypothesized that the absence of CAC might have an additional predictive value for an improved cardiovascular outcome of hospitalized COVID-19 patients.</p>
</sec>
<sec sec-type="materials and methods" id="s2">
<title>Materials and Methods</title>
<p>We prospectively included 310 consecutive hospitalized patients with confirmed COVID-19 by real-time reverse transcription polymerase chain reaction (RT-PCR) test, between March 2020 and April 2020. Thirty patients with a history of coronary artery disease (stable angina, unstable angina, history of acute coronary syndrome) were excluded from the analysis. Demographics, medical history, clinical characteristics, laboratory findings, imaging data, in-hospital treatment, and outcomes were retrospectively analyzed. A composite endpoint [major adverse cardiovascular events (MACE)] was defined as all-cause mortality, heart failure, acute coronary syndrome, atrial fibrillation, and stroke.</p>
<p>In the absence of widely available RT-PCR at the beginning of the pandemic, chest CT had been systematically performed in all suspected COVID-19 patients. All patients were scanned on an Apex Revolution CT (GE Healthcare, Milwaukee, WI, USA). The low-dose non-contrast CT thorax scan protocol consisted of a 128 &#x000D7; 0.625 mm spiral acquisition with pitch 1, rotation time 0.35 s, automated kVp selection and automated mA modulation. Images with 1.25 mm slice thickness were reconstructed with deep learning image reconstruction (DLIR) set at medium level. The average volume CT dose index (CTDIvol) and dose-length product (DLP) were 4.4 mGy (95% CI: 4.3&#x02013;4.5) and 159 mGy&#x000B7;cm (95% CI: 157&#x02013;162), respectively. Visual assessment of CAC was performed using ordinal scoring: each of the four main coronary arteries was identified (left main, left anterior descending, left circumflex, and right coronary artery). Calcium was scored as 0, 1, 2, or 3 for every artery, corresponding to absent, mild, moderate, or severe CAC. Mild CAC was defined as involvement of less than one third of the vessel length, moderate as involvement of one to two thirds of the vessel length and severe CAC as involvement of more than two thirds of the vessel length. A total score was calculated by summing the score of each vessel. The total score was then categorized as 0 (undetectable), 1&#x02013;3 (mild), 4&#x02013;5 (moderate), and &#x02265; 6 (severe) (<xref ref-type="bibr" rid="B10">10</xref>) (<xref ref-type="fig" rid="F1">Figure 1</xref>).</p>
<fig id="F1" position="float">
<label>Figure 1</label>
<caption><p><bold>(A)</bold> CAC score zero in left anterior descending (LAD) coronary artery. <bold>(B)</bold> Mild CAC in LAD. <bold>(C)</bold> Moderate CAC in LAD. <bold>(D)</bold> Severe CAC in LAD.</p></caption>
<graphic xlink:href="fcvm-08-684528-g0001.tif"/>
</fig>
<p>Intraobserver and interobserver reproducibility analyses of CAC score were performed by repeating the measurements in 20 random patients by the same primary investigator 2 weeks after the first assessment and by an additional investigator, respectively. During the repeated analysis, the investigators were blinded to any previous results.</p>
<p>The study was approved by the local Ethical Committee of the University Hospital of Brussels and was carried out in accordance with the ethical principles for medical research involving human subjects established by the Declaration of Helsinki, protecting the privacy of all participants as well as the confidentiality of their personal information. All data were fully anonymized. The need for consent in this study was waived by the ethical committee.</p>
<sec>
<title>Statistical Analysis</title>
<p>Continuous variables were presented as means with standard deviations (SD) or median [interquartile range (IQR)] for skewed variables. Categorical variables were expressed as percentages. Normality of data was tested using Kolmogorov&#x02013;Smirnov test. Comparisons of continuous variables were done using Student <italic>t</italic>-test or Mann&#x02013;Whitney <italic>U</italic>-test and of binominal variables using chi-square or Fisher exact test, respectively. Intraobserver and interobserver variability for CAC score assessment was tested by Cohen&#x00027;s Kappa coefficient. The following criteria for Kappa coefficient were used to interpret the results: &#x0003C;0.00 = poor, 0.00&#x02013;0.20 = light, 0.21&#x02013;0.40 = fair, 0.41&#x02013;0.60 = moderate, 0.61&#x02013;0.80 = substantial, and 0.81&#x02013;0.99 = almost perfect (<xref ref-type="bibr" rid="B11">11</xref>). Univariate and multivariate logistic regression models were used to evaluate potential predictors of MACE. Variables included in the multivariate analysis were chosen based on their statistical significance in the univariate analysis (<italic>p</italic> &#x0003C; 0.05) and on their clinical significance. Specificity, sensitivity, and negative predictive value of CAC score = 0 were calculated using a cross-tabulation table. Specificity was defined as the probability that a test result will be negative when the disease is not present (true negative rate). Sensitivity was defined as the probability that a test result will be positive when the disease is present (true positive rate). Negative predictive value was defined as the probability that the disease is not present when the test is negative (<xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B13">13</xref>). Statistical significance was considered for a <italic>p</italic> &#x0003C; 0.05. Statistical analyses were performed using IBM SPSS Statistic for Windows, Version 27.0 (IBM Corp., Armonk, NY, USA).</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<p>A total of 280 patients (63.2 &#x000B1; 16.7 years old, 57.5% male) were included in the analysis.</p>
<p>Mean length of hospitalization was 13.6 &#x000B1; 13.2 days. Sixty-one patients (21.8%) had at least one MACE: 16 (5.7%) patients presented acute heart failure, 15 (5.3%) patients had atrial fibrillation, 4 (1.4%) patients presented acute coronary syndrome [2 (0.7%) patients had a non-ST elevation myocardial infarction and 2 (0.7%) patients had unstable angina], and 3 (1.0%) patients presented a stroke, respectively. In-hospital mortality rate was 16.1% (45 patients). CAC score = 0 was found in 46.7% (131) patients, vs. 53.2% (149) patients with CAC score &#x02265;1. The baseline characteristics of the study population and the comparison between patients with a CAC score = 0 and CAC score &#x02265; 1 are shown in <xref ref-type="table" rid="T1">Table 1</xref>.</p>
<table-wrap position="float" id="T1">
<label>Table 1</label>
<caption><p>Comparison between patients with CAC score 0 and those with CAC score &#x02265;1.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th/>
<th valign="top" align="center"><bold>Total (<italic>n</italic> &#x0003D; 280)</bold></th>
<th valign="top" align="center"><bold>CAC score &#x0003D; 0 (<italic>n</italic> &#x0003D; 131)</bold></th>
<th valign="top" align="center"><bold>CAC score &#x02265; 1 (<italic>n</italic> &#x0003D; 149)</bold></th>
<th valign="top" align="center"><bold><italic>p</italic>-value</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Age (years)</td>
<td valign="top" align="center">63.2 &#x000B1; 16.7</td>
<td valign="top" align="center">53.7 &#x000B1; 13.1</td>
<td valign="top" align="center">72.7 &#x000B1; 13.2</td>
<td valign="top" align="center">&#x0003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Weight (kg)</td>
<td valign="top" align="center">80.5 &#x000B1; 16.7</td>
<td valign="top" align="center">84.4 &#x000B1; 16.3</td>
<td valign="top" align="center">76.6 &#x000B1; 15.8</td>
<td valign="top" align="center">&#x0003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">BMI (kg/m<sup>2</sup>)</td>
<td valign="top" align="center">27.8 &#x000B1; 5.2</td>
<td valign="top" align="center">28.9 &#x000B1; 5.2</td>
<td valign="top" align="center">26.8 &#x000B1; 4.9</td>
<td valign="top" align="center">0.001</td>
</tr>
<tr>
<td valign="top" align="left">Male gender (<italic>n</italic>, %)</td>
<td valign="top" align="center">161 (57.5)</td>
<td valign="top" align="center">76 (58.0)</td>
<td valign="top" align="center">76 (60.3)</td>
<td valign="top" align="center">0.707</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold>History</bold></td>
</tr>
<tr>
<td valign="top" align="left">Heart failure (<italic>n</italic>, %)</td>
<td valign="top" align="center">6 (2.1)</td>
<td valign="top" align="center">1 (0.8)</td>
<td valign="top" align="center">5 (4.0)</td>
<td valign="top" align="center">0.089</td>
</tr>
<tr>
<td valign="top" align="left">Valve disease (<italic>n</italic>, %)</td>
<td valign="top" align="center">6 (2.1)</td>
<td valign="top" align="center">1 (0.8)</td>
<td valign="top" align="center">5 (4.0)</td>
<td valign="top" align="center">0.089</td>
</tr>
<tr>
<td valign="top" align="left">Atrial fibrillation (<italic>n</italic>, %)</td>
<td valign="top" align="center">14 (5.0)</td>
<td valign="top" align="center">3 (2.2)</td>
<td valign="top" align="center">11 (7.3)</td>
<td valign="top" align="center">0.023</td>
</tr>
<tr>
<td valign="top" align="left">CKD (<italic>n</italic>, %)</td>
<td valign="top" align="center">32 (11.4)</td>
<td valign="top" align="center">9 (6.9)</td>
<td valign="top" align="center">23 (18.3)</td>
<td valign="top" align="center">0.006</td>
</tr>
<tr>
<td valign="top" align="left">Chronic pulmonary disease (<italic>n</italic>, %)</td>
<td valign="top" align="center">43 (15.3)</td>
<td valign="top" align="center">20 (15.2)</td>
<td valign="top" align="center">23 (15.4)</td>
<td valign="top" align="center">0.718</td>
</tr>
<tr>
<td valign="top" align="left">Cancer (<italic>n</italic>, %)</td>
<td valign="top" align="center">28 (10)</td>
<td valign="top" align="center">7 (5.3)</td>
<td valign="top" align="center">21 (16.7)</td>
<td valign="top" align="center">0.004</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold>Risk factors</bold></td>
</tr>
<tr>
<td valign="top" align="left">Hypertension (<italic>n</italic>, %)</td>
<td valign="top" align="center">128 (45.7)</td>
<td valign="top" align="center">40 (30.5)</td>
<td valign="top" align="center">78 (61.9)</td>
<td valign="top" align="center">&#x0003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">DM (<italic>n</italic>, %)</td>
<td valign="top" align="center">64 (22.8)</td>
<td valign="top" align="center">33 (25.2)</td>
<td valign="top" align="center">31 (24.6)</td>
<td valign="top" align="center">0.913</td>
</tr>
<tr>
<td valign="top" align="left">Dyslipidemia (<italic>n</italic>, %)</td>
<td valign="top" align="center">89 (31.8)</td>
<td valign="top" align="center">39 (29.8)</td>
<td valign="top" align="center">50 (39.7)</td>
<td valign="top" align="center">0.095</td>
</tr>
<tr>
<td valign="top" align="left">Smoking (<italic>n</italic>, %)</td>
<td valign="top" align="center">30 (10.7)</td>
<td valign="top" align="center">13 (9.9)</td>
<td valign="top" align="center">17 (13.5)</td>
<td valign="top" align="center">0.373</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold>Laboratory values</bold></td>
</tr>
<tr>
<td valign="top" align="left">Hemoglobin (g/dl)</td>
<td valign="top" align="center">13.5 &#x000B1; 1.8</td>
<td valign="top" align="center">13.7 &#x000B1; 1.7</td>
<td valign="top" align="center">13.4 &#x000B1; 2.0</td>
<td valign="top" align="center">0.205</td>
</tr>
<tr>
<td valign="top" align="left">Platelets (10<sup>3</sup>/mm<sup>3</sup>)</td>
<td valign="top" align="center">218.4 &#x000B1; 86.8</td>
<td valign="top" align="center">218.3 &#x000B1; 84.1</td>
<td valign="top" align="center">212.2 &#x000B1; 86.5</td>
<td valign="top" align="center">0.572</td>
</tr>
<tr>
<td valign="top" align="left">WBC (10<sup>3</sup>/mm<sup>3</sup>)</td>
<td valign="top" align="center">7.8 &#x000B1; 4.4</td>
<td valign="top" align="center">7.2 &#x000B1; 3.0</td>
<td valign="top" align="center">8.1 &#x000B1; 5.0</td>
<td valign="top" align="center">0.072</td>
</tr>
<tr>
<td valign="top" align="left">CRP (mg/L)</td>
<td valign="top" align="center">135.7 &#x000B1; 96.5</td>
<td valign="top" align="center">128.0 &#x000B1; 97.9</td>
<td valign="top" align="center">140.1. 94.1</td>
<td valign="top" align="center">0.312</td>
</tr>
<tr>
<td valign="top" align="left">D-dimers (ng/ml)</td>
<td valign="top" align="center">1,638.6 &#x000B1; 2,720.7</td>
<td valign="top" align="center">1,048.5 &#x000B1; 1,442.4</td>
<td valign="top" align="center">1,830.9 &#x000B1; 2,613.0</td>
<td valign="top" align="center">0.042</td>
</tr>
<tr>
<td valign="top" align="left">LDH (U/L)</td>
<td valign="top" align="center">968.4 &#x000B1; 1,183.8</td>
<td valign="top" align="center">988.6 &#x000B1; 608.8</td>
<td valign="top" align="center">1,000.3 &#x000B1; 595.8</td>
<td valign="top" align="center">0.877</td>
</tr>
<tr>
<td valign="top" align="left">Lactate (mmol/L)</td>
<td valign="top" align="center">1.0 &#x000B1; 0.6</td>
<td valign="top" align="center">1.0 &#x000B1; 0.5</td>
<td valign="top" align="center">1.1 &#x000B1; 0.6</td>
<td valign="top" align="center">0.659</td>
</tr>
<tr>
<td valign="top" align="left">cTnT (&#x003BC;g/L)</td>
<td valign="top" align="center">0.02 &#x000B1; 0.04</td>
<td valign="top" align="center">0.01 &#x000B1; 0.01</td>
<td valign="top" align="center">0.02 &#x000B1; 0.01</td>
<td valign="top" align="center">&#x0003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Creatinine (mg/dl)</td>
<td valign="top" align="center">1.2 &#x000B1; 1.2</td>
<td valign="top" align="center">1.0 &#x000B1; 0.9</td>
<td valign="top" align="center">1.3 &#x000B1; 1.4</td>
<td valign="top" align="center">0.012</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold>Chest CT</bold></td>
</tr>
<tr>
<td valign="top" align="left">Ground-glass opacity (<italic>n</italic>, %)</td>
<td valign="top" align="center">226 (80.7)</td>
<td valign="top" align="center">115 (87.7)</td>
<td valign="top" align="center">111 (74.4)</td>
<td valign="top" align="center">0.854</td>
</tr>
<tr>
<td valign="top" align="left">Interlobular septal thickening (<italic>n</italic>, %)</td>
<td valign="top" align="center">25 (8.9)</td>
<td valign="top" align="center">9 (6.8)</td>
<td valign="top" align="center">17 (11.4)</td>
<td valign="top" align="center">0.076</td>
</tr>
<tr>
<td valign="top" align="left">Pulmonary consolidation (<italic>n</italic>, %)</td>
<td valign="top" align="center">94 (33.5)</td>
<td valign="top" align="center">44 (33.5)</td>
<td valign="top" align="center">50 (33.5)</td>
<td valign="top" align="center">0.267</td>
</tr>
<tr>
<td valign="top" align="left">Pleural effusion (<italic>n</italic>, %)</td>
<td valign="top" align="center">14 (5.0)</td>
<td valign="top" align="center">4 (3.0)</td>
<td valign="top" align="center">10 (6.7)</td>
<td valign="top" align="center">0.068</td>
</tr>
<tr>
<td valign="top" align="left">ICU admission (<italic>n</italic>, %)</td>
<td valign="top" align="center">71 (18.2)</td>
<td valign="top" align="center">33 (25.1)</td>
<td valign="top" align="center">39 (26.1)</td>
<td valign="top" align="center">0.500</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p><italic>BMI, body mass index; CKD, chronic kidney disease; DM, diabetes mellitus; WBC, white blood cells; NLR, neutrophil to lymphocyte ratio; CRP, C-reactive protein; LDH, lactate dehydrogenase; cTnT, cardiac troponin T; CT, computed tomography; ICU, intensive care unit; CAC, coronary artery calcium</italic>.</p>
</table-wrap-foot>
</table-wrap>
<p>Univariate analysis for the prediction of MACE is shown in <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 1</xref>.</p>
<p>Multivariate analysis (<xref ref-type="table" rid="T2">Table 2</xref>) showed that a CAC score of 0 was inversely associated with the occurrence of MACE [<italic>p</italic> = 0.027, odds ratio (OR) = 0.209, 95% confidence interval (CI) 0.052&#x02013;0.833]. The negative predictive value of CAC score for MACE was 84.5% (sensitivity 72%, specificity 55%).</p>
<table-wrap position="float" id="T2">
<label>Table 2</label>
<caption><p>Predictors of MACE.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th/>
<th valign="top" align="center"><bold>OR</bold></th>
<th valign="top" align="center"><bold>95% CI</bold></th>
<th valign="top" align="center"><bold><italic>p</italic></bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Age</td>
<td valign="top" align="center">1.067</td>
<td valign="top" align="center">1.009&#x02013;1.129</td>
<td valign="top" align="center">0.024</td>
</tr>
<tr>
<td valign="top" align="left">Male gender</td>
<td valign="top" align="center">0.702</td>
<td valign="top" align="center">0.221&#x02013;2.228</td>
<td valign="top" align="center">0.548</td>
</tr>
<tr>
<td valign="top" align="left">Atrial fibrillation</td>
<td valign="top" align="center">1.175</td>
<td valign="top" align="center">0.182&#x02013;7.595</td>
<td valign="top" align="center">0.865</td>
</tr>
<tr>
<td valign="top" align="left">Creatinine</td>
<td valign="top" align="center">1.018</td>
<td valign="top" align="center">0.49&#x02013;2.090</td>
<td valign="top" align="center">0.962</td>
</tr>
<tr>
<td valign="top" align="left">CRP</td>
<td valign="top" align="center">1.009</td>
<td valign="top" align="center">1.004&#x02013;1.015</td>
<td valign="top" align="center">0.001</td>
</tr>
<tr>
<td valign="top" align="left">cTnT</td>
<td valign="top" align="center">1.072</td>
<td valign="top" align="center">1.026&#x02013;1.120</td>
<td valign="top" align="center">0.002</td>
</tr>
<tr>
<td valign="top" align="left">CAC score = 0</td>
<td valign="top" align="center">0.209</td>
<td valign="top" align="center">0.052&#x02013;0.833</td>
<td valign="top" align="center">0.027</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p><italic>CRP, C-reactive protein; cTnT, cardiac troponin T; CAC, coronary artery calcium; OR, odds ratio; CI, confidence interval; MACE, major adverse cardiovascular events</italic>.</p>
</table-wrap-foot>
</table-wrap>
<p>Reproducibility of CAC score assessment using Cohen&#x00027;s k showed substantial intraobserver and interobserver agreement for the total CAC score assessment (<italic>k</italic> = 0.859, 95% CI 0.678&#x02013;1.000, <italic>p</italic> &#x0003C; 0.001 and <italic>k</italic> = 0.795, 95% CI 0.581&#x02013;1.000, <italic>p</italic> &#x0003C; 0.001, respectively).</p>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>The main findings of this study were the following: (1) MACE rate in COVID-19 hospitalized patients was 21.8%; (2) the absence of CAC was independently associated with a lower rate of MACE in COVID-19 hospitalized patients.</p>
<p>COVID-19 promotes a rapid systemic inflammation and cytokine storm, which can cause vascular dysfunction, destabilization of atherosclerotic plaques, or myocardial infiltration, which are potential pathways for cardiovascular complications (<xref ref-type="bibr" rid="B14">14</xref>). The most commonly reported MACE in COVID-19 hospitalized patients include heart failure, arrhythmia, and acute coronary syndrome, similar to results from the present study (<xref ref-type="bibr" rid="B14">14</xref>&#x02013;<xref ref-type="bibr" rid="B16">16</xref>). Moreover, patients with pre-existing cardiac disease are more predisposed to develop cardiac complications during hospitalization for COVID-19 (<xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B15">15</xref>).</p>
<p>Similar to previous reports, in the present study, older age was independently associated with worse outcome of COVID-19 patients (<xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B18">18</xref>). Moreover, an increased cardiac troponin independently predicted MACE, which is in line with recent studies showing evidence of myocardial injury in hospitalized COVID-19 patients and subsequently increased disease severity (<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B19">19</xref>).</p>
<p>Current guidelines consider CAC score to be a risk modifier in primary prevention of cardiovascular disease (<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B6">6</xref>). Moreover, CAC score has been shown to improve cardiovascular risk prediction in addition to classical risk factors (<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B20">20</xref>) and to be a potential tool for risk reclassification (<xref ref-type="bibr" rid="B21">21</xref>&#x02013;<xref ref-type="bibr" rid="B24">24</xref>). The Multi-Ethnic Study of Atherosclerosis (MESA) showed that CAC improved risk prediction at 10-year follow-up compared with traditional risk factors alone (<xref ref-type="bibr" rid="B25">25</xref>).</p>
<p>Interestingly, multiple studies have focused on the role of the absence of CAC as a potential downward cardiovascular risk reclassification (<xref ref-type="bibr" rid="B26">26</xref>&#x02013;<xref ref-type="bibr" rid="B29">29</xref>). In the present study, the absence of CAC score independently predicted lower MACE rate in COVID-19 hospitalized patients.</p>
<p>Dillinger et al. (<xref ref-type="bibr" rid="B30">30</xref>) evaluated the role of CAC in COVID-19 patients hospitalized at the intensive care unit (ICU) and showed that the presence of CAC score was associated with the occurrence of mechanical ventilation, extracorporeal membrane oxygenation, or death. Compared to the present study and other previous series, mortality rate in the study of Dillinger et al. (<xref ref-type="bibr" rid="B30">30</xref>) was significantly lower, even if the authors reported only the mortality among ICU patients (<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B31">31</xref>, <xref ref-type="bibr" rid="B32">32</xref>). In our cohort, 71 (25.7%) patients were transferred to ICU, among whom 19 (26.7%) died. Surprisingly, the proportion of elevated CAC score in patients younger than 61 years old was higher in the study of Dillinger et al. (<xref ref-type="bibr" rid="B30">30</xref>) compared to the results from our cohort. For the same group of ethnicity, the MESA study showed that CAC score increased with age, which is comparable to data from the present study (<xref ref-type="bibr" rid="B33">33</xref>). In contrast to MESA, there was no significant difference in CAC score between genders in this study.</p>
<p>In another recent report by Nai Fovino et al. the presence of CAC in COVID-19 patients was associated with ICU admission and in-hospital mortality (<xref ref-type="bibr" rid="B34">34</xref>). However, this study had a small sample population in whom CAC score was evaluated as high or low-intermediate, and potential confounders were not included; therefore, the results cannot be compared to our cohort. Zimmerman et al. also evaluated the role of CAC in the prediction of ICU admission and death in COVID-19 patients (<xref ref-type="bibr" rid="B35">35</xref>). Nevertheless, in this study, patients with a history of coronary artery disease were not excluded from the analysis, and the potential relationship between CAC and inflammatory markers was not assessed.</p>
<p>Although recent studies focused on the power of CAC score 0 to predict an improved cardiovascular outcome, data regarding the role of CAC in COVID-19 patients with classical cardiac risk factors are still limited (<xref ref-type="bibr" rid="B27">27</xref>, <xref ref-type="bibr" rid="B36">36</xref>). In this study, the absence of CAC translated into a low risk for MACE in COVID-19 patients, independent of age and the presence of risk factors or inflammation, reinforcing the idea that the assessment of CAC score in hospitalized COVID-19 patients could be a useful marker for patients&#x00027; risk stratification and management.</p>
<p>At the beginning of the pandemic, RT-PCR tests were not widely available; therefore, a systematic chest CT was performed in almost all COVID-19 patients. The ability to assess CAC score on non-gated chest CT allows the application of CAC to the risk evaluation of COVID-19 patients with no additional cost or time consumption. Moreover, most studies report a low-dose radiation for chest CT in COVID-19 patients (<xref ref-type="bibr" rid="B37">37</xref>). The semi-qualitative assessment of CAC on routine chest CT has proved to be accurate and reproducible when compared to Agatston scoring (<xref ref-type="bibr" rid="B10">10</xref>). Similarly, in our study intraobserver and interobserver reproducibility of CAC score was very good.</p>
<p>Evidence that viral infections represent a trigger for cardiovascular events is increasing, but data regarding long-term follow-up of patients admitted with respiratory viral diseases are still scarce (<xref ref-type="bibr" rid="B38">38</xref>, <xref ref-type="bibr" rid="B39">39</xref>). Future directions should focus on the implementation of CAC score into mid-term and long-term follow-up of this particular population, to provide a more precise and earlier estimation of cardiovascular risk.</p>
</sec>
<sec id="s5">
<title>Study Limitations</title>
<p>This was a single-center study, the sample size was relatively small, and no comparison with a control group was performed; therefore, the extrapolation of these results is limited. The method used to assess CAC is a semi-qualitative scoring system using a non-gated chest CT. The absence of triggering, the lower temporal resolution, and larger field of view which alters the voxel size might modify CAC score assessment. However, this method has been previously validated against quantitative CAC assessment, and its accuracy to predict Agatston score was demonstrated (<xref ref-type="bibr" rid="B10">10</xref>).</p>
</sec>
<sec sec-type="conclusions" id="s6">
<title>Conclusion</title>
<p>In this study, the absence of CAC had a high negative predictive value for MACE in patients hospitalized with COVID-19, independent of the presence of cardiac risk factors. A semi-qualitative assessment of CAC is a simple, reproducible, and non-invasive measure that may be useful for the risk stratification of COVID-19 patients.</p>
</sec>
<sec sec-type="data-availability-statement" id="s7">
<title>Data Availability Statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p>
</sec>
<sec id="s8">
<title>Ethics Statement</title>
<p>The studies involving human participants were reviewed and approved by Medical Ethics Committee, University Hospital of Brussels. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.</p>
</sec>
<sec id="s9">
<title>Author Contributions</title>
<p>M-LL, SL, AM, and BC contributed to the conception and design of the study. M-LL, AM, and SL wrote the first draft of the manuscript. AM and JMa performed the statistical analysis. DB, JMe, SB, and KT performed CT analysis. ES, BR, KV, TD, BK, XG, and CF participated to the investigation, clinical assessment and database. CW, SD, and BC contributed to project administration, supervision and validation. All authors contributed to manuscript revision, read, and approved the submitted version.</p>
</sec>
<sec sec-type="COI-statement" id="conf1">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
</body>
<back>
<sec sec-type="supplementary-material" id="s10">
<title>Supplementary Material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fcvm.2021.684528/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fcvm.2021.684528/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Table_1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink"/>
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