<?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.152404.1</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>Platelet indices as diagnostic and prognostic markers in acute coronary syndrome</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: awaiting peer review]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Krishnan</surname>
                        <given-names>Gokul</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</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/">Writing &#x2013; Original Draft Preparation</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-9714-0904</uri>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Prabhu</surname>
                        <given-names>M Mukhyaprana</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0003-0679-3323</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Stanley</surname>
                        <given-names>Weena</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-9266-8929</uri>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Department of Medicine, Manipal, Manipal Academy of Higher Education, Kasturba Medical College Manipal, Manipal, Karnataka, India</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:mm.prabhu@manipal.edu">mm.prabhu@manipal.edu</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>15</day>
                <month>8</month>
                <year>2024</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2024</year>
            </pub-date>
            <volume>13</volume>
            <elocation-id>927</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>7</day>
                    <month>8</month>
                    <year>2024</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Krishnan G et al.</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/13-927/pdf"/>
            <abstract>
                <sec>
                    <title>Background</title>
                    <p>Acute coronary syndromes refer to STEMI, NSTEMI and unstable angina.</p>
                    <p>The preferred biomarkers for assessing myocardial damage are cTnI and cTnT, and high-sensitivity cardiac troponin assays are recommended in clinical practice. Other biomarkers such as CK-MB have lower sensitivity and specificity.</p>
                    <p>Platelets play a major role in thrombosis, which is a causative factor for most acute coronary syndromes. In our study, we attempted to analyze the effectiveness of platelet indices (mean platelet volume, platelet count, and platelet distribution width) as diagnostic and prognostic markers in acute coronary syndromes.</p>
                    <p>Our data suggest that mean platelet volume and platelet distribution width are potential diagnostic markers, and plateletcrits can serve as prognostic markers.</p>
                </sec>
                <sec>
                    <title>Methods</title>
                    <p>A total of 290 subjects were recruited for the study, including 145 cases and 145 controls matched for sex and age. Cases presented with the first episode of acute coronary syndrome. Controls are those without acute coronary syndrome during present admission or in the past.</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>MPV and plateletcrit correlated with both troponin T and pro-BNP, whereas PDW showed a positive correlation only with troponin T. The only significant correlation was between the plateletcrit and pro-BNP levels. The plateletcrit showed a positive correlation with other parameters (degree of ventricular dysfunction, severity of coronary artery disease, and presence of arrhythmia). On comparing platelet indices with risk factors for coronary artery disease, such as diabetes mellitus and dyslipidemia, MPV showed a positive correlation with HbA1c and the entire lipid profile, whereas PDW showed a positive correlation only with HbA1c and triglycerides. The plateletcrit was positively correlated with HbA1c and total cholesterol levels.</p>
                </sec>
                <sec>
                    <title>Conclusions</title>
                    <p>Our data suggest that mean platelet volume and platelet distribution width are potential diagnostic markers, whereas plateletcrits can serve as prognostic markers.</p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>Platelet indices</kwd>
                <kwd>Acute coronary syndromes</kwd>
                <kwd>MPV</kwd>
                <kwd>PCT</kwd>
                <kwd>PDW</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="sec5" sec-type="intro">
            <title>Introduction</title>
            <p>Acute coronary syndrome (ACS) is a major cause of mortality worldwide. There are several protocols for the diagnosis and triaging of ACS, including ST-elevation myocardial infarction (STEMI), non-ST-elevation myocardial infarction (NSTEMI), and unstable angina, all aimed at timely diagnosis and early referral if indicated, which is essential for a favorable outcome.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup>
            </p>
            <p>The preferred biomarkers for assessing myocardial damage in ACS are cardiac troponin T (cTnT) and cardiac troponin I (cTnI). It is recommended that high-sensitivity cardiac troponin assays should be used in clinical practice.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup> Other biomarkers such as CK-MB have lower sensitivity and specificity.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> Platelets play a major role in thrombosis, which is a causative factor for most acute coronary syndromes.</p>
            <p>Enzyme markers with good specificity have a few disadvantages, such as being negative during the window period and may not be available at all centers.
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> Therefore in our study, we attempted to determine how effective platelet indices (mean platelet volume, platelet count, and platelet distribution width) are diagnostic markers in acute coronary syndromes. Additionally, we attempted to assess their prognostic ability among cases of ACS.</p>
        </sec>
        <sec id="sec6" sec-type="methods">
            <title>Methods</title>
            <sec id="sec7">
                <title>Study design</title>
                <p>This prospective case-control study was conducted at Kasturba Hospital, Manipal, India, from May 2020 to September 2021.</p>
            </sec>
            <sec id="sec8">
                <title>Setting</title>
                <p>The study was approved by our Institutional Review Board (IRB) known as Kasturba Medical College and Kasturba Hospital Institutional Ethics Committee (reference number: 954/2019) on 19th November, 2019. This study was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was obtained from all the participants.</p>
            </sec>
            <sec id="sec9">
                <title>Participants and sample size</title>
                <p>The total sample size was 290, with cases and controls in a ratio of 1:1. All the cases meeting the inclusion criteria over the mentioned study period were included. Blood was collected from cases and controls in ethylenediaminetetraacetic acid (EDTA) tubes, and samples were analyzed using automated analyzers: Beckman Coulter DxH&#x2122; 800, Beckman Coulter DxH&#x2122; 900 and Sysmex XN1500 &#x2122;.</p>
                <p>Inclusion criteria for cases
                    <list list-type="bullet">
                        <list-item>
                            <label>-</label>
                            <p>Those presenting with the first episode of acute coronary syndrome (ACS)</p>
                        </list-item>
                    </list>
                </p>
                <p>Inclusion criteria for controls
                    <list list-type="bullet">
                        <list-item>
                            <label>-</label>
                            <p>Those without acute coronary syndrome at present or in the past</p>
                        </list-item>
                    </list>
                </p>
                <p>Exclusion criteria for cases and controls
                    <list list-type="bullet">
                        <list-item>
                            <label>-</label>
                            <p>Those on antiplatelet agents</p>
                        </list-item>
                        <list-item>
                            <label>-</label>
                            <p>Those with abnormalities in platelet count (thrombocytopenia/thrombocytosis)</p>
                        </list-item>
                    </list>
                </p>
            </sec>
            <sec id="sec10">
                <title>Variables</title>
                <p>Diagnosis of acute coronary syndrome among cases was made according to the fourth universal definition of myocardial infarction.
                    <sup>
                        <xref ref-type="bibr" rid="ref8">8</xref>
                    </sup> Those with unstable angina, non ST elevation myocardial infarction and ST elevation myocardial infarction were considered. Platelet indices (MPV, PCT and PDW) at admission were noted among both the groups. Among cases, in addition to platelet indices, other parameters like troponin T levels, pro BNP levels echocardiography findings, and coronary angiography results were also recorded with intend to analyse their ability to serve as potential prognostic markers.</p>
            </sec>
            <sec id="sec11">
                <title>Data sources &amp; bias</title>
                <p>Cases as mentioned above were cases of acute coronary syndrome. Controls were patients who presented to our center but without a diagnosis of ACS. Cases and controls were matched for age and gender.</p>
            </sec>
            <sec id="sec12">
                <title>Statistical analysis</title>
                <p>Statistical analysis was done using SPSS version 21.0.
                    <sup>
                        <xref ref-type="bibr" rid="ref8">8</xref>
                    </sup> Continuous and normally distributed variables were expressed as mean &#x00b1; standard deviation, and general characteristics were compared using the chi-square test and t-test. Statistical significance was set of statistical significance.</p>
            </sec>
        </sec>
        <sec id="sec13" sec-type="results">
            <title>Results</title>
            <p>A total of 145 patients and 145 controls were included in this study [
                <xref ref-type="table" rid="T1">Table 1</xref>]. Among the cases, the majority had STEMI, followed by NSTEMI, and unstable angina [
                <xref ref-type="table" rid="T2">Table 2</xref>]. On comparing platelet indices between cases and controls, all of them (MPV, plateletcrit, and PDW) were found to be higher among the cases. However, only the MPV was statistically significant [
                <xref ref-type="table" rid="T3">Table 3</xref>].</p>
            <table-wrap id="T1" orientation="portrait" position="float">
                <label>Table 1. </label>
                <caption>
                    <title>Demographics.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Age</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Cases</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Controls</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">30 and below</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.1%(3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.1%(6)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">31-40</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.1%(3)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">2.1%(3)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">41-50</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">15.2%(23)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">14.5%(21)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">51-60</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">34.5%(49)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">33.8 %(49)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">61-70</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">35.2%(51)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">35.9%(52)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2265;70</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11%(16)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">9.7%(14)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Gender</td>
                            <td colspan="1" rowspan="1"/>
                            <td colspan="1" rowspan="1"/>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Male</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">110</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">110</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Female</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">35</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">35</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <table-wrap id="T2" orientation="portrait" position="float">
                <label>Table 2. </label>
                <caption>
                    <title>Acute coronary syndrome subtypes among cases.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">ACS subtypes</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Frequency (percentage)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">STEMI</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">80(55.2%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">NSTEMI</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">52(35.9%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Unstable angina</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">13(9%)</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <table-wrap id="T3" orientation="portrait" position="float">
                <label>Table 3. </label>
                <caption>
                    <title>Platelet indices among cases and controls.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Platelet indices</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Case (mean, standard deviation)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Control (mean, standard deviation)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">P value (t test)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">MPV (fL)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.38 &#x00b1; 0.96</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.03 &#x00b1; 0.90</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.006</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Plateletcrit (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.2198 &#x00b1; 0.0647</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.2158 &#x00b1; 0.0588</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.585</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">PDW (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16.65 &#x00b1; 0.97</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16.60 &#x00b1; 0.60</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.160</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>When platelet indices were compared to the laboratory markers, Troponin T, pro-BNP, MPV, and plateletcrit correlated with both troponin T and pro-BNP, while PDW showed a positive correlation only with troponin T. The only significant correlations were between plateletcrits and pro-BNP [
                <xref ref-type="table" rid="T4">Table 4</xref>]. The degree of ventricular dysfunction, severity of coronary artery disease, and existence or absence of arrhythmias were among the other criteria whose relation with the platelet indices were studied. Plateletcrit showed a positive relationship with all the mentioned parameters [
                <xref ref-type="table" rid="T5">Tables 5</xref>,
                <xref ref-type="table" rid="T6">6</xref>].</p>
            <table-wrap id="T4" orientation="portrait" position="float">
                <label>Table 4. </label>
                <caption>
                    <title>Relation between platelet indices and troponin T &amp; pro-BNP.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="2" valign="top">Platelet indices</th>
                            <th align="left" colspan="2" rowspan="1" valign="top">Troponin T</th>
                            <th align="left" colspan="2" rowspan="1" valign="top">pro BNP</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Pearson correlation</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">P value</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Pearson correlation</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">P value</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">MPV</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.092</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.269</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.145</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.115</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Plateletcrit</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.098</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.239</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.331</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.000</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">PDW</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.091</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.277</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.015</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.867</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <table-wrap id="T5" orientation="portrait" position="float">
                <label>Table 5. </label>
                <caption>
                    <title>Relation between platelet indices and severity of ventricular dysfunction.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="2" valign="top">Platelet indices</th>
                            <th align="left" colspan="5" rowspan="1" valign="top">Ventricular dysfunction</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Absent</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Mild</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Moderate</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Severe</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">P value</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">MPV (fL)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.26</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.50</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.59</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.12</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.312</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Plateletcrit (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.2086</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.2247</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.2308</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.2523</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.153</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">PDW (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16.58</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16.68</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16.75</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16.77</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.850</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <table-wrap id="T6" orientation="portrait" position="float">
                <label>Table 6. </label>
                <caption>
                    <title>Relation between platelet indices and severity of coronary heart disease and arrhythmia.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="2" valign="top">Platelet indices</th>
                            <th align="left" colspan="4" rowspan="1" valign="top">Severity of coronary artery disease</th>
                            <th align="left" colspan="3" rowspan="1" valign="top">Arrhythmia</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Single</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Double</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Triple</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">P value</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Present</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Absent</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">P value</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">MPV (fL)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.36</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.38</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.38</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.990</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.41</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">8.38</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.907</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Plateletcrit (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.2087</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.2229</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.2256</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.370</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.2666</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.2151</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.006</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">PDW (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16.65</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16.64</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16.63</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.994</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16.96</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16.62</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.229</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>Analysis of the relationship between platelet indices and other risk factors of coronary artery disease, such as diabetes mellitus (represented by HbA1c) and dyslipidemia (lipid profile), showed that MPV had a positive relationship with HbA1C and the entire lipid profile, while PDW showed a positive relationship with only Hba1C and triglycerides. Plateletcrits had a positive relation with Hba1C and total cholesterol [
                <xref ref-type="table" rid="T7">Table 7</xref>].</p>
            <table-wrap id="T7" orientation="portrait" position="float">
                <label>Table 7. </label>
                <caption>
                    <title>Relation between platelet indices and glycemic status and lipid profile.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="2" rowspan="1" valign="top">Platelet indices</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">HbA1c</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Total cholesterol</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Triglyceride</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">HDL</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">LDL</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">MPV</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Pearson correlation</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.199</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.231</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.100</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.043</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.221</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">p value</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.018</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.006</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.234</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.611</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.008</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">Plateletcrit</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Pearson correlation</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.097</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.728</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.035</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.034</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.020</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">p value</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.251</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.029</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.675</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.689</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.813</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="2" valign="top">PDW</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Pearson correlation</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.073</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.011</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.120</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.006</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">-0.009</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">p value</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.391</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.899</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.153</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.945</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">0.911</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
        </sec>
        <sec id="sec14" sec-type="discussion">
            <title>Discussion</title>
            <p>Acute coronary syndrome refers to STEMI, NSTEMI, and unstable angina. Myocardial infarction is defined as &#x201c;myocardial cell death due to prolonged ischemia.&#x201d;
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup>
            </p>
            <p>The first ultrastructural alterations include reduced cellular glycogen, loosened myofibrils, and sarcolemmal disruption, which can occur within 10&#x2013;15 min after the onset of ischemia.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup> Mitochondrial anomalies can be observed by electron microscopy as soon as 10 min after cardiac blockage and are progressive.
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> Necrosis proceeds from the subendocardium to the subepicardium over several hours in an experimental setting. An increase in collateral flow, decreased drivers of cardiac oxygen demand, and intermittent occlusion or reperfusion that may prepare the heart can all add to the length of time.</p>
            <p>Significance is that when reperfusion therapy is administered promptly, it helps to prevent myocardial ischemia.
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> Cardiac troponins I (cTnI) and T (cTnT) are components of the contractile machinery of myocardial cells and are found virtually exclusively in the heart.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup>
            </p>
            <p>Injuries to non-cardiac tissues have not been linked to an increase in cTnI levels. This situation is more complicated for cTnTs. Biochemical evidence suggests that the cardiac troponin T assay detects proteins expressed by damaged skeletal muscle, implying that cTnT increases could come from skeletal muscle in some cases.
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup> The preferred biomarkers for assessing myocardial damage are cTnI and cTnT, and it is recommended that high-sensitivity cardiac troponin assays be used in clinical practice.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup> Other biomarkers, such as CK-MB, have lower sensitivity and specificity.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> Myocardial injury is said to be present when the levels of cardiac troponin in the blood are above the 99th percentile of the upper reference limit. Injury may be acute, as demonstrated by a &#x201c;newly found dynamic rising and/or falling level of cTn values above the 99th percentile URL, or chronic, as evidenced by continuously elevated cTn levels&#x201d;.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup>
            </p>
            <p>The commonly measured platelet indices are the mean platelet volume (MPV), plateletcrit (PCT), and platelet distribution width (PDW). The mean platelet volume is a measure of the platelet volume measured in femtolitres, whereas PDW and PCT are presented as percentages. Plateletcrit refers to the volume occupied by platelets in blood. PDW is an indicator of volume variability in platelet size.</p>
            <p>Regarding the role of platelet indices in acute coronary syndrome, larger and hyperactive platelets play a pivotal role in accelerating the formation and propagation of intracoronary thrombi, leading to acute thrombotic events. Larger platelets are enzymatically and metabolically active and have higher thrombotic ability than smaller platelets.
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref22">22</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref23">23</xref>
                </sup>
            </p>
            <p>We evaluated the diagnostic and prognostic significance of platelet indices in ACS, considering the function of platelets in the pathophysiology of the disease.</p>
            <sec id="sec15">
                <title>MPV in ACS</title>
                <p>The literature shows that MPV is higher in patients with myocardial infarction than in those with stable angina pectoris and healthy controls, suggesting that MPV is a risk factor for the severity of coronary artery disease [
                    <xref ref-type="table" rid="T8">Table 8</xref>].
                    <sup>
                        <xref ref-type="bibr" rid="ref24">24</xref>
                    </sup>
                    <sup>&#x2013;</sup>
                    <sup>
                        <xref ref-type="bibr" rid="ref29">29</xref>
                    </sup> In our study, MPV is significantly higher among ACS cases as compared to controls with p value 0.006 and mean difference of 0.35 fL (8.38 fL vs 8.03 fL), suggesting that it may be used as a diagnostic marker of ACS. Regarding MPV as a prognostic marker, it was found to have a positive correlation with trop T, pro-BNP and presence of arrhythmia.</p>
                <table-wrap id="T8" orientation="portrait" position="float">
                    <label>Table 8. </label>
                    <caption>
                        <title>Results of other similar studies.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top"/>
                                <th align="left" colspan="1" rowspan="1" valign="top">Present study</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Akula S P et al.
                                    <sup>
                                        <xref ref-type="bibr" rid="ref24">24</xref>
                                    </sup>
                                </th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Gururajaprasad et al.
                                    <sup>
                                        <xref ref-type="bibr" rid="ref25">25</xref>
                                    </sup>
                                </th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Cost a sc et al.
                                    <sup>
                                        <xref ref-type="bibr" rid="ref26">26</xref>
                                    </sup>
                                </th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Assiri AS et al.
                                    <sup>
                                        <xref ref-type="bibr" rid="ref27">27</xref>
                                    </sup>
                                </th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Pal R et al.
                                    <sup>
                                        <xref ref-type="bibr" rid="ref28">28</xref>
                                    </sup>
                                </th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Yilmaz M B et al.
                                    <sup>
                                        <xref ref-type="bibr" rid="ref29">29</xref>
                                    </sup>
                                </th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Country of origin</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">India</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">India</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">India</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Brazil</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Saudi Arabia</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">India</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Turkey</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Year of publication</td>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">2017</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2018</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2015</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2012</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2014</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2008</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Sample size</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">290</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">120</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">300</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">83</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">261</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">215</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">336</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">MPV (fL) (cases vs controls)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.38 vs 8.03</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11.31 vs 10.5</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.5&#x00b1;0.76 vs 9.4&#x00b1;0.7</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.6&#x00b1;0.9 vs 8.1&#x00b1;0.6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.99&#x00b1;1.5 vs 8.38&#x00b1;0.51</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11.44&#x00b1;1.23 vs 9.91&#x00b1;1.275</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.4&#x00b1;0.6 vs 8.9&#x00b1;0.7</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">P value</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.006</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.04</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.01</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.009</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Plateletcrit(%)(cases vs controls)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.2198 vs 0.2158</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.2217 vs 0.144</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Not assessed</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.16&#x00b1;0.1 vs 0.19&#x00b1;0.1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Not assessed</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Not assessed</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Not assessed</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">P value</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.585</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.0001</td>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">&gt;0.05</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">PDW(%)(cases vs controls)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">16.65 vs 16.60</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">17.34 vs 15.21</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.1&#x00b1;1.68 vs 9.8&#x00b1;1.4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">16.7&#x00b1;2.8 vs 14.1&#x00b1;1.7</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15.88&#x00b1;1.5 vs 11.96&#x00b1;1.8</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Not assessed</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Not assessed</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">P value</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.160</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.0001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.0001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.01</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">.001</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
                <p>However none of them were of statistical significance.</p>
            </sec>
            <sec id="sec16">
                <title>PCT in ACS</title>
                <p>Studies have shown that higher PCT levels are observed in patients with ACS and are associated with worse prognosis [
                    <xref ref-type="table" rid="T8">Table 8</xref>]. Our study also noted that plateletcrit was higher among cases but not statistically significant. However, the plateletcrit was the only platelet index that was found to have a positive correlation with all the prognostic markers assessed (troponin T, pro-BNP, ventricular dysfunction, presence of arrhythmia, and severity of vessel disease). Thus, we conclude that PCT is a potential prognostic marker in patients diagnosed with ACS but may not be a suitable diagnostic marker.</p>
            </sec>
            <sec id="sec17">
                <title>PDW in ACS</title>
                <p>PDW directly measures the variability in platelet size, changes with platelet activation, and reflects heterogeneity in platelet morphology. Under physiological conditions, there is a direct relationship between the MPV and PDW; both usually change in the same direction. In our study, we observed that the PDW was higher in the ACS group, but not significantly higher.
                    <sup>
                        <xref ref-type="bibr" rid="ref30">30</xref>
                    </sup> Among prognostic markers, PDW has been shown to be positively correlated with troponin T, ventricular dysfunction, and the presence of arrhythmia [
                    <xref ref-type="table" rid="T8">Table 8</xref>].</p>
                <p>Comparing platelet indices with other known risk factors, such as diabetes mellitus and dyslipidemia, we found that MPV showed a positive but insignificant correlation with HbA1C and lipid profile. PDW showed a positive correlation only with HbA1C and triglyceride levels. From the results of our study, we can conclude that MPV and PDW are potential diagnostic markers for ACS, with MPV being superior to PDW. PCT was found to be superior to both MPV and PDW. In conclusion, MPV and PDW are potential diagnostic markers of ACS, with MPV being superior to PDW. PCT was found to be superior to both MPV and PDW as a prognostic marker.</p>
            </sec>
        </sec>
        <sec id="sec18" sec-type="conclusion">
            <title>Conclusion</title>
            <p>We suggest that platelet indices be applied in the following clinical practice methods. In an outpatient setting where an individual with risk factors is presented for routine evaluation, if platelet indices are grossly deranged, then they may be candidates for further evaluation in the form of coronary CT or coronary angiography to rule out underlying coronary artery disease.</p>
            <p>In case of an emergency setting with a patient presenting with acute onset symptoms and if ACS is suspected, deranged platelet indices can be used in the periphery where cardiac biomarkers are not available to decide on referral to a higher center. In other words, platelet indices can be used to triage suspected ACS patients. If ACS is confirmed, platelet indices can be used to prognosticate.</p>
            <sec id="sec19">
                <title>Limitations of study</title>
                <p>However, there are limitations associated with applying platelet indices in routine practice, and a few limitations of our study have been elaborated. Patients on antiplatelet agents and those with haematological malignancies were excluded from the study.</p>
            </sec>
        </sec>
        <sec id="sec20">
            <title>Ethics and consent</title>
            <p>The study was approved by our Institutional Review Board (IRB) known as Kasturba Medical College and Kasturba Hospital Institutional Ethics Committee (reference number: 954/2019) on 19th November, 2019. This study was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants.</p>
        </sec>
    </body>
    <back>
        <sec id="sec23" sec-type="data-availability">
            <title>Data availability</title>
            <sec id="sec24">
                <title>Underlying data</title>
                <p>Figshare: Platelet indices as diagnostic and prognostic markers in acute coronary syndrome, 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.25999672">https://doi.org/10.6084/m9.figshare.25999672</ext-link>.
                    <sup>

                        <xref ref-type="bibr" rid="ref31">31</xref>
</sup>
                </p>
                <p>The data contain the three platelet indices (plateletcrit, platelet distribution width, and mean platelet volume) and various other parameters considered, ranging from lipid profile to echocardiography and coronary angiography findings.</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 Common Attribution 4.0 International licence</ext-link> (CC-BY 4.0).</p>
            </sec>
        </sec>
        <ack>
            <title>Acknowledgments</title>
            <p>We would like to thank the Manipal Academy of Higher Education for providing support in performing the study. Permission has been obtained for the same.</p>
        </ack>
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