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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">ijcs</journal-id>
      <journal-title-group>
        <journal-title>International Journal of Cardiovascular Sciences</journal-title>
        <abbrev-journal-title abbrev-type="publisher">Int J Cardiovasc Sci </abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="ppub">2359-4802</issn>
      <issn pub-type="epub">2359-5647</issn>
      <publisher>
        <publisher-name>Sociedade Brasileira de Cardiologia</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id specific-use="scielo-v3" pub-id-type="publisher-id">rmJWmJXJdTqBv9vXmgHhCzq</article-id>
      <article-id specific-use="scielo-v2" pub-id-type="publisher-id">S2359-56472023000100230</article-id>
      <article-id pub-id-type="other">00230</article-id>
      <article-id pub-id-type="doi">10.36660/ijcs.20220009</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>ORIGINAL ARTICLE</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>The Impact of the COVID-19 Pandemic on ST Elevation Myocardial Infarction Care Indicators at a Public Hospital in Brazil</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0003-1810-7335</contrib-id>
          <name>
            <surname>Vargas</surname>
            <given-names>T&#250;lio Torres</given-names>
          </name>
          <role>Conception and design of the research</role>
          <role>analysis and interpretation of the data and statistical analysis</role>
          <role>acquisition of data</role>
          <role>writing of the manuscript</role>
          <role>critical revision of the manuscript for intellectual content</role>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-4301-8230</contrib-id>
          <name>
            <surname>Sonoda</surname>
            <given-names>Lucas Yuji</given-names>
          </name>
          <role>acquisition of data</role>
          <role>critical revision of the manuscript for intellectual content</role>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0003-3896-3411</contrib-id>
          <name>
            <surname>Hawerroth</surname>
            <given-names>Maria da Gra&#231;a Lepre</given-names>
          </name>
          <role>acquisition of data</role>
          <role>critical revision of the manuscript for intellectual content</role>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0003-1964-8002</contrib-id>
          <name>
            <surname>Coutinho</surname>
            <given-names>Stefania de Figueiredo</given-names>
          </name>
          <role>acquisition of data</role>
          <role>critical revision of the manuscript for intellectual content</role>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0003-0483-5104</contrib-id>
          <name>
            <surname>Ferreira</surname>
            <given-names>Gabriela Gon&#231;alves</given-names>
          </name>
          <role>acquisition of data</role>
          <role>critical revision of the manuscript for intellectual content</role>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-0454-2881</contrib-id>
          <name>
            <surname>Mendes</surname>
            <given-names>Mariane da Mata Morato</given-names>
          </name>
          <role>acquisition of data</role>
          <role>critical revision of the manuscript for intellectual content</role>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-2147-3371</contrib-id>
          <name>
            <surname>Costa</surname>
            <given-names>Marilene Ribeiro Almeida</given-names>
          </name>
          <role>critical revision of the manuscript for intellectual content</role>
          <role>translate to English</role>
          <xref ref-type="aff" rid="aff2">
            <sup>2</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-1090-8165</contrib-id>
          <name>
            <surname>Schmidt</surname>
            <given-names>Andr&#233;</given-names>
          </name>
          <role>critical revision of the manuscript for intellectual content</role>
          <xref ref-type="aff" rid="aff3">
            <sup>3</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0001-5242-329X</contrib-id>
          <name>
            <surname>Pazin</surname>
            <given-names>Antonio</given-names>
            <suffix>Filho</suffix>
          </name>
          <role>Conception and design of the research</role>
          <role>analysis and interpretation of the data and statistical analysis</role>
          <role>critical revision of the manuscript for intellectual content</role>
          <xref ref-type="aff" rid="aff3">
            <sup>3</sup>
          </xref>
        </contrib>
      </contrib-group>
      <aff id="aff1">
        <label>1</label>
        <institution content-type="orgname">Universidade do Estado de Minas Gerais</institution>
        <addr-line>
          <named-content content-type="city">Passos</named-content>
          <named-content content-type="state">MG</named-content>
        </addr-line>
        <country country="BR">Brazil</country>
        <institution content-type="original">Universidade do Estado de Minas Gerais, Passos, MG &#8211; Brazil</institution>
      </aff>
      <aff id="aff2">
        <label>2</label>
        <institution content-type="orgname">Unimontes</institution>
        <institution content-type="orgdiv1">CCBS</institution>
        <addr-line>
          <named-content content-type="city">Montes Claros</named-content>
          <named-content content-type="state">MG</named-content>
        </addr-line>
        <country country="BR">Brazil </country>
        <institution content-type="original">Unimontes CCBS, Montes Claros, MG &#8211; Brazil </institution>
      </aff>
      <aff id="aff3">
        <label>3</label>
        <institution content-type="orgname">Universidade de S&#227;o Paulo</institution>
        <addr-line>
          <named-content content-type="city">Ribeir&#227;o Preto</named-content>
          <named-content content-type="state">SP</named-content>
        </addr-line>
        <country country="BR">Brazil</country>
        <institution content-type="original">Universidade de S&#227;o Paulo, Ribeir&#227;o Preto, SP &#8211; Brazil</institution>
      </aff>
      <author-notes>
        <corresp id="c01"> Mailing Address: T&#250;lio Torres Vargas Universidade do Estado de Minas Gerais. Avenida Juca Stockler. Postal code: 37900-457. Passos, MG &#8211; Brazil E-mail: <email>tt.vargas@uol.com.br</email> </corresp>
        <fn fn-type="conflict">
          <p>Potential Conflict of Interest</p>
          <p>No potential conflict of interest relevant to this article was reported.</p>
        </fn>
      </author-notes>
      <pub-date date-type="pub" publication-format="electronic">
        <day>04</day>
        <month>08</month>
        <year>2023</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <year>2023</year>
      </pub-date>
      <volume>36</volume>
      <elocation-id>e20220009</elocation-id>
      <history>
        <date date-type="received">
          <day>28</day>
          <month>01</month>
          <year>2022</year>
        </date>
        <date date-type="rev-recd">
          <day>9</day>
          <month>04</month>
          <year>2023</year>
        </date>
        <date date-type="accepted">
          <day>16</day>
          <month>05</month>
          <year>2023</year>
        </date>
      </history>
      <permissions>
        <license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/" xml:lang="en">
          <license-p> This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. </license-p>
        </license>
      </permissions>
      <abstract>
        <title>Abstract</title>
        <sec>
          <title>Background</title>
          <p> International publications have shown that the COVID-19 pandemic has negatively impacted the indicators of care for ST-segment elevation acute myocardial infarction (STEMI), with a potential increase in morbidity and mortality.</p>
        </sec>
        <sec>
          <title>Objectives</title>
          <p> To compare mortality, time from symptom onset to primary angioplasty (total delay [TD]), time from symptom onset to initial medical contact (patient delay [PD]), and time from initial medical contact to guidewire insertion in the hemodynamics laboratory (system delay [SD]) among patients admitted for STEMI at the Hemodynamics Service of Santa Casa de Passos, Minas Gerais, Brazil before and after the declaration of the COVID-19 pandemic by the World Health Organization, assessing the impact of the COVID-19 pandemic on STEMI care indicators.</p>
        </sec>
        <sec>
          <title>Methods</title>
          <p> This is a before-and-after study involving patients hospitalized with STEMI undergoing primary angioplasty. Data were collected retrospectively through medical record review. Clinical and demographic profiles and outcomes between the pre-pandemic and pandemic groups were compared using the chi-square test for categorical variables or Student's t-test for continuous variables. A significance level of p &lt; 0.05 was adopted.</p>
        </sec>
        <sec>
          <title>Results</title>
          <p> There were no differences in TD (pre-pandemic: 300 min [&#177; 159 min], 95% CI 277.1 to 322.6; pandemic: 300 min [&#177; 148 min], 95% CI 274.3 to 326.6, p = 0.97). However, there was an increase in SD (pre-pandemic: 145 min [&#177; 97 min], 95% CI 122.7 to 167.9; pandemic: 178 min [&#177; 96 min], 95% CI 157.4 to 197.9, p = 0.037). There was no increase in PD (pre-pandemic: 145 min &#177; 133 min; pandemic: 130 min &#177; 117 min, p = 0.44), and no differences in mortality were observed (pre-pandemic: 9.7%; pandemic: 12%, p = 0.49).</p>
        </sec>
        <sec>
          <title>Conclusion</title>
          <p> The COVID-19 pandemic increased SD in the management of STEMI in the region of Passos, Minas Gerais. There were no differences in PD, TD, and in-hospital mortality.</p>
        </sec>
      </abstract>
      <kwd-group xml:lang="en">
        <kwd>ST Elevation Myocardial Infarction</kwd>
        <kwd>COVID-19</kwd>
        <kwd>Reperfusion</kwd>
        <kwd>Quality Indicators, Health Care</kwd>
      </kwd-group>
      <counts>
        <fig-count count="1"/>
        <table-count count="5"/>
        <equation-count count="0"/>
        <ref-count count="23"/>
      </counts>
    </article-meta>
  </front>
  <body>
    <sec sec-type="intro">
      <title>Introduction</title>
      <p>ST elevation acute myocardial infarction (STEMI) has a high morbidity and mortality rate.<sup><xref ref-type="bibr" rid="B1">1</xref></sup> Early diagnosis and immediate definition of a revascularization strategy reduce mortality.<sup><xref ref-type="bibr" rid="B1">1</xref> - <xref ref-type="bibr" rid="B3">3</xref></sup> Indicators of STEMI care are total delay (TD), patient delay (PD), and system delay (SD).<sup><xref ref-type="bibr" rid="B2">2</xref> , <xref ref-type="bibr" rid="B4">4</xref></sup> The TD is composed of the time between the onset of symptoms and the initial care (PD) and the time between the initial care and the introduction of the coronary angioplasty guidewire in the hemodynamics service (SD). The door-to-guidewire time (DGT) refers to the time interval from admission to the hospital where the hemodynamics service is located to the introduction of the coronary angioplasty guidewire into the culprit coronary artery, surpassing the acute occlusion; it is contained in the SD.</p>
      <p>The COVID-19 pandemic has affected the number of STEMI admissions and their care indicators.<sup><xref ref-type="bibr" rid="B5">5</xref></sup> In Hong Kong,<sup><xref ref-type="bibr" rid="B6">6</xref></sup> the United States,<sup><xref ref-type="bibr" rid="B7">7</xref> , <xref ref-type="bibr" rid="B8">8</xref></sup> Italy,<sup><xref ref-type="bibr" rid="B9">9</xref> , <xref ref-type="bibr" rid="B10">10</xref></sup> China,<sup><xref ref-type="bibr" rid="B11">11</xref></sup> Spain,<sup><xref ref-type="bibr" rid="B12">12</xref></sup> France,<sup><xref ref-type="bibr" rid="B13">13</xref></sup> and in a multicenter study in Europe,<sup><xref ref-type="bibr" rid="B14">14</xref></sup> there were few activations of hemodynamics emergency services for the management of STEMI during the COVID-19 pandemic.</p>
      <p>In England, during the COVID-19 pandemic, there was an increase in mortality due to cardiovascular diseases at homes, hospitals, and nursing homes compared to pre-pandemic periods.<sup><xref ref-type="bibr" rid="B15">15</xref></sup></p>
      <p>The pandemic also altered care indicators for STEMI in some countries, with an increase in SD (including DGT) and TD.<sup><xref ref-type="bibr" rid="B5">5</xref> , <xref ref-type="bibr" rid="B6">6</xref> , <xref ref-type="bibr" rid="B11">11</xref> , <xref ref-type="bibr" rid="B13">13</xref> , <xref ref-type="bibr" rid="B14">14</xref> , <xref ref-type="bibr" rid="B16">16</xref></sup> However, there is a lack of data in the literature regarding the Brazilian context.</p>
      <p>The objective of this study is to assess the impact of the COVID-19 pandemic on care indicators for STEMI (TD, PD, and SD) among patients admitted to the Santa Casa de Miseric&#243;rdia de Passos (SCMP) undergoing primary angioplasty within 12 hours of symptom onset.</p>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <p>A convenience sample was used, involving patients treated at the SCMP Hemodynamics Service for STEMI, who underwent primary angioplasty with a door-to-balloon time of up to 12 hours.</p>
      <p>SCMP is a 279-bed facility that provides care to patients under the Brazilian Unified Health System (SUS) and serves as the sole tertiary referral center for primary angioplasty for 27 municipalities in the Passos Regional Health Authority, located in the state of Minas Gerais, covering a population of 436,310 people.<sup><xref ref-type="bibr" rid="B17">17</xref></sup></p>
      <p>The reports from the SCMP Hemodynamics Service were reviewed using the term "primary angioplasty," which was present in all records of patients with STEMI referred to the service. The reports are stored in Microsoft Word<sup>&#174;</sup> files. Patient data were collected and classified in a Microsoft Excel<sup>&#174;</sup> spreadsheet, and the information was extracted from each patient's medical records. The patients were divided into two groups (pre-pandemic and pandemic) based on the date of March 11, 2020, which was chosen to correspond to the declaration of the pandemic by the World Health Organization.<sup><xref ref-type="bibr" rid="B18">18</xref></sup></p>
      <p>Patients admitted with STEMI to the SCMP Hemodynamics Service between January 1, 2018, and August 31, 2021, who underwent primary angioplasty within a maximum TD of 12 hours were included in the study. Patients who did not meet the criteria for STEMI after the medical record review, including retrospective analysis of the admission electrocardiograms (ECG), were excluded; patients who underwent primary angioplasty and were admitted with a TD of more than 12 hours were also excluded.</p>
      <p>Copies of the initial assessment forms and the timing of the initial ECG, when available, were used to determine the cutoff between PD and SD in the retrospective analysis of medical records. The primary outcomes of interest were the indicators of STEMI care: TD, SD, and PD. The secondary outcomes included in-hospital mortality from all causes and DGT.</p>
      <sec>
        <title>Statistical analysis</title>
        <p>A database was created in Microsoft Excel 2016<sup>&#174;</sup> for the implementation of double data entry validation. Subsequently, this database was imported into Minitab version 19<sup>&#174;</sup> for statistical analysis.<sup><xref ref-type="bibr" rid="B19">19</xref></sup> The continuous variables of the clinical-demographic profile and the primary and secondary outcomes were described using mean and standard deviation. Shapiro-Wilk normality test with p &lt; 0.05 was performed for all variables. Categorical variables were described using absolute and relative frequencies. Comparisons of categorical variables were performed using the chi-square test, and continuous variables between the groups of interest were compared using the unpaired Student's t-test. A significance level of &#945; = 0.05 was considered. The study was approved by the SCMP Research Ethics Committee under CAAE 45129621.5.0000.8043.</p>
      </sec>
    </sec>
    <sec sec-type="results">
      <title>Results</title>
      <p>A total of 336 patients were included between January 1, 2018, and August 31, 2021, with 192 (57%) in the pre-pandemic group and 144 (43%) in the pandemic group. There were no differences in the demographic and clinical profiles of the patients ( <xref ref-type="table" rid="t1">Table 1</xref> ). Evaluation of the PD and SD time intervals was only possible in 70 patients (45%) from the pre-pandemic group and 87 patients from the pandemic group (55%). Analysis of the demographic and clinical profiles was also conducted only for the patients in whom precise measurement of the intervals was possible, and no differences were observed ( <xref ref-type="table" rid="t2">Table 2</xref> ).</p>
      <p>
        <table-wrap id="t1">
          <label>Table 1</label>
          <caption>
            <title>&#8211; Comparison of demographic and clinical profile in patients admitted for STEMI at Santa Casa de Miseric&#243;rdia de Passos, pre-pandemic and during the pandemic.</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead>
              <tr>
                <th align="left" style="font-weight:normal"> </th>
                <th>Pre-pandemic (192; 57%)</th>
                <th>Pandemic (144; 43%)</th>
                <th>P value</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td>Mean age (age &#177; SD)</td>
                <td align="center">61.7&#177;11.4</td>
                <td align="center">63.3&#177;11.6</td>
                <td align="center">0.2</td>
              </tr>
              <tr>
                <td>Male sex (%)</td>
                <td align="center">127 (66%)</td>
                <td align="center">98 (68%)</td>
                <td align="center">0.71</td>
              </tr>
              <tr>
                <td>SAH (%)</td>
                <td align="center">107 (59%)</td>
                <td align="center">87 (67%)</td>
                <td align="center">0.14</td>
              </tr>
              <tr>
                <td>DM (%)</td>
                <td align="center">45 (25%)</td>
                <td align="center">42 (32%)</td>
                <td align="center">0.15</td>
              </tr>
              <tr>
                <td>Smoking (%)</td>
                <td align="center">74 (42%)</td>
                <td align="center">49 (38%)</td>
                <td align="center">0.47</td>
              </tr>
              <tr>
                <td>Previous AMI (%)</td>
                <td align="center">12 (6%)</td>
                <td align="center">15 (11%)</td>
                <td align="center">0.14</td>
              </tr>
              <tr>
                <td>Patients from neighboring cities (%)</td>
                <td align="center">109 (58%)</td>
                <td align="center">80 (58%)</td>
                <td align="center">0.94</td>
              </tr>
              <tr>
                <td>Killip &gt; 1 (%)</td>
                <td align="center">53 (28%)</td>
                <td align="center">31 (23%)</td>
                <td align="center">0.29</td>
              </tr>
              <tr>
                <td>Ejection fraction* (mean &#177; SD)</td>
                <td align="center">51.4%&#177;12%</td>
                <td align="center">49.6%&#177;12%</td>
                <td align="center">0.31</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN1">
              <p>AMI: acute myocardial infarction; DM: diabetes mellitus; SAH: systemic arterial hypertension; SD: standard deviation. *Simpson&#8217;s Method.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
      </p>
      <p>
        <table-wrap id="t2">
          <label>Table 2</label>
          <caption>
            <title>&#8211; Demographic and clinical profile for patients with available PD and SD data.</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead>
              <tr>
                <th align="left" style="font-weight:normal"> </th>
                <th>Pre-pandemic n = 70 (45%)</th>
                <th>Pandemic n = 87 (55%)</th>
                <th>P value</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td>Mean age (age &#177; SD)</td>
                <td align="center">n = 70 59.6 (&#177;10.8)</td>
                <td align="center">n = 87 62.9 (&#177;11.4)</td>
                <td align="center">0.06</td>
              </tr>
              <tr>
                <td>Male sex (%)</td>
                <td align="center">n = 70 51 (72%)</td>
                <td align="center">n = 87 62 (71%)</td>
                <td align="center">0.82</td>
              </tr>
              <tr>
                <td>SAH (%)</td>
                <td align="center">n = 70 42 (60%)</td>
                <td align="center">n = 85 56 (66%)</td>
                <td align="center">0.45</td>
              </tr>
              <tr>
                <td>DM (%)</td>
                <td align="center">n = 68 17 (25%)</td>
                <td align="center">n = 85 25 (29%)</td>
                <td align="center">0.54</td>
              </tr>
              <tr>
                <td>Smoking (%)</td>
                <td align="center">n = 67 24 (36%)</td>
                <td align="center">n = 85 38 (45%)</td>
                <td align="center">0.27</td>
              </tr>
              <tr>
                <td>Previous AMI (%)</td>
                <td align="center">n = 69 5 (7%)</td>
                <td align="center">n = 85 10 (12%)</td>
                <td align="center">0.35</td>
              </tr>
              <tr>
                <td>Patients from neighboring cities (%)</td>
                <td align="center">n = 70 32 (46%)</td>
                <td align="center">n = 87 44 (51%)</td>
                <td align="center">0.68</td>
              </tr>
              <tr>
                <td>Killip &gt; 1 (%)</td>
                <td align="center">n = 68 22 (29%)</td>
                <td align="center">n = 79 18 (23%)</td>
                <td align="center">0.35</td>
              </tr>
              <tr>
                <td>Ejection fraction* (mean &#177; SD)</td>
                <td align="center">n = 48 52% &#177; 12%</td>
                <td align="center">n = 48 50% &#177; 12%</td>
                <td align="center">0.48</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN2">
              <p>AMI: acute myocardial infarction; DM: diabetes mellitus; SAH: systemic arterial hypertension; SD: standard deviation. *Simpson&#8217;s Method.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
      </p>
      <p>The distribution of PD, SD, and TD is presented in <xref ref-type="fig" rid="f01">Figure 1</xref> , and the means in minutes, standard deviations, and confidence intervals are shown in <xref ref-type="table" rid="t3">Table 3</xref> . The pandemic increased the average SD by 35 minutes (p = 0.037). The DGT in minutes, which is part of the SD, did not show a statistically significant change. PD and TD also did not exhibit a statistically significant impact between the two groups. The number of deaths did not differ significantly.</p>
      <p>
        <fig id="f01">
          <label>Figure 1</label>
          <caption>
            <title>&#8211; Mean and standard deviation of PD (A), SD (B), and TD (C), in minutes, according to pre-pandemic and pandemic periods, with p value based on Student&#8217;s t test.</title>
            <p>TD: total delay; PD: patient delay; SD: system delay.</p>
          </caption>
          <graphic xlink:href="2359-5647-ijcs-36-e20220009-20009-gf01.tif"/></fig>
      </p>
      <p>
        <table-wrap id="t3">
          <label>Table 3</label>
          <caption>
            <title>&#8211; Primary and secondary outcomes for the total sample according to the "pre-pandemic" and "pandemic" groups</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead>
              <tr>
                <th align="left" style="font-weight:normal"> </th>
                <th>Pre-pandemic</th>
                <th>Pandemic</th>
                <th>P value</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td rowspan="2">Death (%)</td>
                <td align="center">n = 187</td>
                <td align="center">n = 133</td>
                <td align="center" rowspan="2">0.49</td>
              </tr>
              <tr>
                <td align="center">18 (9.7%)</td>
                <td align="center">16 (12%)</td>
              </tr>
              <tr>
                <td rowspan="2">DGT in minutes (mean &#177; SD)</td>
                <td align="center">n = 184</td>
                <td align="center">n = 132</td>
                <td align="center" rowspan="2">0.53</td>
              </tr>
              <tr>
                <td align="center">67.7&#177;31.2</td>
                <td align="center">70&#177;32.5</td>
              </tr>
              <tr>
                <td rowspan="2">PD in minutes (mean &#177; SD)</td>
                <td align="center">n = 70</td>
                <td align="center">n = 87</td>
                <td align="center" rowspan="2">0.44</td>
              </tr>
              <tr>
                <td align="center">145&#177;133</td>
                <td align="center">130&#177;117</td>
              </tr>
              <tr>
                <td rowspan="2">System delay in minutes (mean &#177; SD)</td>
                <td align="center">n = 72</td>
                <td align="center">n = 89</td>
                <td align="center" rowspan="2">0.037</td>
              </tr>
              <tr>
                <td align="center">145&#177;97</td>
                <td align="center">178&#177;96</td>
              </tr>
              <tr>
                <td rowspan="2">TD in minutes (mean &#177; SD)</td>
                <td align="center">n = 178</td>
                <td align="center">n = 135</td>
                <td align="center" rowspan="2">0.97</td>
              </tr>
              <tr>
                <td align="center">300&#177;159</td>
                <td align="center">300&#177;148</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN3">
              <p>SD: standard deviation; TD: total delay; PD: patient delay; DGT: door-to-guidewire time.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
      </p>
      <p>Data from <xref ref-type="table" rid="t4">Tables 4</xref> and <xref ref-type="table" rid="t5">5</xref> demonstrate the results of primary and secondary outcomes for patients from Passos and the neighboring municipalities. Among patients from Passos, there was a statistically significant reduction in PD in minutes during the pandemic, which was not observed among patients from neighboring municipalities. There were no statistically significant differences in SD during the pandemic between patients from Passos or the neighboring municipalities. The TD for patients from Passos and the neighboring municipalities also did not differ significantly during the pandemic.</p>
      <p>
        <table-wrap id="t4">
          <label>Table 4</label>
          <caption>
            <title>&#8211; Primary outcomes of patients from Passos, Minas Gerais, Brazil</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead>
              <tr>
                <th align="left" style="font-weight:normal"> </th>
                <th colspan="3">Patients from Passos</th>
              </tr>
              <tr>
                <th align="left" colspan="4" style="font-weight:normal">
                  <hr/>
                </th>
              </tr>
              <tr>
                <th align="left" style="font-weight:normal"> </th>
                <th>Pre-pandemic</th>
                <th>Pandemic</th>
                <th>P value</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td rowspan="2">PD in minutes (mean &#177; SD)</td>
                <td align="center">n = 38</td>
                <td align="center">n = 43</td>
                <td align="center" rowspan="2">0.044</td>
              </tr>
              <tr>
                <td align="center">143.2&#177;134</td>
                <td align="center">92.5&#177;74.2</td>
              </tr>
              <tr>
                <td rowspan="2">System delay in minutes (mean &#177; SD)</td>
                <td align="center">n = 38</td>
                <td align="center">n = 44</td>
                <td align="center" rowspan="2">0.049</td>
              </tr>
              <tr>
                <td align="center">95.4&#177;88.3</td>
                <td align="center">134.6&#177;88.8</td>
              </tr>
              <tr>
                <td rowspan="2">TD in minutes (mean &#177; SD)</td>
                <td align="center">n = 76</td>
                <td align="center">n = 57</td>
                <td align="center" rowspan="2">0.34</td>
              </tr>
              <tr>
                <td align="center">256&#177;162</td>
                <td align="center">232&#177;125</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN4">
              <p>SD: standard deviation; TD: total delay; PD: patient delay.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
      </p>
      <p>
        <table-wrap id="t5">
          <label>Table 5</label>
          <caption>
            <title>&#8211; Primary outcomes of patients from neighboring municipalities</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead>
              <tr>
                <th align="left" style="font-weight:normal"> </th>
                <th colspan="3">Patients from neighboring municipalities</th>
              </tr>
              <tr>
                <th align="left" colspan="4" style="font-weight:normal">
                  <hr/>
                </th>
              </tr>
              <tr>
                <th align="left" style="font-weight:normal"> </th>
                <th>Pre-pandemic</th>
                <th>Pandemic</th>
                <th>P value</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td rowspan="2">PD in minutes (mean &#177; SD)</td>
                <td align="center">n = 32</td>
                <td align="center">n = 44</td>
                <td align="center" rowspan="2">0.56</td>
              </tr>
              <tr>
                <td align="center">147&#177;133</td>
                <td align="center">166&#177;139</td>
              </tr>
              <tr>
                <td rowspan="2">System delay in minutes (mean &#177; SD)</td>
                <td align="center">n = 34</td>
                <td align="center">n = 45</td>
                <td align="center" rowspan="2">0.3</td>
              </tr>
              <tr>
                <td align="center">201&#177;74.7</td>
                <td align="center">219.8&#177;85.1</td>
              </tr>
              <tr>
                <td rowspan="2">TD in minutes (mean &#177; SD)</td>
                <td align="center">n = 100</td>
                <td align="center">n = 78</td>
                <td align="center" rowspan="2">0.44</td>
              </tr>
              <tr>
                <td align="center">334&#177;151</td>
                <td align="center">351&#177;143</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN5">
              <p>SD: standard deviation; TD: total delay; PD: patient delay.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
      </p>
    </sec>
    <sec sec-type="discussion">
      <title>Discussion</title>
      <p>In this study, we observed that the pandemic has affected the local healthcare system's response to STEMI. The SD significantly increased, without a change in DGT, indicating that the time between initial assessment and transfer to SCMP was prolonged. This effect may be due to system overload and modified triage and treatment protocols implemented during the pandemic. Patients arrive at SCMP from other hospitals in neighboring cities, as well as from the Emergency Care Unit (UPA, acronym in Portuguese) that provides emergency care for patients covered by the SUS, who do not have direct access to SCMP and either come on their own or are transported by emergency medical services (SAMU, acronym in Portuguese).</p>
      <p>No differences were observed in DGT, indicating that the care provided by the healthcare team at SCMP was not significantly impacted by the pandemic.</p>
      <p>Demographic and clinical data did not differ between the pre-pandemic and pandemic groups, indicating that there was no influence on the analyzed outcomes. De Luca et al.<sup><xref ref-type="bibr" rid="B14">14</xref></sup> revealed a proportional reduction in patients with hypertension among cases of STEMI during the pandemic, and Rang&#233; et al.<sup><xref ref-type="bibr" rid="B13">13</xref></sup> found a higher incidence of cardiogenic shock during the pandemic as differences in demographic and clinical data, which were not observed in our study.</p>
      <p>Scholz et al.<sup><xref ref-type="bibr" rid="B20">20</xref></sup> demonstrated, in a prospective multicenter study including 15,800 patients from 2017 to 2020 in Germany, that there were no differences in the number of admissions for myocardial infarction during the pandemic compared to the pre-pandemic period. They also found no significant differences in TD, SD, PD, and in-hospital mortality from STEMI.</p>
      <p>On the other hand, De Luca et al.<sup><xref ref-type="bibr" rid="B14">14</xref></sup> conducted a multicenter European study involving 6,609 patients and found that the pandemic resulted in a reduction in admissions for STEMI and increased the DGT, TD, and in-hospital mortality among these patients. The mortality was significantly higher among patients infected with COVID-19, but it was also higher among non-infected patients (with statistical significance in both groups).</p>
      <p>Rang&#233; et al.,<sup><xref ref-type="bibr" rid="B13">13</xref></sup> in a multicenter study involving 2,064 patients in France, observed a non-significant trend towards increased PD, SD, and TD during the pandemic, as well as an increase in composite in-hospital outcomes including death, stent thrombosis, myocardial infarction, unplanned coronary revascularization, stroke, and major bleeding.</p>
      <p>Xiang et al.<sup><xref ref-type="bibr" rid="B11">11</xref></sup> evaluated 25,150 patients and demonstrated that the PD was not affected by the pandemic, but the SD and in-hospital mortality for STEMI increased during the COVID-19 outbreak. There was no distinction between patients infected with SARS-CoV-2, and more patients received thrombolytic therapy instead of primary angioplasty during the epidemic months, which was statistically significant.</p>
      <p>Daoulah et al.<sup><xref ref-type="bibr" rid="B16">16</xref></sup> showed that in April 2020, during the pandemic, there was a statistically significant increase in patients with DGT &gt; 90 minutes compared to DGT &lt; 90 minutes in Saudi Arabia, compared to the same months in 2018 and 2019, revealing the impact of the pandemic on this indicator. They also found an increase in TD during the pandemic, but without statistically significant differences in mortality.</p>
      <p>In Hong Kong, there was also a significant increase in DGT.<sup><xref ref-type="bibr" rid="B6">6</xref></sup> McLaren et al.<sup><xref ref-type="bibr" rid="B21">21</xref></sup> demonstrated an increase in the time between patient arrival and ECG, as well as between ECG and contact with the catheterization team in Canada; these variables were not recorded in our study.</p>
      <p>Differences in the impact of the pandemic may exist, depending on the organization of the healthcare system or the countries&#8217; level of development. The PD was reduced with statistical significance only among patients from Passos, but not among those from neighboring municipalities. This may reflect a different behavior, with greater perception of disease severity and less delay in seeking medical care influenced by the pandemic. The fear of contracting COVID-19 did not increase the PD. It may also reflect the population's confidence in the local emergency care. However, the same effect was not observed in neighboring municipalities, possibly due to a lesser impact of COVID-19 in those areas or a higher number of patients residing in rural areas, farther from initial medical care.</p>
      <p>Rang&#233; et al.<sup><xref ref-type="bibr" rid="B13">13</xref></sup> found a statistically significant increase in PD among patients who sought emergency services for STEMI during the pandemic, but there was no statistically significant increase in PD when considering the overall sample.</p>
      <p>There were no differences in in-hospital mortality; however, the delay in SD can be used as a substitute outcome for in-hospital and post-discharge mortality for STEMI. This impact may have occurred in other regions of the country as well.</p>
      <p>Several reasons have been suggested to justify the variation in the number of STEMI cases admitted to hospitals and the worsening of STEMI care indicators during the pandemic,<sup><xref ref-type="bibr" rid="B22">22</xref> , <xref ref-type="bibr" rid="B23">23</xref></sup> including the following: the incidence of STEMI may have decreased due to reduced pollution, decreased access to tobacco and processed food in cities with restrictions, and changes in people's routines; viral infection symptoms overlapping with myocardial infarction symptoms, making diagnosis challenging; patients' fear of attending hospitals and contracting SARS-CoV-2; restricted access to healthcare services due to system overload; temporary suspension of outpatient consultations; temporary suspension of elective cardiac catheterizations and coronary angioplasties, as well as elective non-invasive tests; the influence of the pandemic on the clinical diagnostic method in the emergency department to exclude COVID-19 diagnosis and prevent healthcare workers' infections.<sup><xref ref-type="bibr" rid="B22">22</xref> , <xref ref-type="bibr" rid="B23">23</xref></sup></p>
      <p>Limitations of this study include a small sample size, retrospective analysis, unavailable data for some patients in the sample, and the absence of data on COVID-19 infections among the sample patients. Due to the small sample size, it was not possible to compare outcomes between the two periods with higher numbers of COVID-19 cases (waves) in Passos.</p>
    </sec>
    <sec sec-type="conclusions">
      <title>Conclusion</title>
      <p>The pandemic has impacted the indicators of STEMI care, increasing the SD in the Passos region. The PD decreased during the pandemic among patients from the main city, Passos, but not among patients from neighboring municipalities. There was no difference in the TD, DGT, and in-hospital mortality in this study involving patients from the Passos region who were referred for primary angioplasty in the main city.</p>
    </sec>
  </body>
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    <fn-group>
      <fn fn-type="supported-by">
        <p>Sources of Funding: There were no external funding sources for this study.</p>
      </fn>
    </fn-group>
  </back>
</article>
