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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">abcimg</journal-id>
<journal-title-group>
<journal-title>ABC Imagem Cardiovascular</journal-title>
<abbrev-journal-title abbrev-type="publisher">Arq Bras Cardiol: Imagem cardiovasc.</abbrev-journal-title></journal-title-group>
<issn pub-type="epub">2675-312X</issn>
<publisher>
<publisher-name>Sociedade Brasileira de Cardiologia</publisher-name></publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.36660/abcimg.20240067i</article-id>
<article-id pub-id-type="publisher-id">abcimg.20240067i</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Original Article</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>The Prognostic Impact of Myocardial Deformation Measures in Patients with COVID-19</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">0000-0002-8678-5501</contrib-id>
<name><surname>Silveira</surname><given-names>João Giffoni</given-names><suffix>Neto</suffix></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="corresp" rid="c1"/>
<role>Conception and design of the research</role>
<role>acquisition of data</role>
<role>analysis and interpretation of the data</role>
<role>statistical analysis</role>
<role>critical revision of the manuscript for intellectual content</role>
<role>writing of the manuscript</role>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">0000-0002-2499-4295</contrib-id>
<name><surname>Campos</surname><given-names>Marcello de Brito</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<role>acquisition of data</role>
<role>analysis and interpretation of the data</role>
<role>writing of the manuscript</role>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">0009-0006-2935-3266</contrib-id>
<name><surname>Mello</surname><given-names>Luiz</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<role>acquisition of data</role>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">0009-0005-4694-8838</contrib-id>
<name><surname>Giffoni</surname><given-names>Marcela de Castro</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<role>Conception and design of the research</role>
<role>acquisition of data</role>
<role>writing of the manuscript</role>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">0009-0001-1541-5204</contrib-id>
<name><surname>Goveia</surname><given-names>Natanael Arnor da Silva Barros</given-names></name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<role>acquisition of data</role>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">0000-0002-3830-2886</contrib-id>
<name><surname>Nóbrega</surname><given-names>Antonio Claudio Lucas da</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<role>Conception and design of the research</role>
<role>analysis and interpretation of the data</role>
<role>statistical analysis</role>
<role>critical revision of the manuscript for intellectual content</role>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">0000-0001-5560-693X</contrib-id>
<name><surname>Castro</surname><given-names>Renata R. T.</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<role>Conception and design of the research</role>
<role>analysis and interpretation of the data</role>
<role>statistical analysis</role>
<role>critical revision of the manuscript for intellectual content</role>
<role>writing of the manuscript</role>
</contrib>
<aff id="aff1">
<label>1</label>
<institution content-type="orgname">Universidade Federal Fluminense</institution>
<addr-line>
<named-content content-type="city">Niterói</named-content>
<named-content content-type="state">RJ</named-content>
</addr-line>
<country country="BR">Brazil</country>
<institution content-type="original">Universidade Federal Fluminense, Niterói, RJ – Brazil</institution>
</aff>
<aff id="aff2">
<label>2</label>
<institution content-type="orgname">Universidade Iguaçu</institution>
<addr-line>
<named-content content-type="city">Nova Iguacu</named-content>
<named-content content-type="state">RJ</named-content>
</addr-line>
<country country="BR">Brazil</country>
<institution content-type="original">Universidade Iguaçu, Nova Iguacu, RJ – Brazil</institution>
</aff>
<aff id="aff3">
<label>3</label>
<institution content-type="orgname">PUC-Rio</institution>
<addr-line>
<named-content content-type="city">Rio de Janeiro</named-content>
<named-content content-type="state">RJ</named-content>
</addr-line>
<country country="BR">Brazil</country>
<institution content-type="original">PUC-Rio, Rio de Janeiro, RJ – Brazil</institution>
</aff>
<aff id="aff4">
<label>4</label>
<institution content-type="orgname">Universidade Federal do Estado do Rio de Janeiro</institution>
<addr-line>
<named-content content-type="city">Rio de Janeiro</named-content>
<named-content content-type="state">RJ</named-content>
</addr-line>
<country country="BR">Brazil</country>
<institution content-type="original">Universidade Federal do Estado do Rio de Janeiro, Rio de Janeiro, RJ – Brazil</institution>
</aff>
</contrib-group>
<author-notes>
<corresp id="c1"><label>Correspondência: João Giffoni Silveira Neto •</label> Universidade Iguaçu. Av. Abílio Augusto Távora, 2134. CEP: <postal-code>26275-580</postal-code>. Jardim Alvorada, Nova Iguaçu, RJ – Brasil E-mail: <email>joao.giffoni2@hotmail.com</email></corresp>
<fn fn-type="conflict"><label>Potential Conflict of Interest</label><p>No potential conflict of interest relevant to this article was reported.</p></fn>
<fn fn-type="edited-by"><label>Editor responsável pela revisão:</label><p>Marcelo Tavares</p></fn>
</author-notes>
<pub-date publication-format="electronic" date-type="pub">
<day>13</day>
<month>12</month>
<year>2024</year></pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2024</year></pub-date>
<volume>37</volume>
<issue>4</issue>
<elocation-id>e20240067</elocation-id>
<history>
<date date-type="received"><day>11</day><month>07</month><year>2024</year></date>
<date date-type="rev-recd"><day>24</day><month>10</month><year>2024</year></date>
<date date-type="accepted"><day>29</day><month>10</month><year>2024</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</license-p>
</license>
</permissions>
<abstract>
<title>Abstract</title>
<sec>
<title>Background:</title>
<p>Cardiovascular involvement in COVID-19 has been extensively studied. Echocardiography is an important technique in identifying cardiac involvement, serving as an excellent tool for prognostic variables.</p>
</sec>
<sec>
<title>Objectives:</title>
<p>Analyze the prognostic impact of speckle tracking in analyzing the left ventricle in patients with COVID-19 admitted to intensive care units (ICUs).</p>
</sec>
<sec>
<title>Methods:</title>
<p>Patients diagnosed with COVID-19 admitted to the ICU underwent an echocardiographic examination within the first 48 hours of hospitalization and were divided into two groups according to hospital outcome (discharge or death). Conventional echocardiographic data, as well as global longitudinal strain of the left ventricle (LVGLS) and right ventricle (RVGLS) of both groups, were compared using Student&apos;s t test (for continuous variables) or the chi-square test (for categorical variables), considering p &lt; 0.05 as statistically significant.</p>
</sec>
<sec>
<title>Results:</title>
<p>The average age was 56 ± 14 years, and the proportion of men and women was similar. The mortality rate was 64%, more frequent in elderly patients and in patients with a higher number of comorbidities. LVGLS revealed lower values in patients who progressed to death, with a cutoff point below −18.1% (sensitivity = 90.4%, specificity = 96.6%) for this outcome, and, after multivariate statistical analysis, it was found to be the only statistically significant echocardiographic variable.</p>
</sec>
<sec>
<title>Conclusion:</title>
<p>LVGLS is an important tool in the prognostic analysis of critically patients with COVID-19, offering a new window of possibilities for evaluating these patients.</p>
</sec>
</abstract>
<kwd-group xml:lang="en">
<title>Keywords:</title>
<kwd>COVID-19</kwd>
<kwd>Echocardiography</kwd>
<kwd>Global Longitudinal Strain</kwd>
</kwd-group>
<counts>
<fig-count count="10"/>
<table-count count="10"/>
<equation-count count="0"/>
<ref-count count="27"/>
</counts>
</article-meta>
</front>
<body>
<sec sec-type="intro">
<title>Introduction</title>
<p>The evolving understanding of COVID-19, initially identified as an acute respiratory syndrome, has been expanded by studies revealing significant cardiovascular implications.<sup><xref ref-type="bibr" rid="B1">1</xref>-<xref ref-type="bibr" rid="B4">4</xref></sup> This raised pertinent questions about whether the presence of preexisting cardiovascular conditions is a risk factor for the severity and mortality of COVID-19, suggesting a vulnerability profile in affected patients,<sup><xref ref-type="bibr" rid="B5">5</xref>-<xref ref-type="bibr" rid="B10">10</xref></sup> or whether SARS-CoV-2 infection could induce cardiovascular complications even in individuals without a history of cardiac diseases.</p>
<p>In this context, two-dimensional echocardiography is particularly useful in the management of patients with COVID-19, especially given the prevalence of myocardial involvement in these infections. It provides valuable insights for defining cardiac involvement and patient management.<sup><xref ref-type="bibr" rid="B11">11</xref>-<xref ref-type="bibr" rid="B13">13</xref></sup> The use of myocardial strain techniques enhances these assessments through myocardial deformation analysis, a more sensitive approach than traditional volumetric assessments and ejection fractions, demonstrating high inter- and intraobserver reliability.<sup><xref ref-type="bibr" rid="B14">14</xref>-<xref ref-type="bibr" rid="B16">16</xref></sup></p>
<p>We understand that the presence of early alterations in myocardial function, particularly related to subclinical systolic dysfunction of the left ventricle (LV), may be associated with poorer outcomes in patients affected by COVID-19. Consequently, the use of myocardial strain echocardiography (Central Illustration) becomes crucial in the initial assessment of these patients. Thus, the primary objective of this study is to investigate the prognostic impact of utilizing the speckle tracking technique in myocardial strain analysis for the evaluation of patients with COVID-19 infection. This includes describing LV function in patients admitted to intensive care units (ICUs) with COVID-19 and assessing the independent prognostic power of the speckle tracking technique in analyzing their LV function.</p>
<fig id="f1">
<graphic xlink:href="2675-312X-abcimg-37-04-e20240067-gf01.tif"/>
</fig>
</sec>
<sec sec-type="methods">
<title>Methods</title>
<sec>
<title>Study design and population</title>
<p>This is a longitudinal, observational, and prospective study. For its execution, all patients admitted for COVID-19 infection to the ICUs of the Hospital Geral de Nova Iguaçu (HGNI) were recruited during the period from March 28 to December 30, 2020. The criteria for admission to these units included signs of severity and the need for mechanical ventilation.</p>
<p>The diagnosis of COVID-19 was confirmed with a positive result of real-time reverse transcriptase–polymerase chain reaction (RT-PCR) assay of pharyngeal swabs. All participants in the study underwent echocardiographic analysis within 48 hours of admission. Additionally, computed tomography (CT) scans of the lungs were performed.</p>
<p>Demographic data such as age, sex, ethnicity, weight, height, and known comorbidities were collected and cataloged alongside a questionnaire, which is provided in the annex. This included echocardiographic data and CT findings. The presence of comorbidities, such as hypertension or diabetes mellitus (DM), was reported by the patient themselves or, in cases where the patient was unable to respond (due to being sedated and intubated), the information was obtained from medical records or provided by a family member.</p>
<p>Patients were monitored throughout their hospital stay regarding the final in-hospital outcome (discharge, death, or transfer). This study did not interfere with the medical management during hospitalization and took into account that all care provided was in accordance with current best practices.</p>
</sec>
<sec>
<title>Criteria for ICU admission of patients</title>
<p>Patients admitted to the ICU with a diagnosis of COVID-19 were evaluated, based on RT-PCR tests conducted using respiratory secretion samples collected with a nasopharyngeal swab upon patient admission to the hospital, presenting signs or symptoms of SARS-CoV-2 infection. The tests utilized kits produced by Seegene Laboratory from the Republic of Korea, provided by the Brazilian Ministry of Health during that period. The assessment of signs or symptoms followed the guidelines of the Brazilian Ministry of Health&apos;s Clinical Management Protocol for COVID-19 in Specialized Care, as per the electronic version of the revised 1st edition of 2020.</p>
</sec>
<sec>
<title>Patients were considered severe if they demonstrated any of the following characteristics:<sup><xref ref-type="bibr" rid="B17">17</xref></sup></title>
<list list-type="alpha-lower">
<list-item><p>Respiratory failure: significant breathing difficulty, characterized by dyspnea, hypoxemia (low blood oxygen level), or a high respiratory rate (tachypnea), and the need for supplemental oxygen support or mechanical ventilation;</p></list-item>
<list-item><p>Hemodynamic alterations: hypotension unresponsive to fluid resuscitation, presence of shock, whether septic, cardiogenic, or other types;</p></list-item>
<list-item><p>Consciousness alterations: confusion, disorientation, or reduced level of consciousness, which may indicate central nervous system involvement or metabolic encephalopathy;</p></list-item>
<list-item><p>Coagulopathies: evidence of disseminated intravascular coagulation or venous thromboembolism;</p></list-item>
<list-item><p>Chest imaging: progressive multilobar infiltrates in chest radiographs or CT with extensive pulmonary involvement.</p></list-item>
</list>
</sec>
<sec>
<title>Inclusion and Exclusion Criteria for Patients</title>
<p>The study included patients admitted to the HGNI during the study period (<xref ref-type="table" rid="t1">Table 1</xref>), of both sexes, aged 18 years and above, with a confirmed diagnosis of COVID-19 infection. Patients were excluded from the study if they died or were discharged from the hospital before the echocardiogram could be performed. Additionally, patients who were transferred to another hospital at any point during the study were also excluded, as such transfers made it impossible to follow up on patient outcomes. Patients who did not have echocardiographic images suitable for speckle tracking analysis were also excluded. There were no exclusions based on inconclusive results from the RT-PCR tests. All study patients underwent CT of the lungs.</p>
<table-wrap id="t1">
<label>Table 1</label>
<caption><title>Inclusion and exclusion criteria for patients in the study</title></caption>
<table frame="hsides" rules="groups">
<colgroup width="50%">
<col/>
<col/>
</colgroup>
<thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
<tr style="background-color:#C58874">
<th align="left" valign="middle">Patients included in the study</th>
<th align="center" valign="middle">Patients excluded from the study</th>
</tr>
</thead>
<tbody style="border-bottom: thin solid; border-color: #000000">
<tr>
<td align="left" valign="middle">Admitted to the ICU of HGNI with a diagnosis of COVID-19</td>
<td align="center" valign="middle">Died before undergoing echocardiography</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">Diagnosed with COVID-19 via RT-PCR</td>
<td align="center" valign="middle">Transferred to another healthcare facility, precluding outcome follow-up</td>
</tr>
<tr>
<td align="left" valign="middle">Underwent CT of the lungs</td>
<td align="center" valign="middle">Inconclusive COVID-19 diagnosis</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">Echocardiographic examination conducted within 48 hours of ICU admission</td>
<td align="center" valign="middle">Echocardiographic images unsuitable for speckle tracking strain analysis</td>
</tr>
<tr>
<td align="left" valign="middle">Aged 18 years and older</td>
<td align="center" valign="middle">Under 18 years old</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="TFN1"><p>HGNI: Hospital Geral de Nova Iguaçu; ICU: intensive care unit; RT-PCR: reverse transcriptase–polymerase chain reaction; CT: computed tomography.</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec>
<title>Echocardiographic analysis</title>
<p>The echocardiographic evaluation of study participants was conducted within the first 48 hours following hospital admission. Images were collected using GE Healthcare Vivid IQ echocardiography equipment, employing a 3Sc-RS adult sector transducer from GE. The acquisition and analysis of echocardiographic data were performed by a single examiner with extensive experience. Image acquisition was conducted following the guidelines of the American Society of Echocardiography (ASE) and the European Association of Cardiovascular Imaging (EACVI).<sup><xref ref-type="bibr" rid="B11">11</xref></sup> All data were analyzed before the patient outcomes were known.</p>
<p>In the two-dimensional echocardiographic analysis, data were obtained on the diameters of the right and left heart, including left ventricle end-diastolic diameter (LVEDD), left ventricle end-systolic diameter (LVESD), a longitudinal cut of the long axis, as well as posterior wall in diastole (PWd), interventricular septum in diastole (IVSd), values used to obtain left ventricular mass (LVM) and relative wall thickness (RWT), calculated using the equation 2 × PWd/LVEDD. Additionally, the diameter of the right ventricle base was obtained by the apical 4-chamber (4C) view, with an emphasis on the right chambers.</p>
<p>In assessing LV diastolic function, via pulsed-wave Doppler of the transmitral flow in the apical 4C view, E-wave and A-wave velocities were obtained, along with the E/A ratio. The assessment of pulmonary artery systolic pressure (PASP), evaluated by the maximum velocity of tricuspid regurgitation via continuous-wave Doppler of tricuspid regurgitation flow, defines the maximum velocity of this flow squared, multiplied by 4, and is augmented by values based on the variation in diameter of the inferior vena cava, assessed in the subxiphoid view.</p>
<p>Analyses of left ventricular global longitudinal myocardial deformation (LVGLS) were performed using images acquired from the apical long-axis in four, two, and three chambers. These images were transferred to an offline analysis platform (EchoPAC Software Only v 202), where they were processed for study. Peak systolic strain was defined as the point of maximum systolic shortening for longitudinal deformation. Aortic valve closure was used as a reference point to define the end of systole with speckle tracking.</p>
<p>Left ventricular ejection fraction (LVEF) analysis was conducted using the biplane Simpson&apos;s technique, through 4C and 2C views, and the analysis of LVGLS, applying as cutoff points abnormal values for LVEF (&lt; 52% for men and &lt; 54% for women) and LVGLS &lt; 18% for both sexes. Right ventricular function was analyzed by tricuspid annular plane systolic excursion (TAPSE), via the apical 4C view with an emphasis on the right chambers, with abnormal cutoff values being &lt; 17 mm. Furthermore, global longitudinal strain of the right ventricle (RVGLS) was also analyzed offline using EchoPAC Software Only v 202, with abnormal cutoff values of &lt; 20%.</p>
<p>Normal values for echocardiographic variables in relation to sex and also biventricular myocardial strain can be observed in <xref ref-type="table" rid="t2">Table 2</xref> and followed the guidance of the Recommendations for Chamber Quantification by Echocardiography in Adults by the ASE and the EACVI<sup><xref ref-type="bibr" rid="B11">11</xref></sup> and the Position Statement on the Use of Myocardial Strain in Cardiology Routines by the Brazilian Society of Cardiology&apos;s Department Of Cardiovascular Imaging.<sup><xref ref-type="bibr" rid="B16">16</xref></sup></p>
<table-wrap id="t2">
<label>Table 2</label>
<caption><title>Reference values for normality of echocardiographic variables and biventricular longitudinal strain values</title></caption>
<table frame="hsides" rules="groups">
<colgroup width="33%">
<col/>
<col/>
<col/>
</colgroup>
<thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
<tr style="background-color:#C58874">
<th align="left" valign="middle">Echocardiographic parameter</th>
<th align="center" valign="middle">Reference value – male</th>
<th align="center" valign="middle">Reference value – female</th>
</tr>
</thead>
<tbody style="border-bottom: thin solid; border-color: #000000">
<tr>
<td align="left" valign="middle">IVSd, mm</td>
<td align="center" valign="middle">Up to 11</td>
<td align="center" valign="middle">Up to 11</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">LVEDD, mm</td>
<td align="center" valign="middle">42 to 58.4</td>
<td align="center" valign="middle">37.8 to 52.2</td>
</tr>
<tr>
<td align="left" valign="middle">LVESD, mm</td>
<td align="center" valign="middle">25 to 39.8</td>
<td align="center" valign="middle">21.6 to 34.8</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">PWd, mm</td>
<td align="center" valign="middle">Up to 11</td>
<td align="center" valign="middle">Up to 11</td>
</tr>
<tr>
<td align="left" valign="middle">LVEF, %</td>
<td align="center" valign="middle">52% to 72%</td>
<td align="center" valign="middle">54% to 74%</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">LVM, g</td>
<td align="center" valign="middle">88 to 224</td>
<td align="center" valign="middle">67 to 162</td>
</tr>
<tr>
<td align="left" valign="middle">RVBD, mm</td>
<td align="center" valign="middle">25 to 41</td>
<td align="center" valign="middle">25 to 41</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">TAPSE, mm</td>
<td align="center" valign="middle">≥ 17</td>
<td align="center" valign="middle">≥17</td>
</tr>
<tr>
<td align="left" valign="middle">LVGLS, %</td>
<td align="center" valign="middle">&gt; 18%</td>
<td align="center" valign="middle">&gt; 18%</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">RVGLS, %</td>
<td align="center" valign="middle">&gt; 20%</td>
<td align="center" valign="middle">&gt; 20%</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="TFN2"><p>IVSd: interventricular septum in diastole; LVEDD: left ventricular end-diastolic diameter; LVEF: left ventricular ejection fraction; LVESD: left ventricular end-systolic diameter; LVGLS: left ventricular global longitudinal strain; LVM: left ventricular mass; PWd: posterior wall in diastole; RVBD: right ventricular base diameter; RVGLS: right ventricular global longitudinal strain; TAPSE: tricuspid annular plane systolic excursion.</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec>
<title>Chest CT</title>
<p>Patients underwent pulmonary CT evaluation within the first 48 hours of admission, using a Toshiba Alexion 16-channel CT scanner. Moreover, their images were processed for assessment on a K-Pacs reporting system. The multinational consensus of the Fleischner Society<sup><xref ref-type="bibr" rid="B18">18</xref></sup> was utilized, where an experienced radiologist performed the analyses, classifying the pulmonary involvement in patients as mild (pulmonary involvement &lt; 25%), moderate (pulmonary involvement between 25% and 50%), and severe (pulmonary involvement &gt; 50%).</p>
</sec>
<sec>
<title>Statistical analysis</title>
<p>Echocardiographic, CT, clinical, and epidemiological variables were analyzed for the normality of their distribution using the Kolmogorov-Smirnov test. Since all data showed a normal distribution, continuous variables were presented as mean ± standard deviation, and categorical variables were reported as proportions.</p>
<p>The variables of patients who were discharged (discharge group) or who passed away (death group) were compared using the unpaired two-tailed Student&apos;s t test (for continuous variables) or the chi-square test (for categorical variables), or their non-parametric equivalents, when applicable.</p>
<p>The assumptions of the Cox model were verified, including the proportionality of hazards, which was confirmed through the Schoenfeld test (p &gt; 0.05) and residual plots. There was no indication of multicollinearity (VIF &lt; 10 for all covariates), and the sample size was considered sufficient, with an adequate number of events for each covariate. Therefore, we proceeded with the analysis of the independent prognostic power of each studied variable by constructing several Cox regression analysis models.</p>
<p>To test the independent prognostic power of each variable under study, various multiple regression analysis models were constructed. Echocardiographic variables that retained their independent prognostic power in the multiple regression analysis were used to construct ROC (receiver operating characteristic) curves, using hospital mortality as the outcome. Thereafter, cutoff points and their sensitivity, specificity, and area under the curve were calculated for each of these parameters. The best balance between sensitivity and specificity defined the cutoff point for the variables used to construct the Kaplan-Meier survival curve.</p>
<p>A two-tailed p value of &lt; 0.05 was considered significant. All statistical analyses were conducted using STATA 14.2 software (StataCorp, Texas, USA).</p>
</sec>
</sec>
<sec sec-type="results">
<title>Results</title>
<p>During the period from March 28 to December 30, 2020, 174 patients admitted to the ICU of HGNI were analyzed. Of these, 24 patients did not have adequate echocardiographic imaging for the study of myocardial deformation, accounting for 13.8% of the total. The in-hospital mortality rate among the patients included in the study was high (64%), as demonstrated in <xref ref-type="fig" rid="f2">Figure 1</xref>.</p>
<fig id="f2">
<label>Figure 1</label>
<caption><title>Flow diagram of patients included in the study. ICU: intensive care unit.</title></caption>
<graphic xlink:href="2675-312X-abcimg-37-04-e20240067-gf02.tif"/>
</fig>
<sec>
<title>Demographic data, CT, and presence of comorbidities</title>
<p>Among the 150 patients included in this study, as described in <xref ref-type="table" rid="t3">Table 3</xref>, the mean age was 56 ± 14 years, with 77 (51.3%) being male. The majority (77.3%) of the patients exhibited over 50% pulmonary involvement. Regarding comorbidities, hypertension was the most prevalent (84%), followed by obesity (41.3%), and DM (34%).</p>
<table-wrap id="t3">
<label>Table 3</label>
<caption><title>Demographic data, presence of comorbidities, and pulmonary involvement of patients included in the study</title></caption>
<table frame="hsides" rules="groups">
<colgroup width="20%">
<col/>
<col/>
<col/>
<col/>
<col/>
</colgroup>
<thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
<tr style="background-color:#C58874">
<th align="left" valign="middle">Parameter</th>
<th align="center" valign="middle">Total patients (n = 150)</th>
<th align="center" valign="middle">Patients discharged (n = 54)</th>
<th align="center" valign="middle">Patients who died (n = 96)</th>
<th align="center" valign="middle">p value</th>
</tr>
</thead>
<tbody style="border-bottom: thin solid; border-color: #000000">
<tr>
<td align="left" valign="middle">Age (years)</td>
<td align="center" valign="middle">56 ± 14</td>
<td align="center" valign="middle">50 ± 12</td>
<td align="center" valign="middle">59 ± 15</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">Male sex [n (%)]</td>
<td align="center" valign="middle">77 (51.3%)</td>
<td align="center" valign="middle">30 (56%)</td>
<td align="center" valign="middle">47 (49%)</td>
<td align="center" valign="middle">0.44</td>
</tr>
<tr>
<td align="left" valign="middle">Pulmonary involvement &gt;50% on CT [n (%)]</td>
<td align="center" valign="middle">116 (77.3%)</td>
<td align="center" valign="middle">26 (48%)</td>
<td align="center" valign="middle">90 (94%)</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">Obesity [n (%)]</td>
<td align="center" valign="middle">62 (41.3%)</td>
<td align="center" valign="middle">13 (24%)</td>
<td align="center" valign="middle">49 (51%)</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">Hypertension [n (%)]</td>
<td align="center" valign="middle">126 (84.0%)</td>
<td align="center" valign="middle">36 (67%)</td>
<td align="center" valign="middle">90 (94%)</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">DM [n (%)]</td>
<td align="center" valign="middle">51 (34.0%)</td>
<td align="center" valign="middle">4 (7%)</td>
<td align="center" valign="middle">47 (49%)</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="TFN3"><p>CT: computed tomography; DM: diabetes mellitus.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>Patients who died had a higher mean age (59 ± 15 versus 50 ± 12 years, p &lt; 0.001) and more comorbidities compared to those who were discharged (<xref ref-type="table" rid="t3">Table 3</xref>). A clear difference was observed in age and comorbidities when both groups were compared in the univariate analysis (<xref ref-type="table" rid="t3">Table 3</xref>). However, after multivariate regression analysis of the demographic parameters, only the presence of more than 50% pulmonary involvement on tomography remained as an independent predictor of in-hospital mortality (<xref ref-type="fig" rid="f3">Figure 2</xref>).</p>
<fig id="f3">
<label>Figure 2</label>
<caption><title>Multivariate Cox regression analysis of demographic parameters, pulmonary involvement on CT, and the presence of comorbidities, considering the outcome of in-hospital mortality</title></caption>
<graphic xlink:href="2675-312X-abcimg-37-04-e20240067-gf03.tif"/>
</fig>
</sec>
<sec>
<title>Echocardiographic parameters</title>
<p>Patients who died had larger ventricular dimensions and a lower LVEF compared to patients who were discharged (<xref ref-type="table" rid="t4">Table 4</xref>). Only 36% of the patients who died had an abnormal LVEF, while only 2% of the patients who were discharged presented with an abnormal LVEF.</p>
<table-wrap id="t4">
<label>Table 4</label>
<caption><title>Echocardiographic parameters within the first 48 hours of ICU admission in COVID-19 patients who were discharged and those who died during hospitalization</title></caption>
<table frame="hsides" rules="groups">
<colgroup width="25%">
<col/>
<col/>
<col/>
<col/>
</colgroup>
<thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
<tr style="background-color:#C58874">
<th align="left" valign="middle">Echocardiographic parameter</th>
<th align="center" valign="middle">Patients discharged (n = 54)</th>
<th align="center" valign="middle">Patients who died (n = 96)</th>
<th align="center" valign="middle">p value</th>
</tr>
</thead>
<tbody style="border-bottom: thin solid; border-color: #000000">
<tr>
<td align="left" valign="middle">IVSd (mm)</td>
<td align="center" valign="middle">8.1 ± 0.8</td>
<td align="center" valign="middle">8.7 ± 1.3</td>
<td align="center" valign="middle">0.009</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">LVEDD (mm)</td>
<td align="center" valign="middle">47.2 ± 4.4</td>
<td align="center" valign="middle">50.2 ± 7.8</td>
<td align="center" valign="middle">0.010</td>
</tr>
<tr>
<td align="left" valign="middle">LVESD (mm)</td>
<td align="center" valign="middle">29.8 ± 2.8</td>
<td align="center" valign="middle">35.3 ± 8.7</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">PWd (mm)</td>
<td align="center" valign="middle">8.2 ± 0.7</td>
<td align="center" valign="middle">8.9 ± 1.4</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">LVEF (Simpson&apos;s biplane, %)</td>
<td align="center" valign="middle">66 ± 4</td>
<td align="center" valign="middle">57 ± 12</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">E wave (cm/s)</td>
<td align="center" valign="middle">0.7 ± 0.2</td>
<td align="center" valign="middle">0.6 ± 0.2</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">A wave (cm/s)</td>
<td align="center" valign="middle">0.7 ± 0.2</td>
<td align="center" valign="middle">0.7 ± 0.2</td>
<td align="center" valign="middle">0.36</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">LVM (g)</td>
<td align="center" valign="middle">161.2 ± 36.5</td>
<td align="center" valign="middle">195.7 ± 63.0</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">E/A ratio</td>
<td align="center" valign="middle">1.1 ± 0.4</td>
<td align="center" valign="middle">0.9 ± 0.6</td>
<td align="center" valign="middle">0.032</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">RVBD (mm)</td>
<td align="center" valign="middle">32.3 ± 3.0</td>
<td align="center" valign="middle">37.2 ± 6.1</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">PASP (mmHg)</td>
<td align="center" valign="middle">23.6 ± 4.0</td>
<td align="center" valign="middle">34.0 ± 10.8</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">TAPSE (mm)</td>
<td align="center" valign="middle">22.2 ± 2.3</td>
<td align="center" valign="middle">19.4 ± 3.2</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="TFN4"><p>IVSd: interventricular septum in diastole; LVEDD: left ventricular end-diastolic diameter; LVEF: left ventricular ejection fraction; LVESD: left ventricular end-systolic diameter; LVM: left ventricular mass; PASP: pulmonary artery systolic pressure; PWd: posterior wall in diastole; RVBD: right ventricular base diameter; TAPSE: tricuspid annular plane systolic excursion.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>Considering a cutoff point of 40% for LVEF, 16% of the patients who died had an alteration while none of the discharged patients presented this condition (p = 0.002) (<xref ref-type="table" rid="t5">Table 5</xref>).</p>
<table-wrap id="t5">
<label>Table 5</label>
<caption><title>Frequency of altered echocardiographic parameters within the first 48 hours of ICU admission in COVID-19 patients who were discharged and those who died during hospitalization</title></caption>
<table frame="hsides" rules="groups">
<colgroup width="25%">
<col/>
<col/>
<col/>
<col/>
</colgroup>
<thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
<tr style="background-color:#C58874">
<th align="left" valign="middle">Echocardiographic parameter</th>
<th align="center" valign="middle">Patients discharged (n = 54)</th>
<th align="center" valign="middle">Patients who died (n = 96)</th>
<th align="center" valign="middle">p value</th>
</tr>
</thead>
<tbody style="border-bottom: thin solid; border-color: #000000">
<tr>
<td align="left" valign="middle">Normal IVSd (mm)</td>
<td align="center" valign="middle">54 (100)</td>
<td align="center" valign="middle">94 (98)</td>
<td align="center" valign="middle">0.29</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">LVEDD (mm)</td>
<td align="center" valign="middle">53 (98)</td>
<td align="center" valign="middle">71 (74)</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">PW [n(%)]</td>
<td align="center" valign="middle">54 (100)</td>
<td align="center" valign="middle">91 (95)</td>
<td align="center" valign="middle">0.088</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">LVEF [n(%)]</td>
<td align="center" valign="middle">53 (98%)</td>
<td align="center" valign="middle">67 (70%)</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">LVEF &lt; 40% [n(%)]</td>
<td align="center" valign="middle">54 (100%)</td>
<td align="center" valign="middle">81 (84%)</td>
<td align="center" valign="middle">0.002</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">LVM [n(%)]</td>
<td align="center" valign="middle">42 (78)</td>
<td align="center" valign="middle">48 (50)</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">E/A ratio [n(%)]</td>
<td align="center" valign="middle">23 (43)</td>
<td align="center" valign="middle">65 (68)</td>
<td align="center" valign="middle">0.003</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">RVBD n(%)]</td>
<td align="center" valign="middle">53 (98)</td>
<td align="center" valign="middle">69 (72)</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">PASP [n(%)]</td>
<td align="center" valign="middle">40 (74)</td>
<td align="center" valign="middle">36 (38)</td>
<td align="center" valign="middle">&lt;0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="TFN5"><p>IVSd: interventricular septum in diastole; LVEDD: left ventricular end-diastolic diameter; LVEF: left ventricular ejection fraction; LVM: left ventricular mass; PASP: pulmonary artery systolic pressure; PW: posterior wall; RVBD: right ventricular base diameter.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>Among the patients who died, 30% had an increased right ventricular base diameter, in contrast to only 1.85% of discharged patients who exhibited the same increase. Regarding the LVEDD, 26% of the patients who died had elevated values for this parameter, while, among those discharged, only 3.7% showed an increase in LVEDD. These data suggest a correlation between the enlargement of these measurements and a negative outcome during hospitalization for COVID-19.</p>
<p>The comparison of LVGLS revealed lower values in patients who died compared to those who were discharged (15.3 ± 2.3 versus 19.7 ± 1.8, p &lt; 0.001). Similarly, the RVGLS was also lower in patients who died (21.9 ± 4.2 versus 28.0 ± 3.2, p&lt;0.001).</p>
<p>The Cox multivariate analysis indicated that only the LVGLS and more than 50% tomographic involvement remained as independent prognostic predictor variables (<xref ref-type="fig" rid="f4">Figure 3</xref>). Notably, none of the conventional echocardiography variables emerged as independent predictors of prognosis after multivariate analysis.</p>
<fig id="f4">
<label>Figure 3</label>
<caption><title>Multivariate Cox regression analysis of two-dimensional echocardiogram parameters, considering the outcome of in-hospital mortality. IVSd: interventricular septum in diastole with normal values; LVEDD: left ventricular end-diastolic diameter; LVEF: left ventricular ejection fraction; LVESD: left ventricular end-systolic diameter; LVM: left ventricular mass; PASP: pulmonary artery systolic pressure; PWd: posterior wall in diastole; RVBD: right ventricular base diameter; TAPSE: tricuspid annular plane systolic excursion.</title></caption>
<graphic xlink:href="2675-312X-abcimg-37-04-e20240067-gf04.tif"/>
</fig>
<p>A cutoff point of −18.1 was used for the LVGLS in constructing the intra-hospital survival curves (p &lt; 0.001; confidence interval 0.53 to 0.23) (<xref ref-type="fig" rid="f5">Figure 4</xref>).</p>
<fig id="f5">
<label>Figure 4</label>
<caption><title>Kaplan-Meier survival curve based on left ventricular global longitudinal strain. LVGLS: left ventricular global longitudinal strain.</title></caption>
<graphic xlink:href="2675-312X-abcimg-37-04-e20240067-gf05.tif"/>
</fig>
</sec>
</sec>
<sec sec-type="discussion">
<title>Discussion</title>
<p>Since echocardiography was identified as a relevant technique for managing patients with COVID-19, numerous questions and hypotheses have emerged, leading to the development of extensive research worldwide. In this context, our study demonstrated that LVGLS emerged as an independent prognostic marker in patients hospitalized in ICUs due to COVID-19.</p>
<p>With the advancement of these research efforts, certain variables were identified that directly correlate with the outcome of death. The ECHOVID-19 study<sup><xref ref-type="bibr" rid="B19">19</xref></sup> evaluated 214 hospitalized COVID-19 patients without severe criteria and conducted a paired analysis with 214 control patients without a COVID-19 diagnosis. After excluding patients with LVEF &lt; 40%, the authors concluded that reduced LVGLS and elevated TAPSE were prognostic predictors with cutoff points of 16.7% and 24 mm, respectively. This presents a divergence from our study where TAPSE did not show independent prognostic power, and the cutoff for LVGLS was set at less than 18.1%. This indicates that not only the COVID-19 infection itself but also the severity of the patient at the time of admission and the timing of the examination can directly influence the initial analysis. A systematic review and meta-analysis<sup><xref ref-type="bibr" rid="B20">20</xref></sup> also assessed the association between TAPSE and mortality in patients with COVID-19, concluding that lower TAPSE values were associated with higher mortality, with each percentage point decrease resulting in a 20% increased chance of death. However, a specific cutoff point was not provided. Additionally, there were variations among the patient populations used in the meta-analysis, including outpatient groups and more critical patient groups, with variable admission times and examination timings.</p>
<p>In April 2022, Gomez et al.<sup><xref ref-type="bibr" rid="B21">21</xref></sup> assessed echocardiographic predictors of mortality and morbidity in critical COVID-19 patients, analyzing the death outcome over a 60-day hospitalization period. They observed that abnormalities in the right ventricular echocardiographic parameters significantly impacted patient prognosis. Patients with right ventricular dilation had twice the risk of 60-day mortality due to COVID-19, and after multivariate analysis, the right ventricular basal diameter was the only statistically significant variable. However, the timing of the echocardiographic examinations was not specified in their methods, an important factor for understanding the analysis.</p>
<p>Despite the larger values of the right ventricular base diameter and TAPSE observed in patients who died, these variables did not demonstrate independent prognostic power in our study. This could be due to the early collection of data, within 48 hours of admission, meaning this involvement might not have fully manifested, supporting the notion that echocardiographic alterations in the right chambers may become more apparent over the course of hospitalization. This progression can indicate a worsening of the condition, leading to a more unfavorable prognosis.</p>
<p>In studies evaluating LV myocardial deformation in COVID-19 patients, Bhatia et al.<sup><xref ref-type="bibr" rid="B22">22</xref></sup> demonstrated that, although conventional echocardiographic parameters are important, they may not be sufficient. In these studies, despite normal LVEF, patients with greater severity exhibited significantly reduced LVGLS.</p>
<p>Regarding the use of LV deformation values as mortality predictors, Park et al.<sup><xref ref-type="bibr" rid="B23">23</xref></sup> concluded that an LV deformation value of &lt;13.8% was an independent predictor of mortality in hospitalized patients, with a sensitivity of 85% and specificity of 54%. It was also a strong marker of survival. However, the timing of the echocardiographic analysis in this study was not specified, which could account for the difference compared to our data.</p>
<p>Rothschild et al.<sup><xref ref-type="bibr" rid="B24">24</xref></sup> defined an LV deformation value of 16.6% as a predictor for mortality and the need for intubation in admitted patients. A strength of this study was performing the echocardiographic transthoracic test within the first 24 hours of admission. It is common in studies to find a correlation between the presence of subclinical dysfunction and normal LVEF values by two-dimensional echocardiographic analysis.<sup><xref ref-type="bibr" rid="B23">23</xref>,<xref ref-type="bibr" rid="B24">24</xref></sup></p>
<p>These findings corroborate those of the present research, demonstrating that the evaluation of strain is extremely important in defining ventricular function and in identifying cutoff points of LV deformation as predictors of mortality and survival curves.</p>
<p>In our study, we identified that echocardiographic analysis can provide various important variables in assessing patients with severe COVID-19. However, alteration in LVGLS was the only echocardiographic variable that could predict prognosis in patients hospitalized in intensive care with COVID-19 infection.</p>
<p>COVID-19 infection has raised many questions regarding the progression of affected patients. Various pathologies have been associated with worse prognoses, rapid disease progression, and overall disease severity. However, understanding whether merely possessing a risk factor is indicative of a more severe disease course has been and continues to be the focus of extensive research.</p>
<p>This study observed that the prevalence of a more aggressive disease course was associated with the presence of risk factors; however, having some degree of cardiac structural or functional alteration was found to be more relevant than merely having hypertension, DM, obesity, or belonging to a specific sex. Even the presence of biomarkers indicating cardiac injury was less significant.</p>
<p>This line of reasoning leads to another question: understanding which type of echocardiographic technique should be used to define LV function in COVID-19 patients. In this context, the use of echocardiography, with myocardial deformation analysis, emerges as a viable option to define the presence or absence of myocardial dysfunction early on. This approach can then truly determine whether an isolated risk factor is associated with a worse prognosis of COVID-19.</p>
<sec>
<title>Limitations</title>
<p>Regarding the limitations of this study, it is important to note that the analyzed patients were admitted to the ICU, and the study group thus represented cases with more severe COVID-19 progression. Nonetheless, it was possible to identify patients with higher severity who eventually succumbed to in-hospital mortality.</p>
<p>One of the primary challenges encountered was the difficulty in positioning patients in bed to achieve the necessary angulation for optimal image acquisition. This issue, compounded by the chaotic environment caused by the pandemic, led to inadequate imaging for some patients. Similar difficulties in image collection have been reported in ICUs by Croft et al.<sup><xref ref-type="bibr" rid="B25">25</xref></sup> where 53.7% of patients were excluded due to inadequate images. Additionally, Krishnamoorthy et al.<sup><xref ref-type="bibr" rid="B26">26</xref></sup> excluded 88.4% of their patients, and Lassen et al.<sup><xref ref-type="bibr" rid="B27">27</xref></sup> had only 9.3% of their patients excluded for inadequate images, although their examinations were conducted on an outpatient basis.</p>
<p>The correlation between myocardial dysfunction and cardiac injury biomarkers could not be performed in all patients, due to the lack of resources in the unit for conducting laboratory tests within the first 48 hours of admission. Additionally, the unavailability of other supplies precluded the analysis of other markers such as PCR, D-dimer, and interleukins, which were not included in the study.</p>
<p>There was also no correlation made with the drugs used in treatment due to the high divergence in treatments at the time, as it was a period of learning and experimentation in this regard. However, it is important to note that the researchers did not interfere with the therapeutic conduct, and all patients were treated according to the best practices available during that period.</p>
<p>The measurement of systolic and diastolic blood pressure was not included in our data due to the wide variety of sphygmomanometer models in the unit. Even if the echocardiographic examiner wished to perform the pressure measurement at the time of the exam, there was no universal understanding at that time about the management and use of these devices among patients.</p>
<p>Among all the difficulties encountered, the greatest was undoubtedly related to the timing of the research, as we were living under the shadow of insecurity and uncertainty caused by a lack of knowledge, along with a constant fear that dominated the environment. Even though motivated by the necessity of discovery and the production of knowledge to assist the population, these conditions significantly hampered the research process.</p>
</sec>
</sec>
<sec sec-type="conclusions">
<title>Conclusion</title>
<p>We have determined that two-dimensional echocardiography has limited value for routine screening in patients hospitalized with COVID-19, not presenting specific variables that could contribute to prognostic analysis. Even when these variables show statistical significance, they are within the normal range, leading to interpretative ambiguities.</p>
<p>In this context, LVGLS demonstrates high levels of sensitivity and specificity, making it a reliable tool for prognostic evaluation in patients hospitalized in serious condition with COVID-19 infection.</p>
<p>In the fight against COVID-19, it is essential to identify patients at greater risk of developing severe forms of the disease. In addition to existing comorbidities, the prior condition of cardiac function emerges as a decisive factor in risk stratification. Therefore, meticulous analysis is crucial for a more precise risk assessment.</p>
</sec>
</body>
<back>
<fn-group>
<fn fn-type="financial-disclosure" id="fn1"><label>Sources of Funding</label><p>There were no external funding sources for this study.</p></fn>
<fn fn-type="other" id="fn2"><label>Study Association</label><p>This article is part of the thesis of master submitted by João Giffoni da Silveira Neto, from Universidade Federal Fluminense.</p></fn>
<fn fn-type="other" id="fn3"><label>Ethics Approval and Consent to Participate</label><p>This study was approved by the Ethics Committee on Animal Experiments of the Universidade Iguaçu under the protocol number 39511820.5.0000.8044.</p></fn>
</fn-group>
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<sub-article article-type="translation" id="S1" xml:lang="pt">
<front-stub>
<article-id pub-id-type="doi">10.36660/abcimg.20240067</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Artigo Original</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>O Impacto Prognóstico das Medidas de Deformação Miocárdica em Pacientes com COVID-19</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">0000-0002-8678-5501</contrib-id>
<name><surname>Silveira</surname><given-names>João Giffoni</given-names><suffix>Neto</suffix></name>
<xref ref-type="aff" rid="aff5"><sup>1</sup></xref>
<xref ref-type="corresp" rid="c2"/>
<role>Concepção e desenho da pesquisa</role>
<role>obtenção de dados</role>
<role>análise e interpretação dos dados</role>
<role>análise estatística</role>
<role>revisão crítica do manuscrito quanto ao conteúdo intelectual importante</role>
<role>redação do manuscrito</role>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">0000-0002-2499-4295</contrib-id>
<name><surname>Campos</surname><given-names>Marcello de Brito</given-names></name>
<xref ref-type="aff" rid="aff6"><sup>2</sup></xref>
<role>obtenção de dados</role>
<role>análise e interpretação dos dados</role>
<role>redação do manuscrito</role>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">0009-0006-2935-3266</contrib-id>
<name><surname>Mello</surname><given-names>Luiz</given-names></name>
<xref ref-type="aff" rid="aff6"><sup>2</sup></xref>
<role>obtenção de dados</role>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">0009-0005-4694-8838</contrib-id>
<name><surname>Giffoni</surname><given-names>Marcela de Castro</given-names></name>
<xref ref-type="aff" rid="aff7"><sup>3</sup></xref>
<role>Concepção e desenho da pesquisa</role>
<role>obtenção de dados</role>
<role>redação do manuscrito</role>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">0009-0001-1541-5204</contrib-id>
<name><surname>Goveia</surname><given-names>Natanael Arnor da Silva Barros</given-names></name>
<xref ref-type="aff" rid="aff8"><sup>4</sup></xref>
<role>obtenção de dados</role>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">0000-0002-3830-2886</contrib-id>
<name><surname>Nóbrega</surname><given-names>Antonio Claudio Lucas da</given-names></name>
<xref ref-type="aff" rid="aff5"><sup>1</sup></xref>
<role>Concepção e desenho da pesquisa</role>
<role>análise e interpretação dos dados</role>
<role>análise estatística</role>
<role>revisão crítica do manuscrito quanto ao conteúdo intelectual importante</role>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">0000-0001-5560-693X</contrib-id>
<name><surname>Castro</surname><given-names>Renata R. T.</given-names></name>
<xref ref-type="aff" rid="aff6"><sup>2</sup></xref>
<role>Concepção e desenho da pesquisa</role>
<role>análise e interpretação dos dados</role>
<role>análise estatística</role>
<role>revisão crítica do manuscrito quanto ao conteúdo intelectual importante</role>
<role>redação do manuscrito</role>
</contrib>
<aff id="aff5">
<label>1</label>
<addr-line>
<named-content content-type="city">Niterói</named-content>
<named-content content-type="state">RJ</named-content>
</addr-line>
<country country="BR">Brasil</country>
<institution content-type="original">Universidade Federal Fluminense, Niterói, RJ – Brasil</institution>
</aff>
<aff id="aff6">
<label>2</label>
<addr-line>
<named-content content-type="city">Nova Iguacu</named-content>
<named-content content-type="state">RJ</named-content>
</addr-line>
<country country="BR">Brasil</country>
<institution content-type="original">Universidade Iguaçu, Nova Iguacu, RJ – Brasil</institution>
</aff>
<aff id="aff7">
<label>3</label>
<addr-line>
<named-content content-type="city">Rio de Janeiro</named-content>
<named-content content-type="state">RJ</named-content>
</addr-line>
<country country="BR">Brasil</country>
<institution content-type="original">PUC-Rio, Rio de Janeiro, RJ – Brasil</institution>
</aff>
<aff id="aff8">
<label>4</label>
<addr-line>
<named-content content-type="city">Rio de Janeiro</named-content>
<named-content content-type="state">RJ</named-content>
</addr-line>
<country country="BR">Brasil</country>
<institution content-type="original">Universidade Federal do Estado do Rio de Janeiro, Rio de Janeiro, RJ – Brasil</institution>
</aff>
</contrib-group>
<author-notes>
<corresp id="c2"><label>Correspondência: João Giffoni Silveira Neto •</label> Universidade Iguaçu. Av. Abílio Augusto Távora, 2134. CEP: <postal-code>26275-580</postal-code>. Jardim Alvorada, Nova Iguaçu, RJ – Brasil E-mail: <email>joao.giffoni2@hotmail.com</email></corresp>
<fn fn-type="conflict"><label>Potencial Conflito de Interesse</label><p>Declaro não haver conflito de interesses pertinentes.</p></fn>
<fn fn-type="edited-by"><label>Editor responsável pela revisão:</label><p>Marcelo Tavares</p></fn>
</author-notes>
<abstract>
<title>Resumo</title>
<sec>
<title>Fundamento:</title>
<p>O envolvimento cardiovascular na COVID-19 foi extensivamente estudado. A ecocardiografia é uma técnica importante na identificação do acometimento cardíaco, servindo como excelente ferramenta para variáveis prognósticas.</p>
</sec>
<sec>
<title>Objetivo:</title>
<p>Analisar o impacto prognóstico do speckle tracking na análise do ventrículo esquerdo (VE) em pacientes com COVID-19 internados em unidades de terapia intensiva (UTI).</p>
</sec>
<sec>
<title>Métodos:</title>
<p>Pacientes com diagnóstico de COVID-19 admitidos na unidade de terapia intensiva foram submetidos a exame ecocardiográfico nas primeiras 48 horas de internação e divididos em dois grupos de acordo com o desfecho hospitalar (alta ou óbito). Os dados ecocardiográficos convencionais, e de strain longitudinal global do ventrículo esquerdo (SLGVE) e ventrículo direito (SLGVD) de ambos os grupos foram comparados pelo teste t de Student (variáveis contínuas) ou pelo teste do qui-quadrado (variáveis categóricas), considerando-se como estatisticamente significativo p &lt; 0,05.</p>
</sec>
<sec>
<title>Resultados:</title>
<p>A média de idade foi de 56 ± 14 anos, e a proporção de homens e mulheres foi semelhante. A taxa de mortalidade foi de 64%, mais frequente em pacientes idosos e em pacientes com maior número de comorbidades. O SLGVE revelou valores menores nos pacientes que evoluíram para óbito, com ponto de corte abaixo de −18,1% (sensibilidade = 90,4%, especificidade = 96,6%) para esse desfecho e, após análise estatística multivariada, foi a única variável ecocardiográfica estatisticamente significativa.</p>
</sec>
<sec>
<title>Conclusão:</title>
<p>O SLGVE é uma ferramenta importante na análise prognóstica desses pacientes, oferecendo uma nova janela de possibilidades para avaliar pacientes críticos com COVID-19.</p>
</sec>
</abstract>
<kwd-group xml:lang="pt">
<title>Palavras-chave:</title>
<kwd>COVID-19</kwd>
<kwd>Ecocardiografia</kwd>
<kwd>Deformação Longitudinal Global</kwd>
</kwd-group>
</front-stub>
<body>
<fig id="f6">
<graphic xlink:href="2675-312X-abcimg-37-04-e20240067-gf01-pt.tif"/>
</fig>
<sec sec-type="intro">
<title>Introdução</title>
<p>A compreensão evolutiva de COVID-19, inicialmente identificada como uma síndrome respiratória aguda, foi expandida por estudos que revelam implicações cardiovasculares significativas.<sup><xref ref-type="bibr" rid="B1">1</xref>-<xref ref-type="bibr" rid="B4">4</xref></sup> Isto levantou questões pertinentes sobre se a presença de condições cardiovasculares preexistentes é um fator de risco para a severidade e mortalidade de COVID-19, sugerindo um perfil de vulnerabilidade em pacientes afetados,<sup><xref ref-type="bibr" rid="B5">5</xref>-<xref ref-type="bibr" rid="B10">10</xref></sup> ou se a infecção por SARS-CoV-2 poderia induzir complicações cardiovasculares mesmo em indivíduos sem uma história de doenças cardíacas.</p>
<p>Nesse contexto, a ecocardiografia bidimensional no manejo de pacientes com COVID-19 é particularmente útil, especialmente dada a prevalência de envolvimento miocárdico nessas infecções. Ela fornece informações valiosas para definir o envolvimento cardíaco e o manejo do paciente.<sup><xref ref-type="bibr" rid="B11">11</xref>-<xref ref-type="bibr" rid="B13">13</xref></sup> O uso de técnicas como o strain miocárdico aprimora essas avaliações por meio da análise da deformação miocárdica, uma abordagem mais sensível do que as avaliações volumétricas e frações de ejeção tradicionais, demonstrando alta confiabilidade inter e intraobservador.<sup><xref ref-type="bibr" rid="B14">14</xref>-<xref ref-type="bibr" rid="B16">16</xref></sup></p>
<p>Entendemos que a presença de alterações precoces na função miocárdica, particularmente relacionadas à disfunção sistólica subclínica do ventrículo esquerdo (VE), pode estar associada a desfechos piores em pacientes afetados pela COVID-19. Consequentemente, o uso da ecocardiografia com strain miocárdico (Figura Central) torna-se crucial na avaliação inicial desses pacientes. Assim, o objetivo primário deste estudo é investigar o impacto prognóstico da utilização da técnica speckle tracking na análise de strain miocárdico para a avaliação de pacientes acometidos por infecção por COVID-19. Isso inclui descrever a função ventricular esquerda em pacientes admitidos em unidades de terapia intensiva (UTIs) com COVID-19 e avaliar o poder prognóstico independente da técnica speckle tracking na análise da função ventricular esquerda desses pacientes.</p>
</sec>
<sec sec-type="methods">
<title>Métodos</title>
<sec>
<title>Desenho e população do estudo</title>
<p>Trata-se de um estudo longitudinal, observacional e prospectivo. Para sua execução, foram recrutados todos os pacientes internados por infecção por COVID-19 nas UTIs do Hospital Geral de Nova Iguaçu (HGNI) no período de 28 de março a 30 de dezembro de 2020. Os critérios de internação nessas unidades incluíram sinais de gravidade e necessidade de ventilação mecânica.</p>
<p>O diagnóstico de COVID-19 foi confirmado com um resultado positivo do ensaio em tempo real de transcriptase reversa – reação em cadeia da polimerase (RT-PCR) de swabs faríngeos. Todos os participantes do estudo foram submetidos à análise ecocardiográfica em até 48 horas após a admissão. Além disso, foram realizadas tomografias computadorizadas (TC) dos pulmões.</p>
<p>Dados demográficos como idade, sexo, etnia, peso, altura e comorbidades conhecidas foram coletados e catalogados juntamente com um questionário, que está disponível no anexo. Isso incluiu dados ecocardiográficos e achados de TC. A presença de comorbidades, como hipertensão arterial ou diabetes mellitus (DM), foi relatada pelo próprio paciente ou, nos casos em que o paciente não conseguiu responder (por estar sedado e intubado), as informações foram obtidas do prontuário ou fornecidas por um familiar.</p>
<p>Os pacientes foram monitorados durante toda a internação quanto ao desfecho final intra-hospitalar (alta, óbito ou transferência). Este estudo não interferiu na conduta médica durante a internação e levou em consideração que todos os cuidados prestados estavam de acordo com as melhores práticas vigentes.</p>
</sec>
<sec>
<title>Critérios para admissão de pacientes em UTI</title>
<p>Os pacientes internados na UTI com diagnóstico de COVID-19 foram avaliados com base em testes RT-PCR realizados com amostras de secreção respiratória coletadas com swab nasofaríngeo na admissão do paciente no hospital, apresentando sinais ou sintomas de infecção por SARS-CoV-2. Os testes utilizaram kits produzidos pelo Laboratório Seegene, da República da Coreia, fornecidos pelo Ministério da Saúde no período. A avaliação de sinais ou sintomas seguiu as orientações do Protocolo de Manejo Clínico para COVID-19 na Atenção Especializada do Ministério da Saúde, conforme versão eletrônica da 1ª edição revisada de 2020.</p>
</sec>
<sec>
<title>Foram considerados graves os pacientes que demonstrassem alguma das seguintes características:<sup><xref ref-type="bibr" rid="B17">17</xref></sup></title>
<list list-type="alpha-lower">
<list-item><p>Insuficiência respiratória: dificuldade respiratória importante, caracterizada por dispneia, hipoxemia (baixo nível de oxigênio no sangue) ou frequência respiratória elevada (taquipnéia), e necessidade de suporte de oxigênio suplementar ou ventilação mecânica;</p></list-item>
<list-item><p>Alterações hemodinâmicas: hipotensão não responsiva à ressuscitação volêmica, presença de choque, seja ele séptico, cardiogênico ou de outro tipo;</p></list-item>
<list-item><p>Alterações de consciência: confusão, desorientação ou rebaixamento do nível de consciência, que podem indicar comprometimento do sistema nervoso central ou encefalopatia metabólica;</p></list-item>
<list-item><p>Coagulopatias: evidência de coagulação intravascular disseminada ou tromboembolismo venoso;</p></list-item>
<list-item><p>Imagem de tórax: infiltrados multilobares progressivos em radiografias de tórax ou tomografia computadorizada (TC) com extenso envolvimento pulmonar.</p></list-item>
</list>
</sec>
<sec>
<title>Critérios de inclusão e exclusão de pacientes</title>
<p>Foram incluídos no estudo pacientes internados no HGNI durante o período deste estudo (<xref ref-type="table" rid="t6">Tabela 1</xref>), de ambos os sexos, com idade igual ou superior a 18 anos, com diagnóstico confirmado de infecção por COVID-19. Foram excluídos do estudo os pacientes que faleceram ou receberam alta hospitalar antes da realização do ecocardiograma. Além disso, pacientes que foram transferidos para outro hospital em algum momento do estudo também foram excluídos, pois tais transferências impossibilitaram o acompanhamento dos desfechos dos pacientes. Pacientes que não possuíam imagens ecocardiográficas adequadas para análise speckle tracking também foram excluídos. Não houve exclusões com base em resultados inconclusivos dos testes RT-PCR. Todos os pacientes do estudo foram submetidos a TC dos pulmões.</p>
<table-wrap id="t6">
<label>Tabela 1</label>
<caption><title>Critérios de inclusão e exclusão dos pacientes no estudo</title></caption>
<table frame="hsides" rules="groups">
<colgroup width="50%">
<col/>
<col/>
</colgroup>
<thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
<tr style="background-color:#C58874">
<th align="left" valign="middle">Pacientes incluídos no estudo</th>
<th align="center" valign="middle">Pacientes excluídos do estudo</th>
</tr>
</thead>
<tbody style="border-bottom: thin solid; border-color: #000000">
<tr>
<td align="left" valign="middle">Internados em UTI do HGNI com diagnóstico de COVID-19</td>
<td align="center" valign="middle">Vieram a óbito antes da realização dos exames de ecocardiografia</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">Diagnóstico de COVID-19 realizado pelo teste PCR- RT</td>
<td align="center" valign="middle">Foram transferidos para outra unidade de saúde, impossibilitando o acompanhamento do desfecho</td>
</tr>
<tr>
<td align="left" valign="middle">Realização de TC de pulmão</td>
<td align="center" valign="middle">Diagnóstico inconclusivo de COVID-19</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">Realização de exame ecocardiográfico até 48 h após a internação em UTI</td>
<td align="center" valign="middle">Imagens ecocardiográficas inadequadas para a avaliação da técnica do strain miocárdico</td>
</tr>
<tr>
<td align="left" valign="middle">Maiores de 18 anos</td>
<td align="center" valign="middle">Menores de 18 anos</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="TFN6"><p>HGNI: Hospital Geral de Nova Iguaçu; PCR-RT: transcriptase reversa – reação em cadeia da polimerase; UTI: unidade de terapia intensiva; TC: tomografia computadorizada.</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec>
<title>Análise ecocardiográfica</title>
<p>A avaliação ecocardiográfica dos participantes do estudo foi realizada nas primeiras 48 horas após a admissão hospitalar. As imagens foram coletadas utilizando-se o equipamento de ecocardiografia Vivid IQ da GE Healthcare, empregando-se um transdutor setorial adulto 3Sc-RS da GE. A aquisição e análise dos dados ecocardiográficos foram realizadas por um único examinador com vasta experiência. A aquisição das imagens foi realizada seguindo as diretrizes da American Society of Echocardiography (ASE) e da European Association of Cardiovascular Imaging (EACVI).<sup><xref ref-type="bibr" rid="B11">11</xref></sup> Todos os dados foram analisados antes que os desfechos dos pacientes fossem conhecidos.</p>
<p>Na análise ecocardiográfica bidimensional, foram obtidos dados dos diâmetros do coração direito e esquerdo, incluindo diâmetro diastólico do ventrículo esquerdo (DDVE), diâmetro sistólico do ventrículo esquerdo (DSVE), corte longitudinal do eixo longo, bem como espessura da parede posterior do ventrículo esquerdo (PPVE), espessura do septo interventricular (SIV), valores utilizados para obtenção da massa ventricular esquerda (MVE) e espessura relativa da parede (ERP), usando a equação 2 × PPVE/DDVE. Além disso, o diâmetro da base do ventrículo direito foi obtido pelo corte apical 4 câmaras (4C), com ênfase nas câmaras direitas.</p>
<p>Na avaliação da função diastólica do VE, pelo Doppler pulsátil do fluxo transmitral na incidência apical 4C, foram obtidas as velocidades da onda E e da onda A, além da relação E/A. A avaliação da pressão sistólica da artéria pulmonar (PSAP), avaliada pela velocidade máxima da regurgitação tricúspide pelo Doppler de onda contínua do fluxo da regurgitação tricúspide, define a velocidade máxima desse fluxo ao quadrado, multiplicada por 4, e é aumentada por valores baseados na variação do diâmetro da veia cava inferior, avaliada no corte subxifoide.</p>
<p>As análises da deformação miocárdica global longitudinal do VE foram realizadas por meio de imagens adquiridas no eixo longo apical em quatro, duas e três câmaras. Essas imagens foram transferidas para uma plataforma de análise off-line (EchoPAC Software Only v 202), onde foram processadas para estudo. O pico de strain sistólico foi definido como o ponto de encurtamento sistólico máximo para deformação longitudinal. O fechamento da valva aórtica foi utilizado como ponto de referência para definir o término da sístole com o speckle tracking.</p>
<p>A análise da fração de ejeção do ventrículo esquerdo (FEVE) foi realizada pela técnica biplanar de Simpson, por meio das incidências 4C e 2C, e a análise do strain longitudinal global do ventrículo esquerdo (SLGVE), utilizando como pontos de corte valores anormais para FEVE (&lt; 52% para homens e &lt; 54% para mulheres e &lt; 18% para ambos os sexos para o SLGVE). A função ventricular direita foi analisada pela excursão sistólica do plano do ânulo tricúspide (TAPSE), por meio do corte apical 4C, com ênfase nas câmaras direitas, com valores de corte anormais de &lt; 17 mm. Além disso, o strain longitudinal global do ventrículo direito (SLGVD) também foi analisado off-line usando EchoPAC Software Only v 202, com valores de corte anormais de &lt; 20%.</p>
<p>Os valores normais das variáveis ecocardiográficas em relação ao sexo e também ao strain miocárdico biventricular podem ser observados na <xref ref-type="table" rid="t7">Tabela 2</xref> e seguiram as orientações das Recomendações para Quantificação de Câmaras por Ecocardiografia em Adultos da ASE e da EACVI<sup><xref ref-type="bibr" rid="B11">11</xref></sup> e o Posicionamento do Departamento de Imagem Cardiovascular da Sociedade Brasileira de Cardiologia sobre o Uso do Strain Miocárdico na Rotina do Cardiologista.<sup><xref ref-type="bibr" rid="B16">16</xref></sup></p>
<table-wrap id="t7">
<label>Tabela 2</label>
<caption><title>Valores de referência para normalidade das variáveis ecocardiográficas e valores de deformação longitudinal biventricular</title></caption>
<table frame="hsides" rules="groups">
<colgroup width="33%">
<col/>
<col/>
<col/>
</colgroup>
<thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
<tr style="background-color:#C58874">
<th align="left" valign="middle">Parâmetros ecocardiográficos</th>
<th align="center" valign="middle">Valor de referência – masculino</th>
<th align="center" valign="middle">Valor de referência – feminino</th>
</tr>
</thead>
<tbody style="border-bottom: thin solid; border-color: #000000">
<tr>
<td align="left" valign="middle">SIV, (mm)</td>
<td align="center" valign="middle">Maior que 11</td>
<td align="center" valign="middle">Maior que 11</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">DDVE, (mm)</td>
<td align="center" valign="middle">42 a 58,4</td>
<td align="center" valign="middle">37,8 a 52,2</td>
</tr>
<tr>
<td align="left" valign="middle">DSVE, (mm)</td>
<td align="center" valign="middle">25 a 39,8</td>
<td align="center" valign="middle">21,6 a 34,8</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">PPVE, (mm)</td>
<td align="center" valign="middle">Maior que 11</td>
<td align="center" valign="middle">Maior que 11</td>
</tr>
<tr>
<td align="left" valign="middle">FEVE, (%)</td>
<td align="center" valign="middle">52 a 72%</td>
<td align="center" valign="middle">54 a 74%</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">MVE, (g)</td>
<td align="center" valign="middle">88 a 224</td>
<td align="center" valign="middle">67 a 162</td>
</tr>
<tr>
<td align="left" valign="middle">DBVD, (mm)</td>
<td align="center" valign="middle">25 a 41</td>
<td align="center" valign="middle">25 a 41</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">TAPSE, (mm)</td>
<td align="center" valign="middle">≥ 17</td>
<td align="center" valign="middle">≥ 17</td>
</tr>
<tr>
<td align="left" valign="middle">SLGVE, (%)</td>
<td align="center" valign="middle">&gt; 18%</td>
<td align="center" valign="middle">&gt; 18%</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">SLGVD, (%)</td>
<td align="center" valign="middle">&gt; 20%</td>
<td align="center" valign="middle">&gt; 20%</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="TFN7"><p>DBVD: diâmetro basal do ventrículo direito; DDVE: diâmetro diastólico do ventrículo esquerdo; DSVE: diâmetro sistólico do ventrículo esquerdo; FEVE: fração de ejeção do ventrículo esquerdo; MVE: massa do ventrículo esquerdo; PPVE: parede posterior do ventrículo esquerdo; SLGVD: strain longitudinal global do ventrículo direito; SLGVE: strain longitudinal global do ventrículo esquerdo; SIV: espessura do septo interventricular; TAPSE: excursão sistólica do plano do ânulo tricúspide.</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec>
<title>TC de tórax</title>
<p>Os pacientes foram submetidos à avaliação por TC pulmonar nas primeiras 48 horas de internação, utilizando-se tomógrafo de 16 canais Toshiba Alexion. Além disso, suas imagens foram processadas para avaliação em um sistema de relatórios K-Pacs. Utilizou-se o consenso multinacional da Fleischner Society<sup><xref ref-type="bibr" rid="B18">18</xref></sup> onde um radiologista experiente realizou as análises, classificando o acometimento pulmonar nesses pacientes em leve (envolvimento pulmonar &lt; 25%), moderado (envolvimento pulmonar entre 25% e 50%) e grave (envolvimento pulmonar &gt; 50%).</p>
</sec>
<sec>
<title>Análise estatística</title>
<p>Variáveis ecocardiográficas, tomográficas, clínicas e epidemiológicas foram analisadas quanto à normalidade de sua distribuição com o teste de Kolmogorov-Smirnov. Como todos os dados apresentavam distribuição normal, variáveis contínuas foram apresentadas como média ± desvio padrão e variáveis categóricas foram relatadas como proporções.</p>
<p>As variáveis dos pacientes que receberam alta (grupo alta) ou falecido (grupo óbito) foram comparadas pelo teste t de Student não-pareado, bicaudal (variáveis contínuas) ou pelo teste do qui-quadrado (variáveis categóricas), ou seus equivalentes não paramétricos, quando aplicável.</p>
<p>As suposições do modelo de Cox foram verificadas, incluindo a proporcionalidade dos riscos, que foi confirmada por meio do teste de Schoenfeld (p &gt; 0,05) e gráficos de resíduos. Não houve indicação de multicolinearidade (VIF &lt; 10 para todas as covariáveis) e o tamanho amostral foi considerado suficiente, com um número adequado de eventos para cada covariável. Assim, prosseguimos com a análise do poder prognóstico independente de cada variável estudada através da construção de vários modelos de análise de regressão de Cox.</p>
<p>As variáveis ecocardiográficas que mantiveram seu poder prognóstico independente na análise de regressão de Cox foram utilizadas para a construção de curvas ROC (<italic>receiver operating characteristic</italic>), utilizando a mortalidade hospitalar como desfecho. A partir daí, foram calculados os pontos de corte e sua sensibilidade, especificidade e área sob a curva para cada um desses parâmetros. A melhor relação entre sensibilidade e especificidade definiu o ponto de corte das variáveis para construção da curva de sobrevida de Kaplan-Meier.</p>
<p>Um p-valor bicaudal &lt; 0,05 foi considerado significativo. Todas as análises estatísticas foram realizadas utilizando o software STATA 14.2 (StataCorp, Texas, EUA).</p>
</sec>
</sec>
<sec sec-type="results">
<title>Resultados</title>
<p>No período de 28 de março a 30 de dezembro de 2020, foram analisados 174 pacientes internados na UTI do HGNI. Destes, 24 pacientes não apresentavam imagem ecocardiográfica adequada para o estudo da deformação miocárdica, correspondendo a 13,8% do total. A taxa de mortalidade intra-hospitalar entre os pacientes incluídos no estudo foi alta (64%), como demonstrado na <xref ref-type="fig" rid="f7">Figura 1</xref>.</p>
<fig id="f7">
<label>Figura 1</label>
<caption><title>Fluxograma dos pacientes incluídos no estudo. UTI: unidade de terapia intensiva.</title></caption>
<graphic xlink:href="2675-312X-abcimg-37-04-e20240067-gf02-pt.tif"/>
</fig>
<sec>
<title>Dados demográficos, TC e presença de comorbidades</title>
<p>Entre os 150 pacientes incluídos neste estudo, conforme descrito na <xref ref-type="table" rid="t8">Tabela 3</xref>, a média de idade foi de 56 ± 14 anos, sendo 77 (51,3%) do sexo masculino. A maioria (77,3%) dos pacientes apresentou mais de 50% de comprometimento pulmonar. Em relação às comorbidades, a hipertensão arterial foi a mais prevalente (84%), seguida da obesidade (41,3%) e do DM (34%).</p>
<table-wrap id="t8">
<label>Tabela 3</label>
<caption><title>Dados demográficos, presença de comorbidades e acometimento pulmonar dos pacientes incluídos no estudo</title></caption>
<table frame="hsides" rules="groups">
<colgroup width="20%">
<col/>
<col/>
<col/>
<col/>
<col/>
</colgroup>
<thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
<tr style="background-color:#C58874">
<th align="left" valign="middle">Parâmetro</th>
<th align="center" valign="middle">Total de pacientes (n = 150)</th>
<th align="center" valign="middle">Pacientes em alta</th>
<th align="center" valign="middle">Pacientes em óbito</th>
<th align="center" valign="middle">p-valor</th>
</tr>
</thead>
<tbody style="border-bottom: thin solid; border-color: #000000">
<tr>
<td align="left" valign="middle">Idade (anos)</td>
<td align="center" valign="middle">56 ±14</td>
<td align="center" valign="middle">50±12</td>
<td align="center" valign="middle">59±15</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">Sexo masculino [n (%)]</td>
<td align="center" valign="middle">77 (51,3%)</td>
<td align="center" valign="middle">30 (56%)</td>
<td align="center" valign="middle">47 (49%)</td>
<td align="center" valign="middle">0,44</td>
</tr>
<tr>
<td align="left" valign="middle">Comprometimento pulmonar &gt; 50% na TC [n (%)]</td>
<td align="center" valign="middle">116 (77,3%)</td>
<td align="center" valign="middle">26 (48%)</td>
<td align="center" valign="middle">90 (94%)</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">Obesidade [n (%)]</td>
<td align="center" valign="middle">62 (41,3%)</td>
<td align="center" valign="middle">13 (24%)</td>
<td align="center" valign="middle">49 (51%)</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
<tr>
<td align="left" valign="middle">Hipertensão [n (%)]</td>
<td align="center" valign="middle">126 (84,0%)</td>
<td align="center" valign="middle">36 (67%)</td>
<td align="center" valign="middle">90 (94%)</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">DM [n (%)]</td>
<td align="center" valign="middle">51 (34,0%)</td>
<td align="center" valign="middle">4 (7%)</td>
<td align="center" valign="middle">47 (49%)</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="TFN8"><p>TC: tomografia computadorizada; DM: diabetes mellitus.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>Os pacientes que sucumbiram apresentaram maior média de idade (59 ± 15 versus 50 ± 12 anos, p &lt; 0,001) e mais comorbidades em relação aos que receberam alta (<xref ref-type="table" rid="t8">Tabela 3</xref>). Uma clara diferença na idade e comorbidades foi observada quando os dois grupos foram comparados na análise univariada (<xref ref-type="table" rid="t8">Tabela 3</xref>). Entretanto, após análise de regressão multivariada dos parâmetros demográficos, apenas a presença de mais de 50% de acometimento pulmonar na tomografia permaneceu como preditor independente de mortalidade hospitalar (<xref ref-type="fig" rid="f8">Figura 2</xref>).</p>
<fig id="f8">
<label>Figura 2</label>
<caption><title>Análise de regressão multivariada de Cox referente aos parâmetros demográficos, acometimento pulmonar na TC e presença de comorbidades, considerando o desfecho óbito intra-hospitalar.</title></caption>
<graphic xlink:href="2675-312X-abcimg-37-04-e20240067-gf03-pt.tif"/>
</fig>
</sec>
<sec>
<title>Parâmetros ecocardiográficos</title>
<p>Os pacientes que foram a óbito apresentaram maiores dimensões ventriculares e menor FEVE em relação aos pacientes que receberam alta (<xref ref-type="table" rid="t9">Tabela 4</xref>). Apenas 36% dos pacientes que morreram tinham FEVE anormal, enquanto apenas 2% dos pacientes que receberam alta apresentavam FEVE anormal.</p>
<table-wrap id="t9">
<label>Tabela 4</label>
<caption><title>Parâmetros ecocardiográficos nas primeiras 48 horas de internação na UTI em pacientes com COVID-19 que receberam alta e naqueles que morreram durante a internação</title></caption>
<table frame="hsides" rules="groups">
<colgroup width="25%">
<col/>
<col/>
<col/>
<col/>
</colgroup>
<thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
<tr style="background-color:#C58874">
<th align="left" valign="middle">Parâmetro ecocardiográfico</th>
<th align="center" valign="middle">Pacientes em alta (n = 54)</th>
<th align="center" valign="middle">Pacientes em óbito (n = 96)</th>
<th align="center" valign="middle">p-valor</th>
</tr>
</thead>
<tbody style="border-bottom: thin solid; border-color: #000000">
<tr>
<td align="left" valign="middle">SIV (mm)</td>
<td align="center" valign="middle">8,1 ± 0,8</td>
<td align="center" valign="middle">8,7 ± 1,3</td>
<td align="center" valign="middle">0,009</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">DDVE (mm)</td>
<td align="center" valign="middle">47,2 ± 4,4</td>
<td align="center" valign="middle">50,2 ± 7,8</td>
<td align="center" valign="middle">0,010</td>
</tr>
<tr>
<td align="left" valign="middle">DSVE (mm)</td>
<td align="center" valign="middle">29,8 ± 2,8</td>
<td align="center" valign="middle">35,3 ± 8,7</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">PPVE (mm)</td>
<td align="center" valign="middle">8,2 ± 0,7</td>
<td align="center" valign="middle">8,9 ± 1,4</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
<tr>
<td align="left" valign="middle">FEVE (biplano de Simpson, %)</td>
<td align="center" valign="middle">66 ± 4</td>
<td align="center" valign="middle">57 ± 12</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">Onda E (cm/s)</td>
<td align="center" valign="middle">0,7 ± 0,2</td>
<td align="center" valign="middle">0,6 ± 0,2</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
<tr>
<td align="left" valign="middle">Onda A (cm/s)</td>
<td align="center" valign="middle">0,7 ± 0,2</td>
<td align="center" valign="middle">0,7 ± 0,2</td>
<td align="center" valign="middle">0,36</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">MVE (g)</td>
<td align="center" valign="middle">161,2 ± 36,5</td>
<td align="center" valign="middle">195,7 ± 63,0</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
<tr>
<td align="left" valign="middle">Relação E/A</td>
<td align="center" valign="middle">1,1 ± 0,4</td>
<td align="center" valign="middle">0,9 ± 0,6</td>
<td align="center" valign="middle">0,032</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">DBVD (mm)</td>
<td align="center" valign="middle">32,3 ± 3,0</td>
<td align="center" valign="middle">37,2 ± 6,1</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
<tr>
<td align="left" valign="middle">PSAP (mmHg)</td>
<td align="center" valign="middle">23,6 ± 4,0</td>
<td align="center" valign="middle">34,0 ± 10,8</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">TAPSE (mm)</td>
<td align="center" valign="middle">22,2 ± 2,3</td>
<td align="center" valign="middle">19,4 ± 3,2</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="TFN9"><p>DBVD: diâmetro basal do ventrículo direito; DDVE: diâmetro diastólico do ventrículo esquerdo; DSVE: diâmetro sistólico do ventrículo esquerdo; FEVE: fração de ejeção do ventrículo esquerdo; MVE: massa ventricular esquerda; PPVE: espessura da parede posterior do ventrículo esquerdo; PSAP: pressão sistólica arterial pulmonar; SIV: espessura do septo interventricular; TAPSE: excursão sistólica no plano anular tricúspide.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>Considerando um ponto de corte de 40% para FEVE, 16% dos pacientes que foram a óbito apresentaram alteração, enquanto nenhum dos egressos apresentou essa condição (p = 0,002) (<xref ref-type="table" rid="t10">Tabela 5</xref>).</p>
<table-wrap id="t10">
<label>Tabela 5</label>
<caption><title>Frequência de parâmetros ecocardiográficos alterados nas primeiras 48 horas de internação na unidade de terapia intensiva em pacientes com COVID-19 que receberam alta e naqueles que morreram durante a internação</title></caption>
<table frame="hsides" rules="groups">
<colgroup width="25%">
<col/>
<col/>
<col/>
<col/>
</colgroup>
<thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
<tr style="background-color:#C58874">
<th align="left" valign="middle">Parâmetro ecocardiográfico</th>
<th align="center" valign="middle">Pacientes em alta (n=54)</th>
<th align="center" valign="middle">Pacientes em óbito (n=96)</th>
<th align="center" valign="middle">p-valor</th>
</tr>
</thead>
<tbody style="border-bottom: thin solid; border-color: #000000">
<tr>
<td align="left" valign="middle">SIV normal (mm)</td>
<td align="center" valign="middle">54 (100)</td>
<td align="center" valign="middle">94 (98)</td>
<td align="center" valign="middle">0,29</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">DDVE (mm)</td>
<td align="center" valign="middle">53 (98)</td>
<td align="center" valign="middle">71 (74)</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
<tr>
<td align="left" valign="middle">PPVE [n(%)]</td>
<td align="center" valign="middle">54 (100)</td>
<td align="center" valign="middle">91 (95)</td>
<td align="center" valign="middle">0,088</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">FEVE [n(%)]</td>
<td align="center" valign="middle">53 (98%)</td>
<td align="center" valign="middle">67 (70%)</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
<tr>
<td align="left" valign="middle">FEVE &lt; 40% [n(%)]</td>
<td align="center" valign="middle">54 (100%)</td>
<td align="center" valign="middle">81 (84%)</td>
<td align="center" valign="middle">0,002</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">MVE [n(%)]</td>
<td align="center" valign="middle">42 (78)</td>
<td align="center" valign="middle">48 (50)</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
<tr>
<td align="left" valign="middle">Relação E/A [n(%)]</td>
<td align="center" valign="middle">23 (43)</td>
<td align="center" valign="middle">65 (68)</td>
<td align="center" valign="middle">0,003</td>
</tr>
<tr style="background-color:#E8CCBF">
<td align="left" valign="middle">DBVD n(%)]</td>
<td align="center" valign="middle">53 (98)</td>
<td align="center" valign="middle">69 (72)</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
<tr>
<td align="left" valign="middle">PSAP [n(%)]</td>
<td align="center" valign="middle">40 (74)</td>
<td align="center" valign="middle">36 (38)</td>
<td align="center" valign="middle">&lt;0,001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="TFN10"><p>DBVD: diâmetro basal do ventrículo direito; DDVE: diâmetro diastólico do ventrículo esquerdo; FEVE: fração de ejeção do ventrículo esquerdo; MVE: massa ventricular esquerda; PPVE: espessura da parede posterior do ventrículo esquerdo; PSAP: pressão sistólica arterial pulmonar; SIV: espessura do septo interventricular.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>Entre os pacientes que morreram, 30% apresentaram aumento do diâmetro basal do ventrículo direito, em contraste com apenas 1,85% dos pacientes que receberam alta hospitalar que apresentaram o mesmo aumento. Em relação ao DDVE, 26% dos falecidos apresentaram valores elevados para esse parâmetro, enquanto entre os que receberam alta, apenas 3,7% apresentaram aumento do DDVE. Esses dados sugerem uma correlação entre o alargamento dessas medidas e um resultado negativo durante a hospitalização por COVID-19.</p>
<p>A comparação do SLGVE revelou valores menores nos pacientes que morreram em relação aos que receberam alta (15,3 ± 2,3 versus 19,7 ± 1,8, p &lt; 0,001). Da mesma forma, o SLGVD também foi menor nos pacientes que morreram (21,9 ± 4,2 versus 28,0 ± 3,2, p &lt; 0,001).</p>
<p>A análise multivariada de Cox indicou que apenas o SLGVE e mais de 50% de comprometimento tomográfico permaneceram como variáveis preditoras prognósticas independentes (<xref ref-type="fig" rid="f9">Figura 3</xref>). Notadamente, nenhuma das variáveis ecocardiográficas convencionais emergiu como preditora independente de prognóstico após análise multivariada.</p>
<fig id="f9">
<label>Figura 3</label>
<caption><title>Análise de regressão multivariada de Cox referente aos parâmetros do ecocardiograma bidimensional, considerando o desfecho óbito intra-hospitalar. DBVD: diâmetro basal do ventrículo direito; DDVE: diâmetro diastólico do ventrículo esquerdo; DSVE: diâmetro sistólico do ventrículo esquerdo; FEVE: fração de ejeção do ventrículo esquerdo; MVE: massa ventricular esquerda; PP: espessura da parede posterior do ventrículo esquerdo; PSAP: pressão sistólica arterial pulmonar; SIV: espessura do septo interventricular; TAPSE: excursão sistólica no plano anular tricúspide.</title></caption>
<graphic xlink:href="2675-312X-abcimg-37-04-e20240067-gf04-pt.tif"/>
</fig>
<p>O ponto de corte de −18,1 foi utilizado para o SLGVE na construção das curvas de sobrevida intra-hospitalar (p &lt; 0,001; intervalo de confiança 0,53 a 0,23) (<xref ref-type="fig" rid="f10">Figura 4</xref>).</p>
<fig id="f10">
<label>Figura 4</label>
<caption><title>Curva de sobrevida de Kaplan-Meier, de acordo com o SLGVE.</title></caption>
<graphic xlink:href="2675-312X-abcimg-37-04-e20240067-gf05-pt.tif"/>
</fig>
</sec>
</sec>
<sec sec-type="discussion">
<title>Discussão</title>
<p>A partir do momento em que a Ecocardiografia foi pontuada como uma técnica relevante para o manejo de pacientes com COVID-19, inúmeras questões e hipóteses surgiram, levando ao desenvolvimento de uma extensa pesquisa em todo o mundo. Nesse contexto, nosso estudo demonstrou que o SLGVE emergiu como um marcador prognóstico independente em pacientes hospitalizados em UTIs devido à COVID-19.</p>
<p>Com o avanço dessas pesquisas, foram definidas algumas variáveis que teriam uma correlação direta com o desfecho óbito. O estudo ECHOVID-19<sup><xref ref-type="bibr" rid="B19">19</xref></sup> avaliou 214 pacientes com COVID-19 hospitalizados sem critérios de gravidade, fazendo uma análise pareada com 214 pacientes em um grupo controle sem diagnóstico COVID-19. Após excluir pacientes com FEVE &lt; 40%, os autores concluíram que o SLGVE reduzido e TAPSE elevada foram preditores prognósticos com pontos de corte de 16,7% e 24 mm, respectivamente. Essa é uma divergência em relação ao nosso estudo, em que o TAPSE não mostrou poder prognóstico independente, e o ponto de corte para o SLGVE foi fixado em menos de 18,1%. Tal fato indica que não apenas a infecção por COVID-19, mas também a gravidade do paciente no momento da internação e o momento de realização do exame podem influenciar diretamente na análise inicial. Uma revisão sistemática e metanálise<sup><xref ref-type="bibr" rid="B20">20</xref></sup> também avaliou a associação entre TAPSE e mortalidade em pacientes com COVID-19, concluindo que valores mais baixos de TAPSE foram associados a maior mortalidade, com cada redução de ponto percentual resultando em um aumento de 20% na chance de morte. No entanto, um ponto de corte específico não foi fornecido. Além disso, houve variações entre as populações de pacientes utilizadas na metanálise, incluindo grupos ambulatoriais e grupos de pacientes mais críticos, com tempos de admissão e exames variáveis e horários dos exames.</p>
<p>Em abril de 2022, Gomez et al.<sup><xref ref-type="bibr" rid="B21">21</xref></sup> avaliaram preditores ecocardiográficos de mortalidade e morbidade em pacientes críticos com COVID-19, analisando o desfecho de óbito durante um período de hospitalização de 60 dias. Observaram que anormalidades nos parâmetros ecocardiográficos do ventrículo direito influenciavam significativamente o prognóstico dos pacientes. Pacientes com dilatação do ventrículo direito tiveram o dobro do risco de mortalidade em 60 dias devido à COVID-19 e, após análise multivariada, o diâmetro basal do ventrículo direito foi a única variável estatisticamente significativa. Entretanto, o momento dos exames ecocardiográficos não foi especificado em seus métodos, fator importante para o entendimento da análise.</p>
<p>Apesar dos maiores valores de diâmetro da base do ventrículo direito e TAPSE observados nos pacientes que foram a óbito, essas variáveis não demonstraram poder prognóstico independente em nosso estudo. Isso pode ser devido à coleta precoce de dados, dentro de 48 horas após a admissão, significando que esse envolvimento pode não ter se manifestado completamente, reforçando a noção de que alterações ecocardiográficas nas câmaras direitas podem se tornar mais aparentes ao longo da hospitalização. Essa progressão pode indicar piora do quadro, levando a um prognóstico mais desfavorável.</p>
<p>Em estudos que avaliaram a deformação miocárdica do VE em pacientes com COVID-19, Bhatia et al.<sup><xref ref-type="bibr" rid="B22">22</xref></sup> demonstraram que, embora os parâmetros ecocardiográficos convencionais sejam importantes, eles podem não ser suficientes. Nesses estudos, apesar da FEVE normal, os pacientes com maior gravidade apresentaram redução significativa do SLGVE.</p>
<p>Em relação ao uso dos valores de deformação do VE como preditores de mortalidade, Park et al.<sup><xref ref-type="bibr" rid="B23">23</xref></sup> concluíram que um valor de strain do VE de &lt; 13,8% era um preditor independente de mortalidade em pacientes hospitalizados, com sensibilidade de 85% e especificidade de 54%. Era também um forte marcador de sobrevivência. Entretanto, o momento da análise ecocardiográfica neste estudo não foi especificado, o que poderia explicar a diferença em relação aos nossos dados.</p>
<p>Rothschild et al.<sup><xref ref-type="bibr" rid="B24">24</xref></sup> definiram o valor de deformação do VE de 16,6% como preditor de mortalidade e necessidade de intubação em pacientes internados. Um ponto forte deste estudo foi a realização do exame ecocardiográfico transtorácico nas primeiras 24 horas de internação. É comum em estudos encontrarmos correlação entre a presença de disfunção subclínica e valores normais de FEVE por meio da análise ecocardiográfica bidimensional.<sup><xref ref-type="bibr" rid="B23">23</xref>,<xref ref-type="bibr" rid="B24">24</xref></sup></p>
<p>Esses achados corroboram os da presente pesquisa, demonstrando que a avaliação do Strain é de extrema importância na definição da função ventricular e na identificação de pontos de corte de deformação do VE como preditores de mortalidade e curvas de sobrevida.</p>
<p>Em nosso estudo, identificamos que a análise ecocardiográfica pode fornecer diversas variáveis importantes na avaliação de pacientes com COVID-19 grave. No entanto, a alteração no SLGVE foi a única variável ecocardiográfica que poderia prever o prognóstico em pacientes hospitalizados em terapia intensiva com infecção por COVID-19.</p>
<p>A infecção por COVID-19 levantou muitas questões sobre a progressão dos pacientes afetados. Várias patologias têm sido associadas a pior prognóstico, rápida progressão da doença e gravidade geral da doença. No entanto, entender se apenas possuir um fator de risco é indicativo de um curso mais grave da doença tem sido e continua sendo o foco de uma extensa pesquisa.</p>
<p>Neste estudo, observou-se que a prevalência de curso mais agressivo da doença esteve associada à presença de fatores de risco; entretanto, ter algum grau de alteração estrutural ou funcional cardíaca mostrou-se mais relevante do que possuir comorbidades como hipertensão, DM e obesidade ou pertencer a um sexo específico. Mesmo a presença de biomarcadores indicativos de lesão cardíaca foi menos significativa.</p>
<p>Essa linha de raciocínio leva a outra questão: entender que tipo de técnica ecocardiográfica deve ser usada para definir a função do VE em pacientes com COVID-19. Nesse contexto, o uso da ecocardiografia, com análise da deformação miocárdica, surge como opção viável para definir precocemente a presença ou ausência de disfunção miocárdica. Esta aproximação pode então verdadeiramente determinar se um fator de risco isolado está associado a um pior prognóstico de COVID-19.</p>
<sec>
<title>Limitações</title>
<p>Em relação às limitações deste estudo, é importante ressaltar que os pacientes analisados foram admitidos na UTI e, portanto, o grupo de estudo representou casos com evolução mais grave da COVID-19. No entanto, foi possível identificar pacientes com maior gravidade que acabaram sucumbindo à mortalidade intra-hospitalar.</p>
<p>Um dos principais desafios encontrados foi a dificuldade de posicionamento do paciente no leito para obter a angulação necessária para a aquisição ideal das imagens. Esse problema, agravado pelo ambiente caótico causado pela pandemia, levou a exames de imagem inadequados para alguns pacientes. Dificuldades semelhantes na coleta de imagens foram relatadas em UTIs por Croft et al.<sup><xref ref-type="bibr" rid="B25">25</xref></sup> onde 53,7% dos pacientes foram excluídos por apresentarem imagens inadequadas. Além disso, Krishnamoorthy et al.<sup><xref ref-type="bibr" rid="B26">26</xref></sup> excluíram 88,4% de seus pacientes, e Lassen et al.<sup><xref ref-type="bibr" rid="B27">27</xref></sup> tiveram apenas 9,3% de seus pacientes excluídos por imagens inadequadas, embora seus exames tenham sido realizados em regime ambulatorial.</p>
<p>A correlação entre disfunção miocárdica e biomarcadores de lesão cardíaca não pôde ser realizada em todos os pacientes, devido à falta de recursos na unidade para a realização de exames laboratoriais nas primeiras 48 horas de internação. Além disso, a indisponibilidade de outros insumos impossibilitou a análise de outros marcadores como PCR, dímero D e interleucinas, que não foram incluídos no estudo.</p>
<p>Também não foi feita correlação com as drogas utilizadas no tratamento devido à alta divergência de tratamentos na época, por se tratar de um período de aprendizado e experimentação nesse sentido. No entanto, é importante ressaltar que os pesquisadores não interferiram na conduta terapêutica, e todos os pacientes foram tratados de acordo com as melhores práticas disponíveis durante esse período.</p>
<p>A medida da pressão arterial sistólica e diastólica não foi incluída em nossos dados devido à grande variedade de modelos de esfigmomanômetros na unidade. Mesmo que o examinador ecocardiográfico desejasse realizar a medida da pressão no momento do exame, não havia um entendimento universal naquele momento sobre o manuseio e o uso desses dispositivos entre os pacientes.</p>
<p>Dentre todas as dificuldades encontradas, a maior foi, sem dúvida, relacionada ao momento da pesquisa, pois vivíamos sob a sombra da insegurança e incerteza provocadas pela falta de conhecimento, aliadas a um medo constante que dominava o ambiente. Embora motivadas pela necessidade de descoberta e produção de conhecimento para assistir à população, essas condições dificultaram significativamente o processo de pesquisa.</p>
</sec>
</sec>
<sec sec-type="conclusions">
<title>Conclusão</title>
<p>Constatamos que a ecocardiografia bidimensional tem valor limitado para rastreamento de rotina em pacientes hospitalizados com COVID-19, não apresentando variáveis específicas que poderiam contribuir para uma análise prognóstica. Mesmo quando essas variáveis apresentam significância estatística, encontram-se dentro da normalidade, levando a ambiguidades interpretativas.</p>
<p>Neste contexto, o SLGVE apresenta altos níveis de sensibilidade e especificidade, sendo uma ferramenta confiável para avaliação prognóstica em pacientes hospitalizados em estado grave com infecção por COVID-19.</p>
<p>No combate à COVID-19, é fundamental identificar pacientes com maior risco de desenvolver formas graves da doença. Além das comorbidades existentes, a condição prévia de função cardíaca surge como fator decisivo na estratificação de risco. Portanto, uma análise meticulosa é crucial para uma avaliação de risco mais precisa.</p>
</sec>
</body>
<back>
<fn-group>
<fn fn-type="financial-disclosure" id="fn4"><label>Fontes de Financiamento</label><p>O presente estudo não teve fontes de financiamento externas.</p></fn>
<fn fn-type="other" id="fn5"><label>Vinculação Acadêmica</label><p>Este artigo é parte de dissertação de Mestrado de João Giffoni da Silveira Neto pela Universidade Federal Fluminense.</p></fn>
<fn fn-type="other" id="fn6"><label>Aprovação Ética e Consentimento Informado</label><p>Este estudo foi aprovado pela Comissão de Ética em Experimentação Animal da Universidade Iguaçu sob o número de protocolo 39511820.5.0000.8044.</p></fn>
</fn-group>
</back>
</sub-article>
</article>
