| spelling |
Maria do Carmo Pereira Nuneshttp://lattes.cnpq.br/7052421532116243Bruno Ramos Nascimentohttp://lattes.cnpq.br/4662677360417544Cecilia Gomez RavettiVinicius Tostes CarvalhoMaria do Carmo Pereira NunesBruno Ramos Nascimentohttp://lattes.cnpq.br/2094505693173831Sander Luis Gomes Pimentel2022-12-29T02:43:36Z2022-12-29T02:43:36Z2022-10-03http://hdl.handle.net/1843/485060000-0001-6597-8323Embora o trato respiratório seja o principal alvo da nova síndrome respiratória aguda grave - coronavírus 2 (SARS-CoV-2), a doença do coronavírus 19 (COVID-19) acomete o sistema cardiovascular em um considerável número de casos, sendo um dos principais determinantes de mortalidade hospitalar. Muitos pacientes com a COVID-19 apresentam doença cardiovascular subjacente ou desenvolvem cardiopatia aguda durante a evolução da doença. As principais manifestações são arritmias, isquemia miocárdica, miocardite e choque. Entretanto, o conhecimento sobre a interação entre a doença cardiovascular e a COVID-19 é limitado. Uma das estratégias para se avaliar o acometimento cardiovascular nos pacientes graves com COVID-19, com alta taxa de infectividade, é a utilização de equipamentos portáteis que permitem a realização de protocolos simplificados de ecocardiografia à beira do leito. Objetivos: identificar os parâmetros ecocardiográficos obtidos por meio da ecocardiografia à beira do leito, preditores de mortalidade intra-hospitalar em pacientes hospitalizados com COVID-19. Métodos: foram incluídos pacientes consecutivos internados em dois hospitais de referência em Belo Horizonte de julho a setembro/2020 com COVID-19 confirmada. O ecocardiograma à beira do leito (GE Vivid-IQ) foi realizado logo após a admissão hospitalar com interpretação remota. A associação entre dados demográficos, comorbidades clínicas e variáveis ecocardiográficas com mortalidade hospitalar foi analisada utilizando-se modelo de regressão logística. Variáveis com valores de p<0,10 na análise univariada foram incluídas no modelo multivariado. Resultados: o total de 163 pacientes foi incluído, com idade de 64±16 anos e 59% eram do sexo masculino; 107 (66%) necessitaram de internação em terapia intensiva. As comorbidades estavam presentes em 144 (88%) pacientes: hipertensão em 115 (71%), diabetes em 61 (37%) e insuficiência cardíaca em 22 (14%). A mortalidade intra-hospitalar foi de 34% (n=56). Na análise univariada, as variáveis ecocardiográficas significativamente associadas ao óbito foram: fração de ejeção do ventrículo esquerdo (FEVE, Odds ratio - OR=0,94), fração de mudança de área do ventrículo direito (FAC-VD, OR=0,96), excursão sistólica do anel tricúspide (TAPSE, OR=0,83) e disfunção do VD (OR=5,3). Na análise multivariada, após ajuste para variáveis clínicas e demográficas, os preditores independentes de mortalidade foram idade (OR=1,05, intervalo de confiança - IC 95% 1,01–1,10, p=0,023), FEVE (OR=0,95, IC 95% 0,91–1,00, p= 0,048) e TAPSE (OR=0,76, IC 95% 0,63-0,91, p=0,005). O modelo final apresentou boa discriminação, com estatística C de 0,78 (IC95% 0,68–0,88). Conclusão: marcadores de disfunção do VD e VE avaliados pelo ecocardiograma à beira do leito foram preditores independentes de mortalidade em pacientes hospitalizados com COVID-19, após ajuste para variáveis clínicas que expressam gravidade da doença.Background: Although the respiratory tract is the main target of the new coronavirus (SARS-CoV-2), disease of coronavirus (COVID-19) affects the cardiovascular system in a considerable number of cases, being one of the main determinants of hospital mortality. Many patients with COVID-19 have underlying cardiovascular disease or develop acute heart disease during the course of the disease. The main manifestations are arrhythmias, myocardial ischemia, myocarditis and shock. However, knowledge about the interaction between cardiovascular disease and COVID-19 is limited. One of the strategies to assess cardiovascular involvement in critically ill patients with COVID-19, with a high infectivity rate, was the use of portable equipment that allows for simplified bedside echocardiography protocols. Objectives: To identify echocardiographic parameters obtained by bedside echocardiography as predictors of in-hospital mortality in hospitalized patients with COVID-19. Methods: Patients admitted in two Reference Hospitals in Brazil between July to Sept/2020 with confirmed COVID-19 and moderate/severe presentations underwent clinical and laboratory evaluation, and focused bedside echo (GE VividIQ), at the earliest convenience, with remote interpretation. The association between demographics, clinical comorbidities and echo variables with all-cause hospital mortality was assessed, and factors significant at p<0.10 were entered into multivariable models. Results: A total of 163 patients were enrolled, mean age was 64±16 years, 59% were men and 107 (66%) were admitted to intensive care. Comorbidities were present in 144 (88%) patients: hypertension 115 (71%), diabetes 61 (37%) and heart failure 22 (14%). In-hospital mortality was 34% (N=56). In univariate analysis, echo variables significantly associated with death were: LV ejection fraction (LVEF, OR=0.94), RV fractional area change (OR=0.96), tricuspid annular plane systolic excursion (TAPSE, OR=0.83) and RV dysfunction (OR=5.3). In multivariate analysis, after adjustment for clinical and demographic variables, independent predictors of mortality were age (OR=1.05, 95%CI 1.01–1.10, p=0.023), LVEF (OR=0.95, 95%CI 0.91–1.00, p=0.048) and TAPSE (OR=0.76, 95%CI 0.63– 0.91, p=0.005). The final model had good discrimination, with C-statistic of 0.78 (95%CI 0.68–0.88). Conclusion: Markers of RV and LV dysfunction assessed by bedside echo are independent predictors of mortality in hospitalized COVID-19 patients, after adjustment for clinical variables.porUniversidade Federal de Minas GeraisPrograma de Pós-Graduação em Ciências Aplicadas à Saúde do AdultoUFMGBrasilhttp://creativecommons.org/licenses/by-nd/3.0/pt/info:eu-repo/semantics/openAccessEcocardiografiaCOVID-19MortalidadeLeitosDoenças CardiovascularesCOVID-19Manifestações CardiovascularesMortalidadeEcocardiogramaEcocardiograma à beira do leitoParâmetros ecocardiográficos preditores de mortalidade intra-hospitalar em pacientes com COVID-19Echocardiographic parameters predictors of in-hospital mortality in patients with COVID-19info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGORIGINALDissertação final Sander Pimentel.pdfDissertação final Sander Pimentel.pdfapplication/pdf6367361https://repositorio.ufmg.br/bitstream/1843/48506/1/Disserta%c3%a7%c3%a3o%20final%20Sander%20Pimentel.pdf975184ffacc355856dfadc57cb5cf289MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://repositorio.ufmg.br/bitstream/1843/48506/2/license_rdf00e5e6a57d5512d202d12cb48704dfd6MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-82118https://repositorio.ufmg.br/bitstream/1843/48506/3/license.txtcda590c95a0b51b4d15f60c9642ca272MD531843/485062022-12-28 23:43:37.224oai:repositorio.ufmg.br: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ório InstitucionalPUBhttps://repositorio.ufmg.br/oaiopendoar:2022-12-29T02:43:37Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
|