Dataset Information

Prognostic Factors Associated with Acute Heart Failure in Patients Admitted for COVID-19: Analysis of the SEMI-COVID-19 Registry.

ABSTRACT:

Introduction

Since the beginning of the COVID-19 pandemic in March 2020, an intimate relationship between this disease and cardiovascular diseases has been seen. However, few studies assess the development of heart failure during this infection. This study aims to determine the predisposing factors for the development of heart failure (HF) during hospital admission of COVID-19 patients.

Methodology

A retrospective and multicenter study of patients with HF admitted for COVID-19 in 150 Spanish hospitals (SEMI-COVID-19 Registry). A bivariate analysis was performed to relate the different variables evaluated in patients developing heart failure during hospital admission. A multivariate analysis including the most relevant clinical variables obtained in bivariate analyses to predict the outcome of heart failure was performed.

Results

A total of 16.474 patients hospitalized for COVID-19 were included (57.5% men, mean age 67 years), 958 of them (5.8%) developed HF during hospitalization. The risk factors for HF development were: age (odds ratio [OR]): 1.042; confidence interval 95% (CI 95%): 1.035-1.050; p < 0.001), atrial fibrillation (OR: 2.022; CI 95%: 1.697-2.410; p < 0.001), BMI > 30 kg/m² (OR: 1.460 CI 95%: 1.230-1.733; p < 0001), and peripheral vascular disease (OR: 1.564; CI 95%: 1.217-2.201; p < 0.001). Patients who developed HF had a higher rate of mortality (54.1% vs. 19.1%, p < 0.001), intubation rate (OR: 2,36; p < 0.001), and ICU admissions (OR: 2.38; p < 0001).

Conclusions

Patients who presented a higher risk of developing HF were older with cardiovascular risk factors. The risk factors for HF development were age, atrial fibrillation, obesity, and peripheral vascular disease. In addition, patients who developed HF more frequently required to be intubated or admitted to the ICU.

SUBMITTER: Mendez Bailon M

PROVIDER: S-EPMC10380653 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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Publications

Prognostic Factors Associated with Acute Heart Failure in Patients Admitted for COVID-19: Analysis of the SEMI-COVID-19 Registry.

Méndez Bailón Manuel M Lorenzo Villalba Noel N Garcia Onrubia Jorge J Rubio Rivas Manuel M Nuñez Rodriguez Maria Victoria MV de Los Reyes Pascual Pérez María M Díaz Pedroche Carmen C Fonseca Aizpuru Eva María EM Villalba Garcia Maria Victoria MV Garcia Garcia Gema Maria GM Pesqueira Fontán Paula María PM Artero Arturo A Montero Hernandez Esther E Alcalá Pedrajas José Nicolás JN Giner Galvan Vicente V Monge Monge Daniel D Letona Giménez Laura L García Gómez Miriam M Martínez Cilleros Carmen C Puente Ruiz Nuria N Escobar Sevilla Joaquin J Gómez Méndez Raquel R Ramos-Rincón José Manuel JM Gomez Huelgas Ricardo R On Behalf Of The Semi-Covid-Network

Journal of clinical medicine 20230712 14

<h4>Introduction</h4>Since the beginning of the COVID-19 pandemic in March 2020, an intimate relationship between this disease and cardiovascular diseases has been seen. However, few studies assess the development of heart failure during this infection. This study aims to determine the predisposing factors for the development of heart failure (HF) during hospital admission of COVID-19 patients.<h4>Methodology</h4>A retrospective and multicenter study of patients with HF admitted for COVID-19 in ...[more]

PMID: 37510764

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Project description:BackgroundThe assessment of clinical prognosis of pregnant COVID-19 patients at hospital presentation is challenging, due to physiological adaptations during pregnancy. Our aim was to assess the performance of the ABC2-SPH score to predict in-hospital mortality and mechanical ventilation support in pregnant patients with COVID-19, to assess the frequency of adverse pregnancy outcomes, and characteristics of pregnant women who died.MethodsThis multicenter cohort included consecutive pregnant patients with COVID-19 admitted to the participating hospitals, from April/2020 to March/2022. Primary outcomes were in-hospital mortality and the composite outcome of mechanical ventilation support and in-hospital mortality. Secondary endpoints were pregnancy outcomes. The overall discrimination of the model was presented as the area under the receiver operating characteristic curve (AUROC). Overall performance was assessed using the Brier score.ResultsFrom 350 pregnant patients (median age 30 [interquartile range (25.2, 35.0)] years-old]), 11.1% had hypertensive disorders, 19.7% required mechanical ventilation support and 6.0% died. The AUROC for in-hospital mortality and for the composite outcome were 0.809 (95% IC: 0.641-0.944) and 0.704 (95% IC: 0.617-0.792), respectively, with good overall performance (Brier = 0.0384 and 0.1610, respectively). Calibration was good for the prediction of in-hospital mortality, but poor for the composite outcome. Women who died had a median age 4 years-old higher, higher frequency of hypertensive disorders (38.1% vs. 9.4%, p < 0.001) and obesity (28.6% vs. 10.6%, p = 0.025) than those who were discharged alive, and their newborns had lower birth weight (2000 vs. 2813, p = 0.001) and five-minute Apgar score (3.0 vs. 8.0, p < 0.001).ConclusionsThe ABC2-SPH score had good overall performance for in-hospital mortality and the composite outcome mechanical ventilation and in-hospital mortality. Calibration was good for the prediction of in-hospital mortality, but it was poor for the composite outcome. Therefore, the score may be useful to predict in-hospital mortality in pregnant patients with COVID-19, in addition to clinical judgment. Newborns from women who died had lower birth weight and Apgar score than those who were discharged alive.

Dataset Information

Prognostic Factors Associated with Acute Heart Failure in Patients Admitted for COVID-19: Analysis of the SEMI-COVID-19 Registry.

Introduction

Methodology

Results

Conclusions

Publications

Prognostic Factors Associated with Acute Heart Failure in Patients Admitted for COVID-19: Analysis of the SEMI-COVID-19 Registry.

Similar Datasets

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