The Relationship Between Body Mass Index and In-hospital Survival in Patients Admitted With Acute Heart Failure.

Abstract

BackgroundThe association between Body Mass Index (BMI) and clinical outcomes following acute heart failure (AHF) hospitalization is debated in the literature. Our objective was to study the real-world relationship between BMI and in-hospital mortality in patients who were admitted with AHF.MethodsIn this retrospective, multi-center study, we utilized the National Inpatient Sample (NIS) database to identify a sampled cohort of patients who were hospitalized with AHF between October 2015 and December 2016. Outcomes of interest included in-hospital mortality and length of stay (LOS). Patients were divided into 6 BMI (kg/m2) subgroups according to the World Health Organization (WHO) classification: (1) underweight ≤ 19, (2) normal weight 20–25, (3) overweight 26–30, (4) obese I 31–35, (5) obese II 36–39, and (6) extremely obese ≥40. A multivariable logistic regression model was used to identify predictors of in-hospital mortality and to identify predictors of LOS.ResultsA weighted total of 219,950 hospitalizations for AHF across the US were analyzed. The mean age was 66.3 ± 31.5 years and most patients (51.8%) were male. The crude data showed a non-linear complex relationship between BMI and AHF population outcomes. Patients with elevated BMI exhibited significantly lower in-hospital mortality compared to the underweight and normal weight study participants (5.5, 5,5, 2,8, 1.6, 1.4, 1.6% in groups by BMI ≤ 19, 20–25, 26–30, 31–35, 36–39, and, ≥40 respectively, p < 0.001) and shorter LOS. In the multivariable regression model, BMI subgroups of ≤ 25kg/m2 were found to be independent predictors of in-hospital mortality. Age and several comorbidities, and also the Deyo Comorbidity Index, were found to be independent predictors of increased mortality in the study population.ConclusionA reverse J-shaped relationship between BMI and mortality was documented in patients hospitalized for AHF in the recent years confirming the “obesity paradox” in the real-world setting.