BACKGROUND: BNP and N-terminal proBNP (NT-proBNP) concentrations may be depressed in patients with increased body mass index (BMI). Whether increased BMI affects accuracy of these biomarkers for diagnosing decompensated heart failure (HF) and predicting outcomes is unknown. METHODS: We measured BNP and NT-proBNP in 685 patients with possible decompensated HF in a free-living community population subdivided by BMI as obese, overweight, and normal weight. HF diagnosis was adjudicated by a cardiologist blinded to BNP and NT-proBNP results. We tabulated all-cause mortality over a median follow-up of 401 days and assessed marker accuracy for HF diagnosis and mortality by ROC analysis. RESULTS: Of the 685 patients, 40.9% were obese (n = 280), 28.2% were overweight (n = 193), and 30.9% had normal BMI (n = 212). Obese patients had lower BNP and NT-proBNP compared with overweight or normal-weight individuals (P < 0.001) and decreased mortality compared with normal-weight individuals (P < 0.001). Both biomarkers added significantly to a multivariate logistic regression model for diagnosis of decompensated HF across BMI categories. NT-proBNP outperformed BNP for predicting all-cause mortality in normal-weight individuals (chi(2) for BNP = 6.4, P = 0.09; chi(2) for NT-proBNP = 16.5, P < 0.001). Multivariate regression showed that both biomarkers remained significant predictors of decompensated HF diagnosis in each BMI subgroup. CONCLUSIONS: In this study population, obese patients had significantly lower BNP and NT-proBNP that reflected lower mortality. BNP and NT-proBNP can be used in all BMI groups for decompensated HF diagnosis, although BMI-specific cutpoints may be necessary to optimize sensitivity.
BACKGROUND:BNP and N-terminal proBNP (NT-proBNP) concentrations may be depressed in patients with increased body mass index (BMI). Whether increased BMI affects accuracy of these biomarkers for diagnosing decompensated heart failure (HF) and predicting outcomes is unknown. METHODS: We measured BNP and NT-proBNP in 685 patients with possible decompensated HF in a free-living community population subdivided by BMI as obese, overweight, and normal weight. HF diagnosis was adjudicated by a cardiologist blinded to BNP and NT-proBNP results. We tabulated all-cause mortality over a median follow-up of 401 days and assessed marker accuracy for HF diagnosis and mortality by ROC analysis. RESULTS: Of the 685 patients, 40.9% were obese (n = 280), 28.2% were overweight (n = 193), and 30.9% had normal BMI (n = 212). Obesepatients had lower BNP and NT-proBNP compared with overweight or normal-weight individuals (P < 0.001) and decreased mortality compared with normal-weight individuals (P < 0.001). Both biomarkers added significantly to a multivariate logistic regression model for diagnosis of decompensated HF across BMI categories. NT-proBNP outperformed BNP for predicting all-cause mortality in normal-weight individuals (chi(2) for BNP = 6.4, P = 0.09; chi(2) for NT-proBNP = 16.5, P < 0.001). Multivariate regression showed that both biomarkers remained significant predictors of decompensated HF diagnosis in each BMI subgroup. CONCLUSIONS: In this study population, obesepatients had significantly lower BNP and NT-proBNP that reflected lower mortality. BNP and NT-proBNP can be used in all BMI groups for decompensated HF diagnosis, although BMI-specific cutpoints may be necessary to optimize sensitivity.
Authors: Ronald A Booth; Stephen A Hill; Andrew Don-Wauchope; P Lina Santaguida; Mark Oremus; Robert McKelvie; Cynthia Balion; Judy A Brown; Usman Ali; Amy Bustamam; Nazmul Sohel; Parminder Raina Journal: Heart Fail Rev Date: 2014-08 Impact factor: 4.214
Authors: Zyad T Saleh; Terry A Lennie; Muhammad Darawad; Hamza Alduraidi; Rami A Elshatarat; Issa M Almansour; Debra K Moser Journal: Heart Lung Date: 2020-06-05 Impact factor: 2.210
Authors: Janine Wirth; Brian Buijsse; Romina di Giuseppe; Andreas Fritsche; Hans W Hense; Sabine Westphal; Berend Isermann; Heiner Boeing; Cornelia Weikert Journal: PLoS One Date: 2014-11-25 Impact factor: 3.240