2006
DOI: 10.1016/j.ahj.2005.10.011
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How obesity affects the cut-points for B-type natriuretic peptide in the diagnosis of acute heart failure

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Cited by 242 publications
(192 citation statements)
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“…Although exclusion of patients with renal dysfunction in the study by Mahla et al [15] may have decreased the adverse cardiac event rate secondary to a decrease in cardiac clinical risk factors [16], this would not have adversely affected the sensitivity or specificity of the test [1] in their study. Finally, there is an inverse relationship between an increasing body mass index and the optimal discrimination threshold for BNP [19]. This may be an important confounder in vascular patients, as it is well documented that abdominal obesity is an independent predictor of acute MI in medical patients [20].…”
Section: ó 2008 the Authorsmentioning
confidence: 99%
“…Although exclusion of patients with renal dysfunction in the study by Mahla et al [15] may have decreased the adverse cardiac event rate secondary to a decrease in cardiac clinical risk factors [16], this would not have adversely affected the sensitivity or specificity of the test [1] in their study. Finally, there is an inverse relationship between an increasing body mass index and the optimal discrimination threshold for BNP [19]. This may be an important confounder in vascular patients, as it is well documented that abdominal obesity is an independent predictor of acute MI in medical patients [20].…”
Section: ó 2008 the Authorsmentioning
confidence: 99%
“…The mechanisms behind lower circulating BNP levels in obese patients are unclear, but may include decreased production combined with increased clearance of BNP. Nevertheless, some investigators have suggested significantly lower BNP cut-off values in obese patients to indicate the presence of CHF, although there has been no consensus on which levels are appropriate (43).…”
Section: Bnp Versus Nt-probnpmentioning
confidence: 99%
“…Univariable linear regression analysis was performed separately for Caucasians and Asians with NT‐proBNP as the dependent variable. Multivariable adjustment was then performed for factors known to influence NT‐proBNP levels including age, sex, body mass index (BMI), LVEF, New York Heart Association class, previous myocardial infarction, systolic blood pressure, a history of atrial fibrillation, and eGFR 19, 20, 21, 22, 23, 24…”
Section: Methodsmentioning
confidence: 99%