Key result
Mathematically estimating discharge BNP from admission BNP by adjusting for age, blood urea nitrogen, and eLVEDP significantly improved prognostic power (p<0.001) and correlated with actual discharge BNP (r=0.625, p<0.05).
Why the study?
Discharge BNP is more predictive of prognosis than admission BNP in heart failure, but the mechanism underlying that difference was not fully elucidated.
Does mathematically estimating discharge BNP from admission parameters improve prognostic power compared to admission BNP alone in patients hospitalized with acute heart failure?
Observational (n=792)
No
Does mathematically estimating discharge BNP from admission parameters improve prognostic power compared to admission BNP alone in patients hospitalized with acute heart failure?
Answers are grounded in this paper and cite their sources.
Estimating discharge BNP levels using admission BNP, age, BUN, and echocardiographic eLVEDP improves the prognostic utility of admission BNP in patients with acute heart failure.
Backgrounds Earlier studies showed that in patients with heart failure (HF), circulating levels of B-type natriuretic peptide (BNP) at hospital discharge (BNP dis ) are more predictive of prognosis than BNP levels on admission (BNP ad ). However, the mechanism underlying that difference has not been fully elucidated. We examined the association between confounding factors during hospitalisation and BNP dis in patients with HF. Methods We identified patients admitted to our hospital for HF (BNP ad ≥100 pg/mL). Estimated left ventricular end-diastolic pressure (eLVEDP) was calculated using echocardiographic data. To identify the factors associated with the relation between BNP ad and BNP dis , we performed a stepwise regression analysis of retrospective data. To validate that analysis, we performed a prospective study. Results Through stepwise regression of the patient data (n=688, New York Heart Association 3–4, 88%), we found age, blood urea nitrogen and eLVEDP to be significantly (p<0.05) associated with BNP dis . Through multivariate analysis after accounting for these factors, we created a formula for predicting BNP levels at discharge ( predicted -BNP dis ) from BNP ad and other parameters measured at admission (p<0.05). By statistically adjusting for these factors, the prognostic power of BNP ad was significantly improved (p<0.001). The prospective study also confirmed the strong correlation between predicted -BNP dis and BNP dis (n=104, r=0.625, p<0.05). Conclusion This study showed that statistically accounting for confounding factors affecting BNP levels improves the predictive power of BNP levels measured at the time of hospital admission, suggesting that these confounding factors are associated with lowering predictive power of BNP on admission. Trial registration number UMIN 000034409, 00035428.
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Anegawa et al. (2021) conducted an observational in Acute heart failure (n=792). Mathematical estimation of discharge BNP adjusting for age, blood urea nitrogen, and estimated left ventricular end-diastolic pressure vs. Unadjusted admission BNP was evaluated on Correlation between predicted discharge BNP and actual discharge BNP (r=0.625, p=<0.05). Mathematically estimating discharge BNP from admission BNP by adjusting for age, blood urea nitrogen, and eLVEDP significantly improved prognostic power (p<0.001) and correlated with actual discharge BNP (r=0.625, p<0.05).
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