Improvements of predictive power of B-type natriuretic peptide on admission by mathematically estimating its discharge levels in hospitalised 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) are more predictive of prognosis than BNP levels on admission (BNP). However, the mechanism underlying that difference has not been fully elucidated. We examined the association between confounding factors during hospitalisation and BNP in patients with HF.

Methods: We identified patients admitted to our hospital for HF (BNP ≥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 and BNP, 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. Through multivariate analysis after accounting for these factors, we created a formula for predicting BNP levels at discharge (-BNP) from BNP and other parameters measured at admission (p<0.05). By statistically adjusting for these factors, the prognostic power of BNP was significantly improved (p<0.001). The prospective study also confirmed the strong correlation between -BNP and BNP (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.