Improvements of predictive power of B-type natriuretic peptide on admission by mathematically estimating its discharge levels in hospitalised patients with acute heart failure. Issue 1 (17th May 2021)

• Record Type: Journal Article
• Authors: Anegawa, Eiji; Takahama, Hiroyuki; Nishimura, Kunihiro; Onozuka, Daisuke; Irie, Yuki; Moriuchi, Kenji; Amano, Masashi; Okada, Atsushi; Amaki, Makoto; Kanzaki, Hideaki; Noguchi, Teruo; Kusano, Kengo; Yasuda, Satoshi; Izumi, Chisato
• Is Part Of: Open heart. Volume 8:Issue 1(2021)
• Publication Date: 2021-05-17
• Subjects: heart failure -- biomarkers -- heart failure -- diastolic -- heart failure -- systolic Pl; Cardiology -- Periodicals; Heart -- Diseases -- Periodicals; Heart -- Diseases -- Patients -- Periodicals; 616.12005
• DOI: 10.1136/openhrt-2021-001603
• Languages: English
• ISSNs: 2398-595X

Abstract

Abstract : Backgrounds: Earlier studies showed that in patients with heart failure (HF), circulating levels of B-type natriuretic peptide (BNP) at hospital discharge (BNPdis ) are more predictive of prognosis than BNP levels on admission (BNPad ). However, the mechanism underlying that difference has not been fully elucidated. We examined the association between confounding factors during hospitalisation and BNPdis in patients with HF. Methods: We identified patients admitted to our hospital for HF (BNPad ≥100 pg/mL). Estimated left ventricular end-diastolic pressure (eLVEDP) was calculated using echocardiographic data. To identify the factors associated with the relation between BNPad and BNPdis, 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 BNPdis . Through multivariate analysis after accounting for these factors, we created a formula for predicting BNP levels at discharge ( predicted -BNPdis ) from BNPad and other parameters measured at admission (p<0.05). By statistically adjusting for these factors, the prognostic power of BNPad was significantly improved (p<0.001). The prospective study also confirmed the strong correlation between predicted -BNPdis and BNPdis (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.