4.5 Article

Toward personalized risk assessment in patients with chronic heart failure: Detailed temporal patterns of NT-proBNP, troponin T, and CRP in the Bio-SHiFT study

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AMERICAN HEART JOURNAL
卷 196, 期 -, 页码 36-48

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MOSBY-ELSEVIER
DOI: 10.1016/j.ahj.2017.10.008

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  1. Jaap Schouten Foundation
  2. Foreest Medical School

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Background We examined the prognostic information of detailed temporal patterns of N-terminal proBNP (NT-proBNP), high-sensitive troponin T (HsTNT), and C-reactive protein (CRP) in patients with chronic heart failure. Methods The first inclusion round (2011-2013, N = 263) from the ongoing Bio-SHiFT study was used. Biomarkers were measured at baseline and every 3 months. The primary end point (PE) comprised heart failure hospitalization, cardiovascular mortality, cardiac transplantation, and left ventricular assist device implantation. Associations between temporal biomarker patterns and the PE were investigated by joint modeling. Results Mean age was 67 +/- 12 years, 72% were men, 95% had systolic dysfunction, and 73% were in New York Heart Association class I or II. Median follow-up was 2.2 (interquartile range 1.4-2.5) years. We used 2,022 blood samples (median 9 [interquartile range 5-10] per patient), and 70 (27%) patients reached the PE. Temporal patterns of NT-proBNP, HsTNT, and CRP level were associated with the PE (multivariable-adjusted hazard ratio per doubling of biomarker: NT-proBNP 2.28 (95% CI 1.82-2.86), HsTNT 2.05 (1.63-2.58), and CRP 1.65 (1.30-2.08). A combined 3-biomarker model demonstrated independent associations for the temporal patterns of NT-proBNP and CRP level (hazard ratios 2.06 [1.53-2.79] and 1.38 [1.01-1.89], respectively). Instantaneous change in biomarker level was also independently associated with the PE for NT-proBNP and CRP. Long-term biomarker elevation showed an association for NT-proBNP. Conclusions Temporal patterns representing evolution of level and rate of change in level of NT-proBNP and CRP, and long-term elevation of NT-proBNP were independently associated with adverse prognosis in patients with chronic heart failure. Individual patterns of change and combining multiple biomarkers could carry value for prognostication and for therapy guidance.

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