Association of N-terminal pro B-type natriuretic peptide (NT-proBNP) change with the risk of atrial fibrillation in the ARIC cohort

ARIC队列中N末端B型利钠肽前体(NT-proBNP)变化与房颤风险的相关性

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Abstract

BACKGROUND: Circulating N-terminal pro B-type natriuretic peptide (NT-proBNP) predicts incidence of atrial fibrillation (AF), but the association of longitudinal changes in NT-proBNP concentrations with incident AF has not been explored. METHODS: We studied 9705 individuals without prevalent AF in 1996-1998 and with available NT-proBNP measurements obtained in samples collected during two visits in 1990-1992 (visit 2) and 1996-1998 (visit 4) in the Atherosclerosis Risk in Communities (ARIC) Study. Participants were followed through the end of 2013. AF was ascertained from electrocardiograms, hospital discharge codes, and death certificates. Multivariable Cox regression was used to evaluate the association of absolute change in log-transformed NT-proBNP [ln(NT-proBNP)] with incident AF. We also assessed the impact of adding ln(NT-proBNP) change as a predictor of AF by difference in the C-statistic and net reclassification improvement (NRI). RESULTS: Over a median follow up of 16 years, there were 1503 incident cases of AF. The means (SD) ln(NT-proBNP) at visit 2 and visit 4 were 3.83 (1.01) and 4.35 (0.94), respectively. There was a 0.52 (0.79) increase in ln(NT-proBNP) over the 6-year period. Greater increases in ln(NT-proBNP) were associated with higher risk of AF [hazard ratio, 2.82 (95% confidence interval 2.34, 3.39), comparing top to bottom quintiles, and 1.74 (1.61, 1.87) per 1-unit increase in ln(NT-proBNP)]. Adding ln(NT-proBNP) change to a model with multiple predictors including baseline NT-proBNP had relatively limited impact in the C-statistic (increase from 0.748, 95%CI 0.736-0.761, to 0.762, 95%CI 0.750, 0.774). Adding ln(NT-proBNP) change to initial predictive models resulted in a categorical NRI of 0.062 (95% CI 0.033, 0.092) and a continuous NRI of 0.092 (95%CI, 0.017, 0.182). CONCLUSION: Positive NT-proBNP change is associated with an increased incidence rate of AF. Adding NT-proBNP change into the prediction model modestly improved incident AF prediction. Future studies should assess the value of monitoring NT-proBNP concentration among individuals at high risk of developing AF.

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