Association of N-terminal pro B-type natriuretic peptide (NT-proBNP) change with the risk of atrial fibrillation in the ARIC cohort
American Heart Journal Jul 23, 2018
Li L, et al. - Researchers investigated the association of longitudinal changes in N-terminal pro B-type natriuretic peptide (NT-proBNP) concentrations with incident atrial fibrillation (AF). They observed an increased incidence rate of AF in relation to positive NT-proBNP change. Modest improvement in incident AF prediction was seen when NT-proBNP change was added into the prediction model.
Methods
- In the Atherosclerosis Risk in Communities (ARIC) Study, researchers examined 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).
- Follow-up was carried out through the end of 2013.
- Using electrocardiograms, hospital discharge codes, and death certificates, they ascertained AF.
- They used multivariable Cox regression to assess the association of absolute change in log-transformed NT-proBNP [ln(NT-proBNP)] with incident AF.
- They also evaluated the influence of adding ln(NT-proBNP) change as a predictor of AF by difference in the C-statistic and net reclassification improvement (NRI).
Results
- A total of 1503 incident cases of AF were reported over a median follow up of 16 years.
- Data showed that the means (SD) ln(NT-proBNP) at visit 2 and visit 4 were 3.83 (1.01) and 4.35 (0.94), respectively.
- Over the 6-year period, a 0.52 (0.79) increase in ln(NT-proBNP) was observed.
- Association of greater increases in ln(NT-proBNP) with higher risk of AF was reported [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)].
- They found that as a result of adding ln(NT-proBNP) change to a model with multiple predictors including baseline NT-proBNP, a relatively limited impact was seen in the C-statistic (increase from 0.748, 95%CI 0.736–0.761, to 0.762, 95%CI 0.750, 0.774).
- Findings revealed that 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).
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