N-terminal pro-brain natriuretic peptide, but not high sensitivity C-reactive protein, improves cardiovascular risk
Michael H Olsen1, Tine W Hansen, Marina K Christensen
1Research Center for Prevention and Health, Department of Clinical Physiology and Nuclear Medicine, Glostrup University Hospital, DK-2600 Glostrup, Denmark. mho@dadlnet.dk
Aim:
Serum N-terminal pro-brain natriuretic peptide (Nt-proBNP), high sensitivity (hs)-C-reactive protein, and urine albumin/creatinine ratio (UACR) are cardiovascular (CV) risk markers in the general population. The aim of this study was to determine whether they predicted CV events independently of established CV risk factors and whether they did so in an additive fashion.
Methods And Results:
In a population-based sample of 2656 individuals, 41, 51, 61, and 71 years old, we measured UACR, serum Nt-proBNP, hs-C-reactive protein, insulin, lipids and plasma glucose, clinic blood pressures, body composition, left ventricular (LV) mass index, and ejection fraction (EF) by echocardiography and pulse wave velocity. During the following 9.4 years, the combined CV endpoint (CEP) of CV death (136), non-fatal stroke, or non-fatal myocardial infarction occurred in 219 subjects. After adjustment for established CV risk factors using Cox-regression analyses, CEP and CV death were predicted by log(Nt-proBNP)/SD [hazard ratio (HR) = 1.58 and HR = 1.80, both P < 0.001] and by log(UACR)/SD (HR = 1.44 and HR = 1.52, both P < 0.001) in an additive fashion, but not by log(hs-C-reactive protein)/SD (HR = 1.17, P = 0.06 and HR = 1.13, NS). CV risk functions were constructed on the basis of Cox-regression analyses. Inclusion of Nt-proBNP and UACR did not increase the area under the receiver-operating characteristic plots.
Conclusion:
Serum Nt-proBNP and UACR, but not hs-C-reactive protein, predicted CV events after adjustment for established CV risk factors including LV EF and relative wall thickness. However, more studies in relevant subgroups are needed before Nt-proBNP and UACR can be recommended for risk prediction in the general population to select subjects for primary prevention.
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