N-terminal fraction of pro-B-type natriuretic peptide versus clinical risk scores for prognostic stratification in chronic systolic heart failure

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Abstract

Background

The Seattle heart failure model or the cardiac and comorbid conditions (3C-HF) scores may help define patient risk in heart failure. Direct comparisons between them or versus N-terminal fraction of pro-B-type natriuretic peptide (NT-proBNP) have never been performed.

Methods

Data from consecutive patients with stable systolic heart failure and 3C-HF data were examined. A subgroup of patients had the Seattle heart failure model data available. The endpoints were one year all-cause or cardiovascular death.

Results

The population included 2023 patients, aged 68 ± 12 years, 75% were men. At the one year time-point, 198 deaths were recorded (10%), 124 of them (63%) from cardiovascular causes. While areas under the curve were not significantly different, NT-proBNP displayed better reclassification capability than the 3C-HF score for the prediction of one year all-cause and cardiovascular death. Adding NT-proBNP to the 3C-HF score resulted in a significant improvement in risk prediction. Among patients with Seattle heart failure model data available (n = 798), the area under the curve values for all-cause and cardiovascular death were similar for the Seattle heart failure model score (0.790 and 0.820), NT-proBNP (0.783 and 0.803), and the 3C-HF score (0.770 and 0.800). The combination of the 3C-HF score and NT-proBNP displayed a similar prognostic performance to the Seattle heart failure model score for both endpoints. Adding NT-proBNP to the Seattle heart failure model score performed better than the Seattle heart failure model alone in terms of reclassification, but not discrimination.

Conclusions

Among systolic heart failure patients, NT-proBNP levels had better reclassification capability for all-cause and cardiovascular death than the 3C-HF score. The inclusion of NT-proBNP to the 3C-HF and Seattle heart failure model score resulted in significantly better risk stratification.

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