| Summary: | Background Previous evidences have been proved that age, N-terminal pro-B-type natriuretic peptide (NT-proBNP), and ejection fraction are tightly associated with the long-term outcomes in patients suffered from coronary artery disease (CAD). Therefore, the present study aimed to assess the prognosis value of age, NT-proBNP, and ejection fraction (ABEF) score in CAD patients who underwent percutaneous coronary intervention (PCI). Methods Observational cohort methodology was used in this study which enrolled totally 3561 patients. And the patients were followed up regularly for 37.59 ± 22.24 months. Patients were classed into three groups based on the tertiles of ABEF sore: first tertile (<5.06, n = 831), second tertile (5.06-6.25, n = 839), and third tertile (≥ 6.25, n = 834). The ABEF score was calculated as follows: age (years)/ejection fraction (%) + NT-proBNP (NT-proBNP<177pg/mL was 1, 177≤NT-proBNP≥524pg/mL was 2 and NT-proBNP > 524pg/mL is 3). The association between ABEF score and adverse prognosis, including all-cause death (ACD), cardiac death (CD), major adverse cardiovascular events (MACEs) and major adverse cardiac and cerebrovascular events (MACCEs), in patients who underwent PCI was analyzed. Results According to the risk category of ABEF score, the incidences of ACD ( P < .001), CD ( P < .001) and MACCEs ( P = .021) among the three groups showed significant differences. Multivariate Cox regression analysis suggested that the respective risks of ACD and CD were increased 3.013 folds (hazard risk [HR] = 4.013 [95% confidence interval [CI]: 1.922-8.378], P < .001) and 4.922 folds ([HR] = 5.922 [95% [CI]: 2.253-15.566], P < .001) in the third tertile compared with those in the first tertile. Kaplan-Meier survival analyses showed that the cumulative risks of ACD,CD and MACCEs in patients with the high ABEF score tended to increase. Conclusion The present study indicated ABEF score was a novel biomarker suitable for predicting adverse prognosis in patients after PCI, which may be used for early recognition and risk stratification.
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