PS-BPC10-2: A NOVEL PREDICTION MODEL OF ACUTE KIDNEY INJURY BASED ON COMBINED BLOOD VARIABLES IN STEMI

Abstract

Background: Development of acute kidney injury (AKI) is associated with poor prognosis in patients with ST-segment elevation myocardial infarction (STEMI). Objective: We sought to investigate whether a combination of pre-procedural blood tests could predict the incidence of AKI in patients with STEMI. Methods: A total of 908 consecutive Japanese patients with STEMI who underwent primary percutaneous coronary intervention within 48 hours of symptom onset were recruited and divided into derivation (n = 617) and validation (n = 291) cohorts. A risk-score model was created based on a combination of parameters assessed on routine blood tests on admission. Results: In the derivation cohort, multivariate analysis showed that the following 4 variables were significantly associated with AKI: blood sugar ≧ 200 mg/dL (odds ratio [OR] 2.07), high-sensitive troponin I > 1.6 ng/mL (upper limit of normal × 50) (OR 2.43), albumin ≧ 3.5 mg/dL (OR 2.85) and estimated glomerular filtration rate < 45 mL/min/1.73 m2 (OR 2.64) (Table 1). Zero to four points were given according to the number of those factors. Incremental risk scores were significantly associated with a higher incidence of AKI in both cohorts (p < 0.001) (Figure 1). Receiver operating characteristic curve analysis of risk models showed adequate discrimination between patients with and without AKI (derivation cohort: area under the curve [AUC] 0.754, 95% confidence interval [CI] 0.733 - 0.846; validation cohort: AUC 0.754, 95% CI 0.644 - 0.839) (Figure 2). Conclusions: Our novel laboratory-based model might be useful for early prediction of the post-procedural risk of AKI in patients with STEMI.