A risk score model of contrast-induced acute kidney injury in patients with emergency percutaneous coronary interventions - Yuan, Ying; Qiu, Hong; Hu, Xiaoying; Zhang, Jun; Wu, Yuan; Qiao, Shubin; Yang, Yuejin; Gao, Runlin (Frontiers in Cardiovascular Medicine, 2022)
Background The previously built score models of contrast-induced acute kidney injury (CI-AKI) were principally founded on selective percutaneous coronary intervention (PCI) cases. Our study was to form a risk score model of CI-AKI and make a temporal validation in a population who underwent emergency PCIs. Methods We included patients who underwent emergency PCIs from 2013 to 2018 and divided them into the derivation and validation cohorts. Logistic regression analysis was harnessed to create the risk model. In this research, we defined CI-AKI as an increase in serum creatinine (SCr) ≥0.5 mg/dL (44.2 μmol/L) above baseline within seven days following exposure to contrast medium. Results A total of 3564 patients who underwent emergency PCIs were enrolled and divided into the derivation (2376 cases) and validation cohorts (1188 cases), with CI-AKI incidence of 6.61 and 5.39%, respectively. By logistic analysis, the CI-AKI risk score model was constituted by 8 variables: female (1 point), history of transient ischemic attack (TIA)/stroke (1 point), left ventricular ejection fraction (LVEF) classification (1 point per class), big endothelin-1 (ET-1) classification (1 point per class), estimated glomerular filtration rate (eGFR) classification (1 point per class), intra-aortic balloon pump (IABP) application (1 point), left anterior descending (LAD) stented (1 point), and administration of diuretic (2 points). The patients could be further divided into three groups: low-risk, moderate-risk, and high-risk groups, in accordance with the risk scores of 3–6, 7–10, and ≥11 points, and to the CI-AKI rates of 1.4, 11.9, and 42.6%. The CI-AKI risk score model performed well in discrimination (C statistic = 0.787, 95% CI: 0.731–0.844) and calibration ability, and showed a superior clinical utility. Conclusion We developed a simple CI-AKI risk score model which performs well as a tool for CI-AKI prediction in patients who underwent emergency PCIs.