Construction of a risk prediction model for post-CABG acute kidney injury based on clinical data and retrospective analysis of blood purification therapeutic outcomes

Patients undergoing Coronary artery bypass grafting (CABG) surgery often experience acute kidney injury, which dramatically increases mortality and prolongs hospital stays. Our research had two objectives: first, creating a model to predict acute kidney injury (AKI) risk following CABG, and second, investigating how various blood purification techniques influence recovery outcomes. We conducted a retrospective review of 125 CABG cases from our hospital's records (Jan 2018-Dec 2022). Risk factors were determined through logistic regression, allowing us to build a prediction model. We evaluated this model using ROC curves, calibration methods, and internal validation. In a separate analysis, we examined 32 post-CABG patients who developed AKI and received blood purification, comparing the effectiveness of different treatment protocols. Through comprehensive analysis, we identified several independent factors associated with increased risk: advanced age (≥70 years), pre-existing cardiac insufficiency, compromised baseline renal function, diabetes mellitus, surgical procedures of extended duration, prolonged cardiopulmonary bypass (>120 minutes), and intraoperative hypotensive episodes. The predictive framework we developed exhibited excellent discriminatory capacity (AUC=0.81, 95% CI: 0.75-0.87) with appropriate calibration metrics. our findings provide compelling evidence that initiating CRRT early in the treatment course yields substantial benefits over conventional dialysis methods when addressing this severe post-operative complication.