Lactate as a predictive biomarker and therapeutic target in cardiopulmonary bypass-associated acute kidney injury.

Elevated lactate is a common metabolic perturbation following cardiopulmonary bypass (CPB). This study evaluates the clinical predictive value of lactate and explores its mechanism involving protein lactylation. Machine learning (ML) algorithms applied to multicenter intensive care databases identified preoperative lactate as a dominant predictor of CPB-acute kidney injury (AKI) risk. To validate these predictions biologically, rat CPB and cellular models were utilized. Experimental results demonstrated that CPB induces glycolytic reprogramming, lactate accumulation, and elevated pan-lysine lactylation. Inhibiting the production of lactate was associated with decreased protein lactylation, lower oxidative stress, and reduced local tissue inflammation, thereby mitigating renal injury. Collectively, our interpretable ML predictive models identify lactate as a top clinical predictor of CPB-AKI, while our experimental data establish the lactate-lactylation axis as a potential mechanistic pathway linking metabolic dysfunction to renal damage. This axis represents a candidate therapeutic target requiring further validation.