Purpose: To establish a risk model for acute kidney injury and subsequent adverse events in Chinese cardiac patients.
Patients and methods: This study included 11,740 patients who had cardiac surgery at 14 institutions in China. Patients were randomly assigned to a derivation cohort (n = 8197) or a validation cohort (n = 3543). Variables ascertained during hospitalization were screened using least absolute shrinkage and selection operator and logistic regression to construct a nomogram model. Model performance was evaluated using C-statistic, calibration curve, and Brier score. The nomogram was further compared with the five conventional models: Mehta score, Ng score, AKICS score, SRI score, and Cleveland Clinic score. Acute kidney injury was defined according to the Kidney Disease Improving Global Outcomes criteria. Subsequent adverse events included mid-term outcomes: death from all causes and major adverse kidney events (defined as composite outcome of death from renal failure, dialysis, and advanced chronic kidney disease).
Results: Acute kidney injury occurred in 3237 (27.6%) patients. The model included 12 predictors. The total score generated from the nomogram ranged from 0 to 556. The nomogram achieved a C-statistic of 0.825 and 0.804 in the derivation and validation cohorts, respectively, and had well-fitted calibration curves. The model performance of the nomogram was better than other five conventional models. After risk stratification, moderate-risk or high-risk groups were associated with significantly higher rates of death from all causes and major adverse kidney events compared with low-risk group during 7-year follow-up.
Conclusion: The nomogram could serve as an effective tool for predicting acute kidney injury and evaluating its subsequent adverse events after cardiac surgery.
Keywords: acute kidney injury; cardiac surgery; nomogram; prediction model.
© 2022 Zhang et al.