RESULTS
AKI, congenital heart disease, acute kidney injury, SE
REGRESSION, HYPERTENSION, DIABETES MELLITUS
A total of 6106 patients were identified, and 5368 were ultimately included in the present study. The data for 3768 patients were randomly assigned to develop the model, while the data for the remaining 1600 patients were used for validating the model. A summary of the screening results is presented (Supporting Information: Figure Baseline characteristics.
Abbreviations: AKI, acute kidney injury; CABG, coronary artery bypass grafting; CHD, congenital heart disease; COPatients were divided into two groups according to whether persistent AKI occurred. All predictors were compared in the development group. Some variables, such as male gender, hypertension, and postoperative duration of mechanical ventilation, may be potential risk factors for persistent AKI (Supporting Information: Table Multivariate logistic regression analysis of variables for predicting persistent AKI after cardiac surgery.
Abbreviations: AKI, acute kidney injury; CI, confidence interval; CPB, cardiopulmonary bypass; IABP, intra‐aortic balloon pump; MV, mechanical ventilation; OR, odds ratio; SE, standard error.Nomogram for predicting persistent AKI after cardiac surgery. AKI, acute kidney injury; CHD, congenital heart disease; CPB, cardiopulmonary bypass; DM, diabetes mellitus; IABP, intra‐aortic balloon pump; MV, mechanical ventilation.The discrimination and calibration of the model in the development group (Figure Model performance was evaluated using receiver‐operating characteristic and calibration curves. (A) AUC for the model in the development group showing a mean AUC of 0.752 (95% CI: 0.736–0.767). (B) Calibration curve for the new model in the development group. (C) AUC for the model in the validation group showing a mean AUC of 0.761 (95% CI: 0.737–0.784). (D) Calibration curve for the new model in the validation group. Calibration plots show the relationship between the predicted values and actual incidence of persistent AKI. Solid and dotted lines are closely matched, which indicates a more accurate prediction model. AKI, acute kidney injury; AUC, area under the receiver operating characteristic curve.Clinical values for the prediction model with decision curve analyses (DCA). Threshold probability was represented versus the net benefit. Dashed and solid black lines indicated the hypothesis of “all patients” and “no patients with persistent AKI,” respectively. As the curve on the DCA graph approaches the top, the model diagnosis value increases. AKI, acute kidney injury.