Development and validation of a model for predicting acute kidney injury after cardiac surgery in patients of advanced age

Abstract

Objective To develop a clinical model for predicting postoperative acute kidney injury (AKI) in patients of advanced age undergoing cardiac surgery. Methods A total of 848 patients (aged ≥ 60 years) undergoing cardiac surgery were consecutively enrolled. Among them, 597 were randomly selected for the development set and the remaining 251 for the validation set. AKI was the primary outcome. To develop a model for predicting AKI, visualized as a nomogram, we performed logistic regression with variables selected by Lasso regression analysis. The discrimination, calibration, and clinical usefulness of the new model were assessed and compared with those of Cleveland Clinic score and Simplified Renal Index (SRI) score in the validation set. Results The incidence of AKI was 61.8% in the development set. The new model included seven variables including preoperative serum creatinine, hypertension, preoperative uric acid, New York Heart Association classification ≥ 3, cardiopulmonary bypass time > 120 min, intraoperative red blood cell transfusion, and postoperative prolonged mechanical ventilation. In the validation set, the areas under the receiver operating characteristic curves for assessing discrimination of the new model, Cleveland Clinic score, and SRI score were 0.801, 0.670, and 0.627, respectively. Compared with the other two scores, the new model presented excellent calibration according to the calibration curves. Decision curve analysis presented the new model was more clinically useful than the other two scores. Conclusions We developed and validated a new model for predicting AKI after cardiac surgery in patients of advanced age, which may help clinicians assess patients' risk for AKI.

Development and Validation of a Prediction Model for Survival in Diabetic Patients With Acute Kidney Injury

“…AKI is associated with poor prognosis in patients, including the occurrence of CKD, progression of CKD, prolonged hospital stays, increased adverse cardiovascular events, and mortality ( 28 – 31 ). Previous studies on predictive models of AKI have mainly focused on specific populations of patients with AKI after cardiac surgery ( 32 , 33 ), AKI after non-cardiac surgery ( 34 , 35 ), septic AKI ( 36 , 37 ), tumor-related AKI ( 38 ), and critical AKI ( 39 ). James et al.…”

A new model to predict acute kidney injury after cardiac surgery in patients with renal insufficiency

“…Nomograms have been widely accepted as reliable tools to quantify AKI risk by incorporating and illustrating important factors for AKI [ 23–25 ]. In our study, we built a simple and clear nomogram model, the RRT risks were calculated by adding each point according to different parameters, which was more simple and more practical for clinicians compared to the Cleveland Clinic score and SRI score.…”

In reference to development and validation of a predictive model for acute kidney injury after cardiac surgery in patients of advanced age: Call for methodological issues

“…However, the readers were not provided with the detailed results of the LASSO regression analysis for 60 potential variables. According to the results of bivariate analysis for perioperative variables provided by Hu et al 1 in their table S2, we noted that age, preoperative anemia, proteinuria, the complexity of cardiac surgery (valve + CABG), intraoperative IABP, and postoperative RBC transfusion were significantly different between patients with and without AKI. In the available literature, these variables have been shown as significant predisposing and precipitating factors for the development of AKI after cardiac surgery.…”

“…First, this study only determined the occurrence of AKI based on the Kidney Disease Improving Global Outcomes criteria but did not assess the severity of AKI. That is, this new model designed by Hu et al 1 can predict the risk of AKI occurrence, but has no ability to predict the severity of AKI. In view of the fact that severe AKI has been significantly associated with more and worse postoperative adverse outcomes after cardiac surgery, 2 most available risk scores or models for predicting AKI, such as the Cleveland Clinic score and simplified renal index score, are actually designed for identification of patients at risk of postoperative severe AKI (stages 2 and 3) or renal replacement therapy.…”

“…We have read with great interest the recent article by Hu et al 1 about the development and validation of a predictive model for acute kidney injury (AKI) after cardiac surgery in patients of advanced age.…”