Preoperative risk prediction models for acute kidney injury after noncardiac surgery: an independent external validation cohort study

医学 急性肾损伤 接收机工作特性 队列 围手术期 肌酐 回顾性队列研究 肾脏疾病 队列研究 急诊医学 内科学 外科 重症监护医学
作者
Xiaohui Zhuo,Shao-Hui Lei,Lingyun Sun,Yongxiao Bai,Jiao Wu,Yong-Jia Zheng,Ke-Xuan Liu,Ke-Xuan Liu,Bing-Cheng Zhao
出处
期刊:BJA: British Journal of Anaesthesia [Elsevier]
标识
DOI:10.1016/j.bja.2024.02.018
摘要

Abstract

Background

Numerous models have been developed to predict acute kidney injury (AKI) after noncardiac surgery, yet there is a lack of independent validation and comparison among them.

Methods

We conducted a systematic literature search to review published risk prediction models for AKI after noncardiac surgery. An independent external validation was performed using a retrospective surgical cohort at a large Chinese hospital from January 2019 to October 2022. The cohort included patients undergoing a wide range of noncardiac surgeries with perioperative creatinine measurements. Postoperative AKI was defined according to the Kidney Disease Improving Global Outcomes creatinine criteria. Model performance was assessed in terms of discrimination (area under the receiver operating characteristic curve, AUROC), calibration (calibration plot), and clinical utility (net benefit), before and after model recalibration through intercept and slope updates. A sensitivity analysis was conducted by including patients without postoperative creatinine measurements in the validation cohort and categorising them as non-AKI cases.

Results

Nine prediction models were evaluated, each with varying clinical and methodological characteristics, including the types of surgical cohorts used for model development, AKI definitions, and predictors. In the validation cohort involving 13,186 patients, 650 (4.9%) developed AKI. Three models demonstrated fair discrimination (AUROC between 0.71 and 0.75); other models had poor or failed discrimination. All models exhibited some miscalibration; five of the nine models were well-calibrated after intercept and slope updates. Decision curve analysis indicated that the three models with fair discrimination consistently provided a positive net benefit after recalibration. The results were confirmed in the sensitivity analysis.

Conclusions

We identified three models with fair discrimination and potential clinical utility after recalibration for assessing the risk of acute kidney injury after noncardiac surgery.
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