A model for predicting AKI after cardiopulmonary bypass surgery in Chinese patients with normal preoperative renal function.

IF 1.6 3区 医学 Q2 SURGERY
Xuan Lin, Li Xiao, Weibin Lin, Dahui Wang, Kangqing Xu, Liting Kuang
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引用次数: 0

Abstract

Objective: To develop and validate a predictive model for acute kidney injury (AKI) after cardiopulmonary bypass (CPB) surgery in Chinese patients with normal preoperative renal function.

Method: From January 1, 2015, to September 1, 2022, a total of 1003 patients were included in the analysis as a development cohort. We used the ratio of 7:3 to divide the patients into a training group (n = 703) and a testing group (n = 300). In addition, a total of 178 patients were collected as an external validation cohort from January 1, 2023, to May 1, 2023. In the training group, independent risk factors for postoperative AKI were identified through the least absolute shrinkage and selection operator (LASSO) regression and multifactor logistic regression analysis. A nomogram predictive model was then established. The area under the curve (AUC) of receiver operating characteristic (ROC) curve, as well as calibration curve and decision curve, were used for validation of the model.

Results: Age, body mass index (BMI), emergent surgery, CPB time, intraoperative use of adrenaline, and postoperative procalcitonin (PCT) were identified as important risk factors for AKI after CPB surgery (P < 0.05). The nomogram predictive model demonstrated good discrimination (AUC: 0.772 (95%CI: 0.735 - 0.809), 0.780 (95% CI: 0.724 - 0.835), and 0.798 (95% CI: 0.731 - 0.865)), calibration (Hosmer and Lemeshow goodness of fit test: P-value 0.6941, 0.9539, and 0.2358), and clinical utility (the threshold probability values in the decision curves are respectively > 12%, > 10%, and 16% ~ 75%) in the training, testing, and external validation groups.

Conclusion: The predictive model, which was established in Chinese patients with normal preoperative renal function, has high accuracy, calibration, and clinical utility. Clinicians can utilize this model to predict and potentially reduce the incidence of AKI after CPB surgery in the Chinese population.

预测中国术前肾功能正常患者体外循环术后AKI的模型。
目的:建立并验证中国术前肾功能正常的体外循环(CPB)术后急性肾损伤(AKI)预测模型。方法:2015年1月1日至2022年9月1日,共1003例患者作为发展队列纳入分析。我们采用7:3的比例将患者分为训练组(n = 703)和试验组(n = 300)。此外,从2023年1月1日至2023年5月1日,共收集178例患者作为外部验证队列。在训练组中,通过最小绝对收缩和选择算子(LASSO)回归和多因素logistic回归分析确定术后AKI的独立危险因素。建立了nomogram预测模型。采用受试者工作特征曲线(ROC)曲线下面积(AUC)、校正曲线和决策曲线对模型进行验证。结果:年龄、体重指数(BMI)、急诊手术、CPB时间、术中肾上腺素使用、术后降钙素原(PCT)是CPB术后AKI发生的重要危险因素(P值为12%,P值为10%,P值为16% ~ 75%)。结论:在中国术前肾功能正常患者中建立的预测模型具有较高的准确性、可校准性和临床实用性。临床医生可以利用该模型预测并潜在地降低中国人群CPB手术后AKI的发生率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Surgery
BMC Surgery SURGERY-
CiteScore
2.90
自引率
5.30%
发文量
391
审稿时长
58 days
期刊介绍: BMC Surgery is an open access, peer-reviewed journal that considers articles on surgical research, training, and practice.
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