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一种用于预测心脏手术后急性肾损伤患者住院不良预后的新模型。

A novel predictive model for poor in-hospital outcomes in patients with acute kidney injury after cardiac surgery.

机构信息

State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Vascular & Cardiology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.

Department of Intensive Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.

出版信息

J Thorac Cardiovasc Surg. 2023 Mar;165(3):1180-1191.e7. doi: 10.1016/j.jtcvs.2021.04.085. Epub 2021 May 11.

Abstract

OBJECTIVE

Patients with cardiac surgery-associated acute kidney injury are at risk of renal replacement therapy and in-hospital death. We aimed to develop and validate a novel predictive model for poor in-hospital outcomes among patients with cardiac surgery-associated acute kidney injury.

METHODS

A total of 196 patients diagnosed with cardiac surgery-associated acute kidney injury were enrolled in this study as the training cohort, and 32 blood cytokines were measured. Least absolute shrinkage and selection operator regression and random forest quantile-classifier were performed to identify the key blood predictors for in-hospital composite outcomes (requiring renal replacement therapy or in-hospital death). The logistic regression model incorporating the selected predictors was validated internally using bootstrapping and externally in an independent cohort (n = 52).

RESULTS

A change in serum creatinine (delta serum creatinine) and interleukin 16 and interleukin 8 were selected as key predictors for composite outcomes. The logistic regression model incorporating interleukin 16, interleukin 8, and delta serum creatinine yielded the optimal performance, with decent discrimination (area under the receiver operating characteristic curve: 0.947; area under the precision-recall curve: 0.809) and excellent calibration (Brier score: 0.056, Hosmer-Lemeshow test P = .651). Application of the model in the validation cohort yielded good discrimination. A nomogram was generated for clinical use, and decision curve analysis demonstrated that the new model adds more net benefit than delta serum creatinine.

CONCLUSIONS

We developed and validated a promising predictive model for in-hospital composite outcomes among patients with cardiac surgery-associated acute kidney injury and demonstrated interleukin-16 and interleukin-8 as useful predictors to improve risk stratification for poor in-hospital outcomes among those with cardiac surgery-associated acute kidney injury.

摘要

目的

心脏手术后发生急性肾损伤的患者存在接受肾脏替代治疗和院内死亡的风险。本研究旨在建立并验证一种用于预测心脏手术后急性肾损伤患者院内不良结局的新模型。

方法

本研究纳入了 196 例心脏手术后急性肾损伤患者作为训练队列,检测了 32 种血液细胞因子。采用最小绝对收缩和选择算子回归和随机森林分位数分类器来识别与院内复合结局(需要肾脏替代治疗或院内死亡)相关的关键血液预测因子。利用Bootstrap 方法对纳入了筛选出的预测因子的逻辑回归模型进行内部验证,并在独立队列(n=52)中进行外部验证。

结果

血清肌酐变化(血清肌酐差值)、白细胞介素 16 和白细胞介素 8 被选为复合结局的关键预测因子。纳入白细胞介素 16、白细胞介素 8 和血清肌酐差值的逻辑回归模型具有最佳性能,具有良好的区分度(受试者工作特征曲线下面积:0.947;精准度-召回曲线下面积:0.809)和优秀的校准度(Brier 评分:0.056,Hosmer-Lemeshow 检验 P=0.651)。该模型在验证队列中的应用也具有良好的区分度。生成了一个列线图用于临床应用,决策曲线分析表明,与血清肌酐差值相比,新模型增加了更多的净获益。

结论

我们建立并验证了一种有前途的用于预测心脏手术后急性肾损伤患者院内复合结局的模型,并证明白细胞介素-16 和白细胞介素-8 是有用的预测因子,可改善心脏手术后急性肾损伤患者的院内不良结局的风险分层。

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