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基于网络的术后急性肾损伤预测模型的建立与验证

Development and Validation of a Web-Based Prediction Model for AKI after Surgery.

机构信息

Division of Hospital Medicine, Department of Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania.

Division of Nephrology, Department of Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania.

出版信息

Kidney360. 2020 Dec 29;2(2):215-223. doi: 10.34067/KID.0004732020. eCollection 2021 Feb 25.

Abstract

BACKGROUND

AKI after surgery is associated with high mortality and morbidity. The purpose of this study is to develop and validate a risk prediction tool for the occurrence of postoperative AKI requiring RRT (AKI-dialysis).

METHODS

This retrospective cohort study had 2,299,502 surgical patients over 2015-2017 from the American College of Surgeons National Surgical Quality Improvement Program Database (ACS NSQIP). Eleven predictors were selected for the predictive model: age, history of congestive heart failure, diabetes, ascites, emergency surgery, hypertension requiring medication, preoperative serum creatinine, hematocrit, sodium, preoperative sepsis, and surgery type. The predictive model was trained using 2015-2016 data (=1,487,724) and further tested using 2017 data (=811,778). A risk model was developed using multivariable logistic regression.

RESULTS

AKI-dialysis occurred in 0.3% (=6853) of patients. The unadjusted 30-day postoperative mortality rate associated with AKI-dialysis was 37.5%. The AKI risk prediction model had high area under the receiver operating characteristic curve (AUC; training cohort: 0.89, test cohort: 0.90) for postoperative AKI-dialysis.

CONCLUSIONS

This model provides a clinically useful bedside predictive tool for postoperative AKI requiring dialysis.

摘要

背景

手术后急性肾损伤(AKI)与高死亡率和高发病率相关。本研究旨在开发和验证一种预测术后需要肾脏替代治疗(AKI-透析)的 AKI 发生风险的工具。

方法

本回顾性队列研究纳入了 2015 年至 2017 年期间美国外科医师学会国家外科质量改进计划数据库(ACS NSQIP)中的 2299502 例手术患者。选择了 11 个预测因素用于预测模型:年龄、充血性心力衰竭史、糖尿病、腹水、急诊手术、需要药物治疗的高血压、术前血清肌酐、血细胞比容、钠、术前脓毒症和手术类型。使用 2015-2016 年的数据(=1487724)对预测模型进行训练,并进一步使用 2017 年的数据(=811778)进行测试。使用多变量逻辑回归开发风险模型。

结果

AKI-透析在 0.3%(=6853)的患者中发生。未调整的 AKI-透析术后 30 天死亡率为 37.5%。AKI 风险预测模型对术后 AKI-透析具有较高的接受者操作特征曲线下面积(AUC;训练队列:0.89,测试队列:0.90)。

结论

该模型为术后需要透析的 AKI 提供了一种具有临床实用价值的床边预测工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fe0/8740985/024f8aa8d7ad/KID.0004732020absf1.jpg

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