肾脏替代疗法
中止
急性肾损伤
医学
重症监护医学
重症监护室
病危
Lasso(编程语言)
急诊医学
内科学
计算机科学
万维网
作者
Lei Zhong,Jie Min,Jinyu Zhang,Beiping Hu,Caihua Qian
出处
期刊:iScience
[Elsevier]
日期:2024-06-28
卷期号:27 (8): 110397-110397
标识
DOI:10.1016/j.isci.2024.110397
摘要
Continuous renal replacement therapy (CRRT) is a commonly utilized treatment modality for individuals experiencing severe acute kidney injury (AKI). The objective of this research was to construct and assess prognostic models for the timely discontinuation of CRRT in critically ill AKI patients receiving this intervention. Data were collected retrospectively from the MIMIC-IV database (n = 758) for model development and from the intensive care unit (ICU) of Huzhou Central Hospital (n = 320) for model validation. Nine machine learning models were developed by utilizing LASSO regression to select features. In the training set, all models demonstrated an AUROC exceeding 0.75. In the validation set, the XGBoost model exhibited the highest AUROC of 0.798, leading to its selection as the optimal model for the development of an online calculator for clinical applications. The XGBoost model demonstrates significant predictive capabilities in determining the discontinuation of CRRT.
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