急性肾损伤
重症监护医学
医学
预测建模
梅德林
风险分析(工程)
计算机科学
内科学
机器学习
政治学
法学
作者
Sehoon Park,Hajeong Lee
出处
期刊:Current Opinion in Nephrology and Hypertension
[Ovid Technologies (Wolters Kluwer)]
日期:2019-07-29
卷期号:28 (6): 552-559
被引量:19
标识
DOI:10.1097/mnh.0000000000000536
摘要
Purpose of review Acute kidney injury (AKI) is a critical condition associated with poor patient outcomes. We aimed to review the current concepts and future strategies regarding AKI risk prediction models. Recent findings Recent studies have shown that AKI occurs frequently in patients with common risk factors and certain medical conditions. Prediction models for AKI risk have been reported in medical fields such as critical care medicine, surgery, nephrotoxic agent exposure, and others. However, practical, generalizable, externally validated, and robust AKI prediction models remain relatively rare. Further efforts to develop AKI prediction models based on comprehensive clinical data, artificial intelligence, improved delivery of care, and novel biomarkers may help improve patient outcomes through precise AKI risk prediction. Summary This brief review provides insights for current concepts for AKI prediction model development. In addition, by overviewing the recent AKI prediction models in various medical fields, future strategies to construct advanced AKI prediction models are suggested.
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