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人工智能预测围手术期发生急性肾损伤患者临床结局的潜力。

The potential for artificial intelligence to predict clinical outcomes in patients who have acquired acute kidney injury during the perioperative period.

作者信息

Kelly Barry J, Chevarria Julio, O'Sullivan Barry, Shorten George

机构信息

Department of Anaesthesiology and Intensive Care Medicine, University College Cork School of Medicine, Cork, Ireland.

Department of Nephrology, University College Cork School of Medicine, Cork, Ireland.

出版信息

Perioper Med (Lond). 2021 Dec 15;10(1):49. doi: 10.1186/s13741-021-00219-y.

Abstract

Acute kidney injury (AKI) is a common medical problem in hospitalised patients worldwide that may result in negative physiological, social and economic consequences. Amongst patients admitted to ICU with AKI, over 40% have had either elective or emergency surgery prior to admission. Predicting outcomes after AKI is difficult and the decision on whom to initiate RRT with a goal of renal recovery or predict a long-term survival benefit still poses a challenge for acute care physicians. With the increasing use of electronic healthcare records, artificial intelligence may allow postoperative AKI prognostication and aid clinical management. Patients will benefit if the data can be readily accessed andregulatory, ethical and human factors challenges can be overcome.

摘要

急性肾损伤(AKI)是全球住院患者中常见的医学问题,可能导致负面的生理、社会和经济后果。在因AKI入住重症监护病房(ICU)的患者中,超过40%在入院前接受过择期或急诊手术。预测AKI后的预后很困难,对于哪些患者启动以肾脏恢复为目标的肾脏替代治疗(RRT)或预测长期生存获益,这一决策对急症科医生来说仍然是一个挑战。随着电子健康记录的使用日益增加,人工智能可能有助于术后AKI的预后评估并辅助临床管理。如果数据能够方便获取且监管、伦理和人为因素方面的挑战能够得到克服,患者将从中受益。

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Guiding Clinical Decisions Through Predictive Risk Rules.通过预测风险规则指导临床决策。
JAMA Netw Open. 2020 Aug 3;3(8):e2013101. doi: 10.1001/jamanetworkopen.2020.13101.
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Perioperative Acute Kidney Injury.围手术期急性肾损伤。
Anesthesiology. 2020 Jan;132(1):180-204. doi: 10.1097/ALN.0000000000002968.

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