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主动脉夹层患者术后谵妄临床预测模型的系统评价OA

Systematic Review of Clinical Prediction Models for Postoperative Delirium in Patients with Aortic Dissection

中文摘要英文摘要

目的 系统评价主动脉夹层患者术后发生谵妄的临床预测模型.方法 检索the Cochrane Li-brary、PubMed、Web of Science、Embase、中国生物医学文献数据库、中国知网、万方数据库以及维普数据库中与主动脉夹层患者术后谵妄风险预测模型相关的研究,检索时限从建库至2025年3月.两名研究人员独立进行文献筛选、数据提取以及纳入研究的偏倚风险评估.结果 最终纳入10项研究,涉及10个主动脉夹层患者术后谵妄临床预测模型.评价结果显示,偏倚风险方面,10项研究均为高风险;适用性方面,1项研究为高风险、6项研究为低风险、3项研究为不清楚.纳入模型曲线下面积为0.771~0.980,标准差为0.005.最常见预测因子包括年龄、肾损伤、深低温停循环持续时间等.结论 主动脉夹层患者术后谵妄临床预测模型的整体预测性能一般,模型偏倚风险较高,临床适用性需进一步验证.

Objective To systematically review clinical prediction models for postoperative delirium in patients with aortic dissection.Methods Studies on risk prediction models for postoperative delirium in patients with aortic dissection were searched in the Cochrane Library,PubMed,Web of Science,Embase,CBMdisc,CNKI,Wanfang Data and VIP from their establishment to March 2025.Two investigators independently performed literature screening,data extraction,and risk of bias assessment for the included studies.Results A total of 10 studies were included,involving 10 clinical prediction models for postoperative delirium in patients with aortic dissection.The review showed that in terms of risk of bias,all 10 studies were rated as high risk;in terms of applicability,1 study was rated at high risk,6 as low risk and 3 as unclear.The area under the curve for the included models was within the range of 0.771-0.980,SD=0.005.The most common predictors included age,renal impairment and duration of deep hypothermic circulatory arrest.Conclusion The clinical prediction models for postoperative delirium in patients with aortic dissection exhibit moderate overall predictive performance and high risk of bias,and require further validation for their clinical applicability.

张美;丁敏;周旻;高键;嵇初敏;成李;虞正红;虞奋

复旦大学附属中山医院,上海 200030复旦大学附属中山医院,上海 200030复旦大学附属中山医院,上海 200030复旦大学附属中山医院,上海 200030复旦大学临床流行病学与循证医学中心,上海 200030复旦大学附属中山医院,上海 200030复旦大学附属中山医院,上海 200030复旦大学附属中山医院,上海 200030

医药卫生

主动脉夹层谵妄预测模型系统评价

Aortic dissectionDeliriumPrediction modelSystematic review

《上海护理》 2026 (1)

39-44,6

国家自然科学基金(82102146)复旦大学附属中山医院重要薄弱学科建设加速康复外科护理亚专科(XK-082-007).

10.3969/j.issn.1009-8399.2026.01.008

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