预测心脏手术患者术后谵妄风险的Nomogram模型的建立。

IF 2.4 3区 医学 Q2 CARDIAC & CARDIOVASCULAR SYSTEMS
Zikomo Gaudence Kipanga, Zexiang Bao, Marvel Gyeyock Tella, Emmanuel Delali Kofi Fiagbey, Salama Habibu Saad, Bongani Mbambara, Chernor Sulaiman Bah, Asha Khatib Iddi, Rui Ding, Yanna Si, Yuan Zhang, Jianjun Zou
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引用次数: 0

摘要

术后谵妄(POD)是心脏手术后常见且严重的并发症,在老年患者中发病率约为65%。本研究旨在建立≥18岁患者POD的预测模型,以加强早期发现和干预。回顾性分析南京市第一医院(2021年5月- 2022年7月)825例心脏手术患者的资料。采用ICU混淆评定法(CAM-ICU)诊断POD。我们使用LASSO回归和多元逻辑回归来确定nomogram关键预测因子。POD的发生率为23.6%,显著的预测因素包括头部CT表现、拔管前高乳酸血症、APACHE II评分、ASA评分和住院时间。模型具有较强的预测能力(训练AUC: 0.922,验证AUC: 0.896)。开发了一个基于网络的计算器(https://baozexiang.shinyapps.io/dynnomapp/),以加强临床风险评估和患者预后。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of a Nomogram Model to Predict the Risk of Postoperative Delirium in Cardiac Surgery Patients.

Postoperative delirium (POD) is a common and severe complication following cardiac surgery, with an incidence of about 65% in older patients. This study aimed to develop a predictive model for POD in patients aged ≥ 18 years, to enhance early detection and intervention. A retrospective analysis was performed on the data collected from 825 patients who underwent cardiac surgery at Nanjing First Hospital (May 2021-July 2022). POD was diagnosed using the Confusion Assessment Method for the ICU (CAM-ICU). We used LASSO regression and multivariate logistic regression to identify key predictors for the nomogram. The incidence of POD was 23.6%, with significant predictors including head CT findings, hyperlactatemia before extubation, APACHE II score, ASA score, and length of hospital stay. The model demonstrated strong predictive ability (AUC: 0.922 training, 0.896 validation). A web-based calculator ( https://baozexiang.shinyapps.io/dynnomapp/ ) was developed to enhance clinical risk assessment and patient outcomes.

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来源期刊
Journal of Cardiovascular Translational Research
Journal of Cardiovascular Translational Research CARDIAC & CARDIOVASCULAR SYSTEMS-MEDICINE, RESEARCH & EXPERIMENTAL
CiteScore
6.10
自引率
2.90%
发文量
148
审稿时长
6-12 weeks
期刊介绍: Journal of Cardiovascular Translational Research (JCTR) is a premier journal in cardiovascular translational research. JCTR is the journal of choice for authors seeking the broadest audience for emerging technologies, therapies and diagnostics, pre-clinical research, and first-in-man clinical trials. JCTR''s intent is to provide a forum for critical evaluation of the novel cardiovascular science, to showcase important and clinically relevant aspects of the new research, as well as to discuss the impediments that may need to be overcome during the translation to patient care.
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