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纳入衰弱因素可改善心脏重症监护病房老年患者谵妄预测模型的性能(D-FRAIL):一项前瞻性推导和外部验证研究。

Inclusion of frailty improved performance of delirium prediction for elderly patients in the cardiac intensive care unit (D-FRAIL): A prospective derivation and external validation study.

作者信息

Guo Rongrong, Zhang Shan, Yu Saiying, Li Xiangyu, Liu Xinju, Shen Yanling, Wei Jinling, Wu Ying

机构信息

School of Nursing, Capital Medical University, Beijing 100069, China.

Cardiac Intensive Care Unit, China-Japan Friendship Hospital, Beijing 100029, China.

出版信息

Int J Nurs Stud. 2023 Nov;147:104582. doi: 10.1016/j.ijnurstu.2023.104582. Epub 2023 Aug 6.

DOI:10.1016/j.ijnurstu.2023.104582
PMID:37672971
Abstract

BACKGROUND

The elderly patients admitted to cardiac intensive care unit (CICU) are at relatively high risk for developing delirium. A simple and reliable predictive model can benefit them from early recognition of delirium followed by timely and appropriate preventive strategies.

OBJECTIVE

To explore the role of frailty in delirium prediction and develop and validate a delirium predictive model including frailty for elderly patients in CICU.

DESIGN

A prospective, observational cohort study.

SETTINGS

CICU at China-Japan Friendship Hospital from March 1, 2022 to August 25, 2022 (derivation cohort); CICU at Beijing Anzhen Hospital affiliated to Capital Medical University from March 14, 2023 to May 8, 2023 (external validation cohort).

PARTICIPANTS

A total of 236 and 90 participants were enrolled in the derivation and external validation cohorts, respectively. Participants in the derivation cohort were assigned into either the delirium (n = 70) or non-delirium group (n = 166) based on the occurrence of delirium.

METHODS

The simplified Chinese version of the Confusion Assessment Method for the Diagnosis of Delirium in the Intensive Care Unit was used to assess delirium twice a day at 8:00-10:00 and 18:00-20:00 until the onset of delirium or discharge from the CICU. Frailty was assessed using the FRAIL scale during the first 24 h in the CICU. Other possible risk factors were collected prospectively through patient interviews and medical records review. After processing missing data via multiple imputations, univariate analysis and bootstrapped forward stepwise logistic regression were performed to select optimal predictors and develop the models. The models were internally validated using bootstrapping and evaluated comprehensively via discrimination, calibration, and clinical utility in both the derivation and external validation cohorts.

RESULTS

The study developed D-FRAIL predictive model using FRAIL score, hearing impairment, Acute Physiology and Chronic Health Evaluation-II score, and fibrinogen. The area under the receiver operating characteristic curve (AUC) was 0.937 (95% confidence interval [CI]: 0.907-0.967) and 0.889 (95%CI: 0.840-0.938) even after bootstrapping in the derivation cohort. Inclusion of frailty was demonstrated to improve the model performance greatly with the AUC increased from 0.851 to 0.937 (p < 0.001). In the external validation cohort, the AUC of D-FRAIL model was 0.866 (95%CI: 0.782-0.907). Calibration plots and decision curve analysis suggested good calibration and clinical utility of the D-FRAIL model in both the derivation and external validation cohorts.

CONCLUSIONS

For elderly patients in the CICU, FRAIL score is an independent delirium predictor and the D-FRAIL model demonstrates superior performance in predicting delirium.

摘要

背景

入住心脏重症监护病房(CICU)的老年患者发生谵妄的风险相对较高。一个简单可靠的预测模型能够使他们受益于对谵妄的早期识别,进而采取及时且恰当的预防策略。

目的

探讨衰弱在谵妄预测中的作用,并开发和验证一个包含衰弱因素的针对CICU老年患者的谵妄预测模型。

设计

一项前瞻性观察性队列研究。

地点

2022年3月1日至2022年8月25日期间中日友好医院的CICU(推导队列);2023年3月14日至2023年5月8日期间首都医科大学附属北京安贞医院的CICU(外部验证队列)。

参与者

推导队列和外部验证队列分别纳入了236名和90名参与者。推导队列中的参与者根据谵妄的发生情况被分为谵妄组(n = 70)或非谵妄组(n = 166)。

方法

使用重症监护病房谵妄诊断的简化中文版意识模糊评估方法,每天8:00 - 10:00和18:00 - 20:00评估谵妄两次,直至谵妄发作或从CICU出院。在入住CICU的最初24小时内使用FRAIL量表评估衰弱情况。通过患者访谈和病历审查前瞻性收集其他可能的危险因素。通过多重填补处理缺失数据后,进行单因素分析和自抽样向前逐步逻辑回归以选择最佳预测因素并开发模型。使用自抽样对模型进行内部验证,并在推导队列和外部验证队列中通过区分度、校准度和临床实用性进行综合评估。

结果

该研究使用FRAIL评分、听力障碍、急性生理与慢性健康状况评分系统II评分和纤维蛋白原开发了D - FRAIL预测模型。在推导队列中,即使经过自抽样,受试者工作特征曲线(AUC)下面积仍为0.937(95%置信区间[CI]:0.907 - 0.967)和0.889(95%CI:0.840 - 0.938)。结果表明纳入衰弱因素极大地改善了模型性能,AUC从0.851增加到0.937(p < 0.001)。在外部验证队列中,D - FRAIL模型的AUC为0.866(95%CI:0.782 - 0.907)。校准图和决策曲线分析表明D - FRAIL模型在推导队列和外部验证队列中均具有良好的校准度和临床实用性。

结论

对于CICU中的老年患者,FRAIL评分是谵妄的独立预测因素,且D - FRAIL模型在预测谵妄方面表现出卓越性能。

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