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本文引用的文献

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2
Implementation of delirium screening in the emergency department: A qualitative study with early adopters.急诊科谵妄筛查的实施:对早期采用者的定性研究。
J Am Geriatr Soc. 2024 Dec;72(12):3753-3762. doi: 10.1111/jgs.19188. Epub 2024 Sep 12.
3
A Qualitative Study of Emergency Department Delirium Prevention Initiatives.急诊科谵妄预防措施的定性研究
Delirium Commun. 2022;2022. doi: 10.56392/001c.55690. Epub 2022 Dec 6.
4
Boarding Duration in the Emergency Department and Inpatient Delirium and Severe Agitation.急诊科候诊时间与住院期间谵妄及严重躁动
JAMA Netw Open. 2024 Jun 3;7(6):e2416343. doi: 10.1001/jamanetworkopen.2024.16343.
5
Risk factors and risk stratification approaches for delirium screening: A Geriatric Emergency Department Guidelines 2.0 systematic review.谵妄筛查的风险因素和风险分层方法:老年急诊指南 2.0 系统评价。
Acad Emerg Med. 2024 Oct;31(10):969-984. doi: 10.1111/acem.14939. Epub 2024 Jun 7.
6
Delirium detection in the emergency department: A diagnostic accuracy meta-analysis of history, physical examination, laboratory tests, and screening instruments.急诊科谵妄检测:病史、体格检查、实验室检查和筛查工具的诊断准确性荟萃分析。
Acad Emerg Med. 2024 Oct;31(10):1014-1036. doi: 10.1111/acem.14935. Epub 2024 May 16.
7
Delirium and Delirium Prevention in the Emergency Department.急诊科的谵妄与谵妄预防
Clin Geriatr Med. 2023 Nov;39(4):535-551. doi: 10.1016/j.cger.2023.05.006. Epub 2023 Jun 14.
8
Identification of delirium from real-world electronic health record clinical notes.从真实世界电子健康记录临床笔记中识别谵妄。
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9
External validity of an automated delirium prediction model (DEMO) and comparison to the manual VMS-questions: a retrospective cohort study.自动谵妄预测模型 (DEMO) 的外部有效性及与手动 VMS 问题的比较:一项回顾性队列研究。
Int J Clin Pharm. 2023 Oct;45(5):1128-1135. doi: 10.1007/s11096-023-01641-6. Epub 2023 Sep 15.
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Association of delirium with increased short-term mortality among older emergency department patients: A cohort study.谵妄与老年急诊科患者短期死亡率增加的相关性:一项队列研究。
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一种用于识别急诊科谵妄的病历审查方法的验证

Validation of a chart review method for identifying delirium in the emergency department.

作者信息

Thao Piayeng, Carpenter Kayla P, Howick Annelise S, Mullan Aidan F, Boie Madeline A, Maia Ian W, Palmer Allyson K, Southerland Lauren T, Goldberg Elizabeth M, Jeffery Molly M, Bellolio Fernanda

机构信息

Department of Emergency Medicine, Mayo Clinic, Rochester, MN, USA; University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA.

Department of Emergency Medicine, Mayo Clinic, Rochester, MN, USA.

出版信息

Am J Emerg Med. 2025 Jun 16;96:62-68. doi: 10.1016/j.ajem.2025.06.025.

DOI:10.1016/j.ajem.2025.06.025
PMID:40532407
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12354326/
Abstract

OBJECTIVE

To validate the Chart-based Delirium Identification Instrument (CHART-DEL) which was developed in the inpatient setting, for identifying delirium in the emergency department (ED).

METHODS

This retrospective observational study included ED patients aged 75 and older who presented between 2021 and 2023 and were screened for delirium utilizing a validated two-step tool which included the Delirium Triage Screen (DTS) and the Brief Confusion Assessment Method (bCAM). A stratified random sample of 600 medical records were reviewed using the CHART-DEL method. Inter-rater agreement and diagnostic test accuracy were calculated. We followed standardized guidelines for reporting (STROBE).

RESULTS

A total of 27,082 visits were included. Median age was 83 years, 51.8 % were women. Twenty percent of patients had known dementia and/or cognitive impairment, and 48.8 % were admitted to the hospital. There were 1197 patients (4.4 %) with delirium in the ED. When compared to the ED assessment, the chart review correctly identified 474/600 cases (accuracy 79.0 %, 95 % CI: 75.5-82.1 %), including 223/300 with delirium (sensitivity 74.3 %, 95 % CI: 68.9-79.1 %), and 251/300 without delirium (specificity 83.7 %, 95 % CI: 78.9-87.6 %). Agreement between the reviewers was 91.0 %. Weight calculations to approximate the original population resulted in an accuracy of 86.4 % (95 % CI: 86.0-86.8 %), sensitivity of 74.2 % (95 % CI: 71.6-76.6 %) and specificity of 87.0 % (95 % CI: 86.6-87.4 %).

CONCLUSION

The CHART-DEL can be applied to the ED setting, but performed better at correctly identifying patients who do not have delirium. Automating this method could improve retrospective delirium detection in the ED and support future clinical applications of delirium screening tools.

摘要

目的

验证在住院环境中开发的基于图表的谵妄识别工具(CHART-DEL),用于识别急诊科(ED)中的谵妄。

方法

这项回顾性观察研究纳入了2021年至2023年间就诊的75岁及以上的急诊科患者,并使用经过验证的两步法工具进行谵妄筛查,该工具包括谵妄分诊筛查(DTS)和简易意识模糊评估方法(bCAM)。使用CHART-DEL方法对600份病历进行分层随机抽样审查。计算了评分者间一致性和诊断测试准确性。我们遵循标准化报告指南(STROBE)。

结果

共纳入27082次就诊。中位年龄为83岁,51.8%为女性。20%的患者已知患有痴呆和/或认知障碍,48.8%的患者入院治疗。急诊科有1197例患者(4.4%)发生谵妄。与急诊科评估相比,图表审查正确识别了474/600例病例(准确率79.0%,95%CI:75.5-82.1%),包括223/300例谵妄患者(敏感性74.3%,95%CI:68.9-79.1%),以及251/300例无谵妄患者(特异性83.7%,95%CI:78.9-87.6%)。审查者之间的一致性为91.0%。对原始人群进行加权计算得出准确率为86.4%(95%CI:86.0-86.8%),敏感性为74.2%(95%CI:71.6-76.6%),特异性为87.0%(95%CI:86.6-87.4%)。

结论

CHART-DEL可应用于急诊科环境,但在正确识别无谵妄患者方面表现更好。将此方法自动化可改善急诊科谵妄的回顾性检测,并支持谵妄筛查工具未来的临床应用。