谵妄
病危
医学
混乱
重症监护室
可预测性
荟萃分析
重症监护医学
重症监护
危重病
内科学
心理学
量子力学
物理
精神分析
作者
Yue Zhang,Dongmei Diao,Hao Zhang,Yongli Gao
摘要
Abstract Background Delirium is the most common psychiatric diagnosis in the intensive care unit (ICU), and 55%‐80% of delirium cases are unrecognized and undocumented the most popular validated instruments available to diagnose delirium for critically ill patients are the Confusion Assessment Method for the ICU (CAM‐ICU). [Correction added on 16 October 2024, after first online publication: The Background section in Abstract has been added in this version.] Aim To identify the validity and predictability of the confusion assessment method for the intensive care unit (CAM‐ICU) for delirium in critically ill patients in the ICU. Study Design In this systematic review, PubMed, Embase, Cochrane Central Register of Controlled Trials, and MEDLINE databases were searched for observational studies investigating delirium screening tools for ICU patients. In the meta‐analysis, we combined the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the curve (AUC) of SROC to analysis the predictive value of CAM‐ICU. Results Twenty‐nine articles met the inclusion criteria. The pooled sensitivity and specificity values were 0.82 (95% confidence interval [CI]: 0.75–0.87) and 0.95 (95% CI: 0.93–0.97), respectively. The AUC point estimate of the SROC curve was 0.96 (95% CI: 0.94–0.97). Race (Asian or Others) could affect the pooled sensitivity and specificity, and the analysis method (Patient‐ or Scan‐based) and study design were not sources of heterogeneity for pooled sensitivity and specificity. Conclusions The CAM‐ICU is a valid and reliable tool for delirium prediction among ICU patients. When introducing CAM‐ICU to assess delirium, it is necessary to localize its language and content to improve its predictive efficacy in different countries and different ethnic groups. Relevance to Clinical Practice In clinical practice, nurses can use CAM‐ICU to evaluate delirium in critically ill patients in ICU. However, it is necessary to debug the language and content according to the application population.
科研通智能强力驱动
Strongly Powered by AbleSci AI