Lindroth Heidi, Bratzke Lisa, Purvis Suzanne, Brown Roger, Coburn Mark, Mrkobrada Marko, Chan Matthew T V, Davis Daniel H J, Pandharipande Pratik, Carlsson Cynthia M, Sanders Robert D
Department of Anesthesiology, University of Wisconsin Madison School of Medicine and Public Health, Madison, Wisconsin, USA.
School of Nursing, University of Wisconsin Madison, Madison, Wisconsin, USA.
BMJ Open. 2018 Apr 28;8(4):e019223. doi: 10.1136/bmjopen-2017-019223.
To identify existing prognostic delirium prediction models and evaluate their validity and statistical methodology in the older adult (≥60 years) acute hospital population.
Systematic review.
PubMed, CINAHL, PsychINFO, SocINFO, Cochrane, Web of Science and Embase were searched from 1 January 1990 to 31 December 2016. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses and CHARMS Statement guided protocol development.
age >60 years, inpatient, developed/validated a prognostic delirium prediction model.
alcohol-related delirium, sample size ≤50. The primary performance measures were calibration and discrimination statistics. Two authors independently conducted search and extracted data. The synthesis of data was done by the first author. Disagreement was resolved by the mentoring author.
The initial search resulted in 7,502 studies. Following full-text review of 192 studies, 33 were excluded based on age criteria (<60 years) and 27 met the defined criteria. Twenty-three delirium prediction models were identified, 14 were externally validated and 3 were internally validated. The following populations were represented: 11 medical, 3 medical/surgical and 13 surgical. The assessment of delirium was often non-systematic, resulting in varied incidence. Fourteen models were externally validated with an area under the receiver operating curve range from 0.52 to 0.94. Limitations in design, data collection methods and model metric reporting statistics were identified.
Delirium prediction models for older adults show variable and typically inadequate predictive capabilities. Our review highlights the need for development of robust models to predict delirium in older inpatients. We provide recommendations for the development of such models.
识别现有的谵妄预后预测模型,并评估其在老年(≥60岁)急性医院患者群体中的有效性和统计方法。
系统评价。
检索了1990年1月1日至2016年12月31日期间的PubMed、CINAHL、PsychINFO、SocINFO、Cochrane、科学引文索引和Embase。系统评价和Meta分析的首选报告项目以及CHARMS声明指导了方案制定。
年龄>60岁,住院患者,已开发/验证了谵妄预后预测模型。
酒精相关性谵妄,样本量≤50。主要性能指标为校准和区分统计。两位作者独立进行检索和数据提取。数据合成由第一作者完成。分歧由指导作者解决。
初步检索得到7502项研究。在对192项研究进行全文审查后,根据年龄标准(<60岁)排除了33项,27项符合既定标准。识别出23个谵妄预测模型,14个进行了外部验证,3个进行了内部验证。涉及以下人群:11个内科、3个内科/外科和13个外科。谵妄评估通常不系统,导致发病率各异。14个模型进行了外部验证,受试者工作特征曲线下面积范围为0.52至0.94。确定了设计、数据收集方法和模型指标报告统计方面的局限性。
老年谵妄预测模型显示出可变且通常不足的预测能力。我们的综述强调需要开发强大的模型来预测老年住院患者的谵妄。我们为此类模型的开发提供了建议。