Systematic review of prediction models for delirium in the older adult inpatient

Abstract

Objective: To identify existing prognostic delirium prediction models and evaluate their validity and statistical methodology in the older adult (≥60 years) acute hospital population.

Design: Systematic review.

Data sources and methods: 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.

Inclusion criteria: age >60 years, inpatient, developed/validated a prognostic delirium prediction model.

Exclusion criteria: 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.

Results: 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.

Conclusions: 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.

Keywords: delirium; geriatric medicine; statistic.

Figure 1

PRISMA diagram: study selection. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

Figure 2

This displays the CHARMS risk of bias assessment on all included studies. Study participants: design of included study, sampling method and inclusion/exclusion criteria. Predictors: definition, timing and measurement. Outcome: definition, timing and measurement. Sample size and missing data: number of participants in study, events per variable and missing data. Statistical analysis: selection of predictors, internal validation and type of external validation.

Figure 3

This displays the mean frequency of variable use in the 14 externally validated delirium prediction models. ‘(P)’ indicated a precipitating risk factor used in a delirium prediction model. The following variables were used twice and are not represented in the figure: BUN/Cr ratio (Blood Urea Nitrogen/Creatinine ratio), comorbidities, history of delirium, depression, medications (1: upon admission, 1: added during hospital stay), restraint use and malnutrition (1: altered albumin level, 1: malnutrition scale). The following variables were used once and are not represented in the figure: bladder catheter use, C reactive protein, emergency surgery, presence of fracture on admission, history of cerebrovascular accident, iatrogenic event, intensive care unit admission and open surgery.

Figure 4

This shows the published AUROC statistic for the 14 externally validated delirium prediction models. #D/N: number of confirmed delirium in study/overall sample size. DPM: delirium prediction model name. The corresponding number of references the different AUROCs calculated based on different cognitive tests applied to the model by the authors. Squares with error bars: size of square corresponds to sample size of study. AUROC: reported area under the receiver curve statistic, 95% CIs.