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Background: recognition of prevalent delirium and prediction of incident delirium may be difficult at first assessment. We therefore aimed to validate a pragmatic delirium susceptibility (for any, prevalent and incident delirium) score for use in front-line clinical practice in a consecutive cohort of older acute medicine patients. Methods: consecutive patients aged ≥65 years over two 8-week periods (2010-12) were screened prospectively for delirium using the Confusion Assessment Method (CAM), and delirium was diagnosed using the DSM IV criteria. The delirium susceptibility score was the sum of weighted risk factors derived using pooled data from UK-NICE guidelines: age >80 = 2, cognitive impairment (cognitive score below cut-off/dementia) = 2, severe illness (systemic inflammatory response syndrome) = 1, infection = 1, visual impairment = 1. Score reliability was determined by the area under the receiver operating curve (AUC). Results: among 308 consecutive patients aged ≥65 years (mean age/SD = 81/8 years, 164 (54%) female), AUC was 0.78 (95% CI 0.71-0.84) for any delirium; 0.71 (0.64-0.79), for prevalent delirium; 0.81 (0.70-0.92), for incident delirium; odds ratios (ORs) for risk score 5-7 versus <2 were 17.9 (5.4-60.0), P < 0.0001 for any delirium, 8.1 (2.2-29.7), P = 0.002 for prevalent delirium, and 25.0 (3.0-208.9) P = 0.003 for incident delirium, with corresponding relative risks of 5.4, 4.7 and 13. Higher risk scores were associated with frailty markers, increased care needs and poor outcomes. Conclusions: the externally derived delirium susceptibility score reliably identified prevalent and incident delirium using clinical data routinely available at initial patient assessment and might therefore aid recognition of vulnerability in acute medical admissions early in the acute care pathway.

Original publication

DOI

10.1093/ageing/afw198

Type

Journal article

Journal

Age Ageing

Publication Date

01/03/2017

Volume

46

Pages

226 - 231

Keywords

acute medicine, delirium, external validation, older people, prediction, risk score