The course of delirium in older long-term care residents

Int J Geriatr Psychiatry. 2012 Dec;27(12):1291-7. doi: 10.1002/gps.3782. Epub 2012 Apr 20.

Abstract

Objective: The purpose of this study was to determine the course of delirium in older long-term care (LTC) residents.

Methods: A prospective cohort study of 279 residents in seven LTC facilities in Montreal and Quebec City, Canada, was conducted. The Mini Mental State Examination (MMSE), Confusion Assessment Method (CAM), Delirium Index (DI), Hierarchic Dementia Scale, Barthel Index, and Cornell Scale for Depression were completed at baseline. The MMSE, CAM, and DI were repeated weekly for 6 months. Information on medical problems and medication was abstracted from resident charts. Data were analyzed using descriptive statistics, Cox proportional hazard regression, and logistic regression.

Results: Of the 279 residents, 41 (14.7%) had 61 CAM-defined incident episodes of delirium: 28 (10%) had one episode and 13 (4.7%) had two or more episodes. Episode duration was 7-63 days, mean, 11.3 (SD, 10.1) days. The mean episode DI score was 11.5 (SD, 3.5). Rates of recovery at 1, 2, 4, and 24 weeks were 57.4%, 67.2% 77.1%, and 80.3%, respectively. Most episodes were preceded or followed by one or more CAM core symptoms of delirium, sometimes lasting many weeks.

Conclusions: Confusion Assessment Method-defined incident episodes of delirium in older LTC residents appear to last longer than episodes in acute care hospital patients, but rates of recovery at 4 and 24 weeks are similar. Notably, most episodes were preceded or followed by one or more CAM core symptoms of delirium. These findings have implications for clinical practice and research in LTC settings.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged, 80 and over
  • Canada / epidemiology
  • Delirium / epidemiology*
  • Delirium / physiopathology
  • Disease Progression
  • Female
  • Humans
  • Incidence
  • Long-Term Care / statistics & numerical data*
  • Male
  • Prospective Studies
  • Regression Analysis