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Latent class analysis of the multivariate Delirium Index in long-term care settings
Published online by Cambridge University Press: 03 May 2018
Abstract
A few studies examine the time evolution of delirium in long-term care (LTC) settings. In this work, we analyze the multivariate Delirium Index (DI) time evolution in LTC settings.
The multivariate DI was measured weekly for six months in seven LTC facilities, located in Montreal and Quebec City. Data were analyzed using a hidden Markov chain/latent class model (HMC/LC).
The analysis sample included 276 LTC residents. Four ordered latent classes were identified: fairly healthy (low “disorientation” and “memory impairment,” negligible other DI symptoms), moderately ill (low “inattention” and “disorientation,” medium “memory impairment”), clearly sick (low “disorganized thinking” and “altered level of consciousness,” medium “inattention,” “disorientation,” “memory impairment” and “hypoactivity”), and very sick (low “hypoactivity,” medium “altered level of consciousness,” high “inattention,” “disorganized thinking,” “disorientation” and “memory impairment”). Four course types were also identified: stable, improvement, worsening, and non-monotone. Class order was associated with increasing cognitive impairment, frequency of both prevalent/incident delirium and dementia, mortality rate, and decreasing performance in ADL.
Four ordered latent classes and four course types were found in LTC residents. These results are similar to those reported previously in acute care (AC); however, the proportion of very sick residents at enrolment was larger in LTC residents than in AC patients. In clinical settings, these findings could help identify participants with a chronic clinical disorder. Our HMC/LC approach may help understand coexistent disorders, e.g. delirium and dementia.
- Type
- Original Research Article
- Information
- International Psychogeriatrics , Volume 31 , Issue 1: Issue Theme: Parkinson's Disease , January 2019 , pp. 59 - 72
- Copyright
- Copyright © International Psychogeriatric Association 2018
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