Neuropsychiatric Symptom Patterns in Hospice-Eligible Nursing Home Residents with Advanced Dementia
Objective
The purpose of this study was to determine whether specific neuropsychiatric symptom patterns could be identified in a cohort of hospice-eligible nursing home residents with advanced dementia.
Methods
Surrogate decision makers gave informed consent to enroll 123 residents from 3 nursing homes. All participating residents met criteria for hospice eligibility and were determined by direct examination at the time of study enrollment to have advanced dementia. Retrospective medical record review was used to collect data on residents' demographics, diagnoses, and the presence of any neuropsychiatric symptoms during the 6 months prior to study enrollment. Latent class analysis (LCA) was used to classify residents based on neuropsychiatric symptom patterns.
Results
Overall, 85% of residents exhibited one or more neuropsychiatric symptoms. LCA revealed that these individuals could be classified into 3 groups: one with low symptom frequencies (36%) considered to be the normative class, one characterized by psychosis and agitation or aggression (23%), and a third characterized by withdrawal or lethargy (41%).
Conclusions
These results add to the growing understanding of neuropsychiatric symptom patterns in advanced dementia and have implications for more dimensional classification and treatment approaches.
Keywords: Advanced dementia, neuropsychiatric, latent class analysis (LCA), end-of-life
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This research was supported by the National Institute of Neurological Disorders and Stroke, Grant #NS39810. None of the authors have any financial disclosures or conflicts of interest. The first author gratefully acknowledges the support of the Blaustein Postdoctoral Fellowship in Psychiatric Nursing of the Johns Hopkins University School of Nursing and the Johns Hopkins Medical Institution Department of Psychiatry.
PII: S1525-8610(08)00131-X
doi:10.1016/j.jamda.2008.04.008
© 2008 American Medical Directors Association. Published by Elsevier Inc. All rights reserved.
