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Sundowning in Patients with Dementia: Identification, Prevalence, and Clinical Correlates
Marco Toccaceli Blasi1, Martina Valletta2, Alessandro Trebbastoni1,3
1Department of Human Neuroscience, "Sapienza" University, Rome, Italy.
Background:
The term sundowning is used to describe the emergence or worsening of neuropsychiatric symptoms in late afternoon or early evening in people with dementia.
Objective:
Our aim was to evaluate sundowning's prevalence and clinical manifestations among patients attending a tertiary memory clinic and to investigate its clinical and neuropsychological correlates.
Methods:
Patients with dementia attending our memory clinic were enrolled in the study. Sundowning was identified through a specifically designed questionnaire. Sociodemographic and clinical features of sundowners and non-sundowners were compared, and a logistic regression was performed to identify the variables associated with the phenomenon. A subgroup of patients underwent a complete neuropsychological assessment.
Results:
Among 184 recruited patients, 39 (21.2%) exhibited sundowning, mostly expressed as agitation (56.4%), irritability (53.8%), and anxiety (46.2%). Sundowners were significantly older, had a later dementia onset, exhibited more severe cognitive and functional impairment, more frequent nocturnal awakenings, and hearing loss relative to non-sundowners. They were also more likely to use anticholinergic medications and antipsychotics, and less likely to use memantine. In a multi-adjusted model, the factors significantly associated with sundowning were the Clinical Dementia Rating score (OR 3.88; 95% CI 1.39-10.90) and the use of memantine (OR 0.20; 95% CI 0.05-0.74). Participants with and without sundowning obtained similar results in single domain neuropsychological tests.
Conclusion:
Sundowning is commonly experienced by patients with dementia and appears as a multiply determined condition. Its presence should always be evaluated in clinical practice and a multidimensional approach should be adopted to identify its predictors.
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