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Distinguishing characteristics of delirium in a skilled nursing facility in Spain: Influence of baseline cognitive
José G Franco1,2, Paula T Trzepacz3, Ana M Gaviria1,4
1Hospital Psiquiatric Universitari Institut Pere Mata, IISPV, Universitat Rovira i Virgili, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Reus, Spain.
Objective:
Mild cognitive impairment (MCI) and dementia (DEM) are prevalent in skilled nursing facilities (SNFs), confounding delirium detection. We report characteristics of delirium in an SNF to ascertain distinguishing features for delirium diagnosis, despite challenges of comorbidity with MCI and DEM.
Methods:
Cross-sectional study of 200 consecutive patients from an SNF in Catalunya, Spain, assessed within the first 24 to 48 admission hours by independent experts with Spanish-Informant Questionnaire on Cognitive Decline in the Elderly (for MCI-DEM), Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) delirium criteria, and Delirium Rating Scale Revised-98 (DRS-R98) for delirium phenomenology. Delirium characteristics were modeled in successive steps, according to the presence of delirium and MCI-DEM, with analysis of variance (ANOVA), receiver operator characteristic analyses, and conditional logistic regression.
Results:
The final model produced symptoms that represented each of the three delirium core domains (ie, cognitive, higher order thinking, and circadian). The DRS-R98 items rated these symptoms as moderate-severe attention/vigilance, mild-severe language, and moderate-severe sleep-wake cycle alterations. The delirium discriminant accuracy of the three symptoms together was high: 84.6% in the MCI-DEM group to 92.8% in the No MCI-DEM group.
Conclusions:
Impairments of attention, language, and sleep-wake cycle indicate delirium in SNF patients regardless of the underlying MCI-DEM status. Because delirium is underdetected in SNFs, where nursing staff/patient ratios are low, brief simple tools that measure these symptoms could potentially enhance delirium detection.
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