Potential Targets for Deprescribing in Medically Complex Older Adults with Suspected Cognitive Impairment.
Juliessa M PavonTheodore S Z BerkowitzValerie A SmithJaime M HughesAnna HungSusan N HastingsPublished in: Geriatrics (Basel, Switzerland) (2022)
Deprescribing may be particularly beneficial in patients with medical complexity and suspected cognitive impairment (CI). We describe central nervous system (CNS) medication use and side effects in this population and explore the relationship between anticholinergic burden and sleep. We conducted a cross-sectional analysis of baseline data from a pilot randomized-controlled trial in older adult veterans with medical complexity (Care Assessment Need score > 90), and suspected CI (Telephone Interview for Cognitive Status score 20-31). CNS medication classes included antipsychotics, benzodiazepines, H2-receptor antagonists, hypnotics, opioids, and skeletal muscle relaxants. We also coded anticholinergic-active medications according to their Anticholinergic Cognitive Burden (ACB) score. Other measures included self-reported medication side effects and the Pittsburgh Sleep Quality Index (PSQI). ACB association with sleep (PSQI) was examined using adjusted linear regression. In this sample (N = 40), the mean number of prescribed CNS medications was 2.2 (SD 1.5), 65% experienced ≥ 1 side effect, and 50% had an ACB score ≥ 3 (high anticholinergic exposure). The ACB score ≥ 3 compared to ACB < 3 was not significantly associated with PSQI scores (avg diff in score = -0.1, 95% CI -2.1, 1.8). Although results did not demonstrate a clear relationship with worsened sleep, significant side effects and anticholinergic burden support the deprescribing need in this population.
Keyphrases
- sleep quality
- cognitive impairment
- healthcare
- randomized controlled trial
- physical activity
- skeletal muscle
- pulmonary embolism
- blood brain barrier
- depressive symptoms
- study protocol
- clinical trial
- pain management
- climate change
- middle aged
- electronic health record
- big data
- artificial intelligence
- cerebrospinal fluid
- drug induced