SLEEP

Chekani, Farid; Mirchandani, Kirti; Zaki, Saba; Goswami, Swarnali; Sharma, Manvi

doi: 10.1093/sleep/zsaf003pmid: 39862174

Study ObjectivesThis study assessed the utilization of potentially inappropriate medications (PIM) including oral sedative-hypnotic and atypical antipsychotic (OSHAA), healthcare resource utilization (HCRU), and costs among elderly individuals with insomnia and in the subpopulation with Alzheimer’s disease (AD) who also had a diagnosis of insomnia.MethodsUsing a claims database containing International Classification of Diseases, 10th Revision (ICD-10) codes, the cohort included individuals aged ≥ 65 with incident insomnia (EI, N = 152 969) and AD insomnia subpopulation (ADI, N = 4888). The proportion of patients utilizing atypical antipsychotics or oral sedative-hypnotic medications, namely z-drugs, benzodiazepines, doxepin, dual orexin receptor antagonists (DORAs), and melatonin agonists, were assessed. Inappropriate OSHAA utilization was defined as per the American Geriatrics Society (AGS) Beers criteria. Multivariable models were utilized to compare HCRU and costs between PIM-OSHAA and no PIM-OSHAA groups.ResultsAmong the EI cohort, z-drugs (13.39%) were the most commonly utilized OSHAA, and in the ADI cohort, it was AAPs (29.97%). PIM-OSHAA was utilized by 20% of the EI and 35% of the ADI cohorts. Patients with PIM-OSHAA use among the EI cohort had a higher annualized adjusted mean HCRU (pharmacy visits: 31.21 vs. 23.68; ambulatory and outpatient visits: 18.55 vs. 16.85) and costs, primarily due to medical costs (mean total cost: $36 676.08 vs. $31 346.54) compared to those without.ConclusionsSubstantial utilization of PIM-OSHAA was observed in EI and ADI cohorts. PIM-OSHAA use was associated with higher HCRU and costs. These findings underscore the importance of appropriate treatment strategies for insomnia in the elderly population especially in those with concurrent AD.

Ferri, Raffaele; Lanza, Giuseppe; Mogavero, Maria P

doi: 10.1093/sleep/zsaf028pmid: 39901781

Kawada, Tomoyuki

doi: 10.1093/sleep/zsaf029pmid: 39954003

Agar, Georgie

doi: 10.1093/sleep/zsaf025pmid: 39866143

Chakravorty, Subhajit; Pillai, Manju

doi: 10.1093/sleep/zsae315pmid: 39749965

Ko, Chih-Yuan

doi: 10.1093/sleep/zsaf001pmid: 39798071

Walch, Olivia; Chee, Michael W L

doi: 10.1093/sleep/zsaf011pmid: 39806764

Wang, Wei; Cheung, Sing-Hang; Cheung, Shu Fai; Sun, Rong Wei; Hui, C Harry; Ma, Ho Yin Derek; Lau, Esther Yuet Ying

doi: 10.1093/sleep/zsaf021pmid: 39909735

Study ObjectivesTo shed light on understanding sleep duration trajectories (SDTs) using different classification methods and their outcomes, this study aimed to (1) identify common SDTs among different age groups, (2) investigate the alignment versus differences between SDTs identification by group-based trajectory modeling (GBTM) and clinical standards, and (3) examine the impacts of SDTs on health outcomes.MethodsA systematic literature search from four databases yielded 34 longitudinal SDT studies with GBTM analyses spanning three or more data waves. Apart from the proportion meta-analysis, a three-level meta-analysis was conducted with 14 of the studies that examined the association between SDT groups and health outcomes. Assessment of study quality was performed using the Guidelines for Reporting on Latent Trajectory Studies checklist.ResultsQualitative analysis identified four age-related SDT classes based on longitudinal trends: “persistent sleepers,” “increase sleepers,” “decrease sleepers,” and “variable sleepers.” Meta-analysis also showed differential proportions of “GBTM-defined shortest sleepers” across age groups and sample regions, as well as significant discrepancies in the prevalence of short sleep identified by clinical standards (=50% vs. 15% per GBTM). Overall, SDTs predicted emotional and behavioral outcomes, neurocognitive problems, and physical health (OR = 1.538, p < 0.001), in GBTM-defined “short,” “fluctuating,” “long,” and “decreasing” sleepers as compared to the “adequate” group. The effects were stronger in adolescents and in datasets with more waves.ConclusionsThe identification of the GBTM-defined “short,” “fluctuating,” “long,” and “decreasing” SDT groups and their associations with various health outcomes supported longitudinal investigations, as well as the development of interventions focusing on both the length and stability of sleep durations, especially in younger populations. Study registration: PROSPERO registration number CRD42023412201.

Hasler, Brant P; Oryshkewych, Nina; Wallace, Meredith L; Clark, Duncan B; Siegle, Greg J; Buysse, Daniel L

doi: 10.1093/sleep/zsaf031pmid: 39901722

Study ObjectivesIn a sample of high-school students, (1) to characterize within-person changes in sleep and circadian characteristics from school nights to weekend nights, (2) to examine whether later circadian phase relates to weekday–weekend changes in sleep/circadian characteristics, and (3) to examine correlations between biological and proxy measures of circadian phase.MethodsSample included 95 high-school students reporting at least one drink of alcohol in their lifetime. Participants completed baseline self-report measures, wrist actigraphy for 8 days, and two overnight laboratory visits (Thursday and Sunday) for salivary melatonin sample collection. Circadian phase was calculated as the dim light melatonin onset (DLMO; 4 pg/mL threshold). Proxy circadian phase measures included the Composite Scale of Morningness (CSM), Munich Chronotype Questionnaire (MCTQ), and actigraphy-based midsleep.ResultsOther than nap duration, all examined actigraphy-based sleep characteristics, DLMO, and DLMO-sleep phase angles showed weekday–weekend differences (adjusted p-value < .05). Later mean DLMO was associated with larger weekday–weekend changes in total sleep time (b = 0.39, padjusted = .010). CSM and actigraphy-based midsleep showed small-to-moderate (rho = ~0.3) and moderate (rho = ~0.5) correlations with DLMO, respectively, but chronotype based on the MCTQ was not correlated with DLMO.ConclusionsIn the largest published sample to date, circadian phase substantially shifted from the school week to weekend, underscoring the “social jetlag” imposed by early school start times. Similarly, teens with the latest circadian phase exhibited the greatest weekend catch-up sleep. Finally, perhaps due to the instability of circadian phase in this context, self-reported proxies for circadian timing were poor approximations of biological circadian phase.

Veitch, Matthew R; AlHamid, May Adel; Muir, Ryan T; Dharmakulaseelan, Laavanya; Ramirez, Joel R; Gao, Fuqiang; Swartz, Richard H; Murray, Brian J; Black, Sandra E; Boulos, Mark I

doi: 10.1093/sleep/zsaf027pmid: 39901803