P.051 Effect of lemborexant on cognition in patients with comorbid insomnia disorder and mild obstructive sleep apnea
Bibliographic record
Abstract
Background: Some sleep-promoting medications are associated with cognitive impairment, making treatment of comorbid obstructive-sleep-apnea (OSA) and insomnia (COMISA) challenging. Lemborexant is a dual-orexin-receptor-antagonist approved for insomnia treatment. This post-hoc analysis evaluated cognition in the subgroup of subjects with mild-OSA (apnea-hypopnea-index ≥5–<15 events/h-of-sleep). Methods: Study E2006-G000-304 was a 1-month, randomized, double-blind, placebo (PBO)- and active-comparator (zolpidem-ER 6.25mg [ZOL])-controlled study of lemborexant 5/10mg (LEM5/LEM10). Subjects ≥55y with insomnia disorder/sleep maintenance problems were enrolled (N=1006). A cognitive-performance assessment battery (CPAB) was performed at morning waketime of Days(D)2/3 and D30/31. Change-from-baseline (CFB) for mean power-of-attention (PoA), continuity-of-attention (CoA), quality-of-memory (QoM), and speed-of-memory-retrieval (SoMR) for CPAB tasks was analyzed. Results: The mild-OSA subgroup comprised 410 (40.8%) subjects. On D2/3 and D30/31, CFB for PoA, CoA, QoM, and SoMR for LEM5/LEM10 were not significantly different than PBO. On D2/3, PoA and QoM were significantly worse with ZOL vs PBO; QoM was significantly better with LEM5/LEM10 vs ZOL. On D30/31, SoMR was significantly worse with ZOL vs PBO and significantly better with LEM5/LEM10 vs ZOL. LEM safety in the subgroup was consistent with the overall study population. Conclusions: Memory and attention domains in subjects with COMISA characterized by mild-OSA were not impacted by LEM, unlike ZOL. Support: Eisai Inc.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".