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Record W4410481996 · doi:10.1093/sleep/zsaf090.0550

0550 Lemborexant’s Effects on Rapid Eye Movement (REM) Sleep Architecture in Asian and Non-Asian Adults with Insomnia: Comparative Analysis from 3 Studies

2025· article· en· W4410481996 on OpenAlexaff
Yong Won Cho, Michael Mak, Jocelyn Y. Cheng, Naoto Yamakawa, Dinesh Kumar, Kisaki Onishi, Takao Takase, Margaret Moline

Bibliographic record

VenueSLEEP · 2025
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsEye movementInsomniaSleep architectureSleep (system call)Non-rapid eye movement sleepRapid eye movement sleepAudiologyPsychologyMedicinePolysomnographyPhysical medicine and rehabilitationElectroencephalographyPsychiatryNeuroscienceComputer science

Abstract

fetched live from OpenAlex

Abstract Introduction Sleep architecture is altered in insomnia, including reduced rapid eye movement (REM) sleep. As REM sleep supports cognition and emotional regulation, its preservation has potentially important clinical implications. Treatment with lemborexant (LEM), a dual orexin-receptor antagonist, led to increased REM sleep compared with placebo (PBO) in adults with insomnia. This investigation evaluated the comparative effects of LEM on REM sleep parameters between Asian and non-Asian adults with insomnia, thereby evaluating potential effects of race. Methods This analysis incorporated data from 3 independent, 1-month, randomized, double-blind, PBO-controlled, parallel-group studies. E2006-J086-311 (Study 311; NCT04549168) included Chinese participants ≥18y. E2006-J082-204 (Study 204; NCT05594589) included Korean participants 19–80y. E2006-G000-304 (Study 304; NCT02783729) enrolled participants ≥55y (females)/≥65y (males) of any race; only non-Asian participants are presented here. Polysomnographic assessment of REM sleep and REM latency (REML) was conducted at baseline (during single-blind PBO run-in) and following 1 month of treatment with LEM 10mg (LEM10) or PBO. Results Mean (SD) baseline REM for LEM10 and PBO was 68.65(19.167) and 69.85(17.091) min, 67.37(28.695) and 58.96(36.077) min, and 61.58(20.409) and 65.32(19.591) min for Study 311 (LEM10, n=93; PBO, n=100), Study 204 (LEM10, n=26; PBO, n=13), and Study 304 (LEM10, n=264; PBO, n=206), respectively. At 1 month, least squares mean (LSM) (SE) CFB in REM for LEM10 and PBO was 24.05(3.451) and 8.59(3.176) min (P< 0.0001), 28.06(5.325) and 12.77(7.529) min (P=0.1035), and 21.82(1.368) and 5.10(1.528) min (P< 0.0001) for Study 311, Study 204, and Study 304, respectively. Mean (SD) baseline REML for LEM10 and PBO was 98.26(41.392) and 95.59(33.729) min, 125.63(68.727) and 131.42(91.967) min, and 100.14(54.320) and 99.60(51.803) min for Study 311, Study 204, and Study 304, respectively. Mean (SD) CFB in REML for LEM10 and PBO was −38.47(45.677) and −7.20(37.393) min (P< 0.0001), −42.15(73.471) and −0.83(59.514) min (P=0.0709), and −38.16(56.103) and −7.28(62.479) min (P< 0.0001) for Study 311, Study 204, and Study 304, respectively. Conclusion The magnitude of changes in REM sleep and REML was comparable between Asian and non-Asian participants, demonstrating LEM’s consistent therapeutic effect across diverse patient populations. Given REM sleep’s established role in cognition and emotional regulation, these findings suggest potentially significant clinical implications warranting further evaluation. Support (if any) Eisai

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.497
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.284
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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