P.054 Older subjects with insomnia disorder and comorbid pain at baseline: response to Lemborexant
Bibliographic record
Abstract
Background: There is a well-established reciprocal relationship between pain and poor sleep. Therefore, we evaluated whether an approved sleep-promoting drug, lemborexant (LEM), could improve sleep in older adults who reported both insomnia and pain. Methods: Study E2006-G000-304 (NCT02783729) was a 1-month, placebo (PBO)- and active-controlled study in subjects (age ≥55y) with insomnia disorder. Those reporting some/severe pain on the pain/discomfort dimension of the EQ-5D-3L at baseline were included. Subjects were randomized to placebo (PBO), LEM 5mg (LEM5), 10mg (LEM10) or zolpidem (not reported here). Changes from baseline (CFB) in objective sleep parameters latency-to-persistent sleep (LPS) and total-sleep-time (TST) were analyzed in paired polysomnograms. Results: 183/743 (24.6%) subjects in the PBO (n=55/208[26.4%]), LEM5 (n=78/266[29.3%]) and LEM10 (n=50/269[18.6%]) treatment groups reported some/extreme pain at baseline, with median LPS (minutes): 31.0, 29.4, 42.1, respectively. Respective median CFB for LPS at the beginning (Nights[NT]1/2: +2.5, –8.4, –15.8; P<0.005) was significantly larger/decreased for LEM5/LEM10 versus PBO and LEM5 at treatment end (NT29/30: –7.1, –9.9, –9.0; P=0.031). Mean baseline TST (minutes) was 335.3 (PBO), 336.3 (LEM5), 324.3 (LEM10), and mean CFB was significantly larger/increased (P<0.001) for LEM5/LEM10 versus PBO at NT1/2 and NT29/30. Conclusions: Results suggest LEM may effectively treat insomnia in older adults with comorbid pain. 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.015 | 0.001 |
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".