Poor Sleep is Common in Treatment-Resistant Late-life Depression and Associated With Poorer Antidepressant Response: Findings From the OPTIMUM Clinical Trial
Bibliographic record
Abstract
BACKGROUND: Adults with treatment-resistant late-life depression (TRLLD) have high rates of sleep problems; however, little is known about the occurrence and change in sleep during pharmacotherapy of TRLLD. This analysis examined: (1) the occurrence of insufficient sleep among adults with TRLLD; (2) how sleep changed during pharmacotherapy; and (3) whether treatment outcomes differed among participants with persistent insufficient sleep, worsened sleep, improved sleep, or persistent sufficient sleep. METHODS: Secondary analysis of data from 634 participants age 60+ years in the OPTIMUM clinical trial for TRLLD. Sleep was assessed using the sleep item from the Montgomery-Asberg Depression Rating Scale at the beginning (week-0) and end (week-10) of treatment. The analyses examined whether treatment outcomes differed among participants with persistent insufficient sleep, worsened sleep, improved sleep, or persistent sufficient sleep during depression treatment. RESULTS: About half (51%, n = 323) of participants reported insufficient sleep at baseline. Both persistent insufficient sleep (25%, n = 158) and worsened sleep (10%, n = 62) during treatment were associated with antidepressant nonresponse. Participants who maintained sufficient sleep (26%, n = 164) or who improved their sleep (n = 25%, n = 158) were three times more likely to experience a depression response than those with persistent insufficient sleep or worsened sleep. CONCLUSION: Insufficient sleep is common in TRLLD and it is associated with poorer treatment response to antidepressants.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".