1625 MELATONIN MODESTLY IMPROVES SLEEP EFFICIENCY IN PATIENTS WITH NEUROCOGNITIVE DISORDERS: A SYSTEMATIC REVIEW AND META-ANALYSIS
Bibliographic record
Abstract
Abstract Introduction The administration of melatonin and melatonin receptor agonists (MRA) may result in a small improvement in sleep quality among middle-aged and older adults living with neurocognitive disorders, but debate remains as to whether effects are clinically meaningful. The purpose of this PROSPERO-registered systematic review and meta-analysis (CRD42022373972) was to synthesise evidence from randomized controlled trials (RCTs) of melatonin or MRA against placebo and other interventions for the treatment of sleep disturbances in adults with neurocognitive disorders. Method CENTRAL, MEDLINE, EMBASE, AMED, CINAHL and PsycINFO were systematically searched on November 4th 2022, examining the effect of melatonin and MRA on sleep efficiency: the percentage of time spent asleep while in bed. Results were analysed using Review Manager 5.4. Risk of bias was assessed using RoB 2 and the certainty of evidence was assessed with the GRADE framework. Results Among the 1,579 references evaluated, 13 RCTs were selected, corresponding to 16 studies, none including MRA, with a total of 592 patients. Compared with placebo, bright light treatment, or clonazepam, sleep efficiency significantly improved with melatonin administration (MD = 2.85, 95% CI: 0.88 to 4.81, p = 0.004). In subgroup analyses, only low doses of melatonin (< 5 mg) yielded a statistically significant improvement to sleep efficiency (MD = 3.81, 95% CI: 1.13 to 6.49, p = 0.005, I2 = 34%), and melatonin administration statistically significantly improved sleep efficiency in patients with Mild Cognitive Impairment, Parkinson's Disease, or Multiple Sclerosis (MD = 3.27, 95% CI: 0.11 to 6.43, p = 0.04, I2 = 41%), but not patients with Alzheimer's Disease. We found the overall quality of evidence to be moderate according to GRADE. Conclusion Melatonin may modestly ameliorate sleep quality in patients with neurocognitive disorders by improving sleep efficiency, which may be clinically significant to patients and those who care for them.
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.031 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".