Adverse events in long-term studies of exogenous melatonin
Bibliographic record
Abstract
Exogenous melatonin is regulated as a drug in the UK and EU but is available as an over-the-counter dietary supplement in the US and Canada. In the last 15 years, melatonin use has increased rapidly in many countries, in particular, in children and adolescents who frequently have many years of continuous exposure. Despite this, the potential risks associated with extended use continue to be unclear, and there remains a lack of systematically assessed safety data from long-term prospective trials. This review focuses on adverse event data reported in long-term (≥6 months) prospective trials of melatonin. The Embase and Medline electronic databases were searched from inception to 12 September 2022 for long-term studies of melatonin, in which adverse events were systematically monitored and reported. Although the reported frequency of possible adverse events associated with long-term melatonin use is low and few clinically significant adverse events have been reported, the scarcity of data from double-blind randomized placebo-controlled trials should caution against complacency. Ideally, analysis of data from large well-established research databases should be conducted to provide good quality evidence on which to base a more rigorous evaluation of the safety profile.
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 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 | 0.041 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".