The Effects of Melatonin Supplementation on Glycemic Control: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Why this work is in the frame
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Bibliographic record
Abstract
Abstract This systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted to clarify the effect of melatonin supplementation on glycemic control. Databases including PubMed, MEDLINE, EMBASE, Web of Science, and Cochrane Central Register of Controlled Trials were searched until July 30th, 2018. Two reviewers independently assessed study eligibility, extracted data, and evaluated the risk of bias for included trials. Heterogeneity among included studies was assessed using Cochran’s Q test and I-square (I2) statistic. Data were pooled using random-effect models and standardized mean difference (SMD) was considered as the overall effect size. Twelve trials out of 292 selected reports were identified eligible to be included in current meta-analysis. The pooled findings indicated that melatonin supplementation significantly reduced fasting glucose (SMD=–6.34; 95% CI, –12.28, –0.40; p=0.04; I2: 65.0) and increased the quantitative insulin sensitivity check index (QUICKI) (SMD=0.01; 95% CI, 0.00, 0.02; p=0.01; I2: 0.0). However, melatonin administration did not significantly influence insulin levels (SMD=–1.03; 95% CI, –3.82, 1.77; p=0.47; I2: 0.53), homeostasis model assessment of insulin resistance (HOMA-IR) (SMD=–0.34; 95% CI, –1.25, 0.58; p=0.37; I2: 0.37) or HbA1c levels (SMD=–0.22; 95% CI, –0.47, 0.03; p=0.08; I2: 0.0). In summary, the current meta-analysis showed a promising effect of melatonin supplementation on glycemic control through reducing fasting glucose and increasing QUICKI, yet additional prospective studies are recommended, using higher supplementation doses and longer intervention period, to confirm the impact of melatonin on insulin levels, HOMA-IR and HbA1c.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.052 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.045 | 0.007 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it