Association of Serum Melatonin Level with Mild Cognitive Impairment in Type 2 Diabetic Patients: A Cross-Sectional Study
Bibliographic record
Abstract
Objectives. Melatonin is an essential neuroendocrine hormone that participates in the regulation of sleep rhythm and cognitive function. This study aimed to determine serum melatonin levels with mild cognitive impairment (MCI) in patients with type 2 diabetes (T2DM). Methods. A total of 247 T2DM patients were recruited in this retrospective study and divided into 75 subjects with MCI and 172 with normal cognition. Cognitive function was evaluated by the Montreal Cognitive Assessment (MoCA). Their blood sample was examined for the level of melatonin and other biochemical parameters. Results. Melatonin concentration was decreased in MCI patients to non-MCI patients ( P < 0.001). Melatonin level was negatively correlated with age (r = −0.202; P = 0.001), diabetes duration (r = −0.282; P < 0.001), serum HbA1c (r = −0.195; P = 0.002), hs-CRP (r = −0.324; P < 0.001), and TSH (r = −0.184; P = 0.004) levels and positively correlated with MoCA score, serum HDL-C (r = 0.145; P < 0.001), FT3 (r = 0.241; P < 0.001), and FT4 (r = 0.169; P = 0.008) levels. The multivariable analysis indicated that fewer years of formal education, longer diabetes duration, higher serum HbA1c, higher serum hs-CRP, and lower serum melatonin are the predisposing factors for MCI. Conclusion. Lower melatonin level was associated with cognitive impairment in patients with T2DM. Melatonin might serve as a potential protective molecule against cognitive dysfunction in T2DM.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".