Ghrelin is a possible new predictor associated with executive function in patients with type 2 diabetes mellitus
Bibliographic record
Abstract
AIMS/INTRODUCTION: The aim of the present research was to study the ghrelin level, executive function and their possible association in patients with type 2 diabetes mellitus. MATERIALS AND METHODS: A total of 370 people were recruited between March 2015 and March 2016 in this study. Among them, 212 participants were patients with type 2 diabetes mellitus and 158 participants were included as the control group. Their blood sample was analyzed for the level of ghrelin and other clinical indexes. Cognitive function was measured by the Montreal Cognitive Assessment, and executive function was evaluated by the Wisconsin Card Sorting Test. RESULTS: In the type 2 diabetes mellitus group, age, years of education, duration of diabetes, fasting blood glucose, glycated hemoglobin, hypertension and waist-to-hip ratio were correlated with total Montreal Cognitive Assessment scores. No association was found between ghrelin level and total Montreal Cognitive Assessment score in patients with type 2 diabetes mellitus. However, ghrelin was found to be a significant predictor for executive function impairment measured by the Wisconsin Card Sorting Test in patients with type 2 diabetes mellitus. CONCLUSIONS: The level of serum ghrelin might be a biomarker of executive function and become a strong predictor of executive function impairment in patients with type 2 diabetes mellitus. Ghrelin might have a potential protective effect against cognitive function impairment in type 2 diabetes patients.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".