Cognitive Function in Type 2 Diabetes Mellitus Patients Taking Metformin and Metformin-Sulfonylurea
Bibliographic record
Abstract
The most prescribed antidiabetic drugs in Indonesian primary health care are metformin or a combination of metformin and sulfonylurea. Studies on metformin have shown various impacts on cognitive decline in patients with type 2 diabetes mellitus, whereas sulfonylurea has been shown to reduce this impact. This study aimed to compare the impacts of metformin and metformin-sulfonylurea on cognitive function and determine what factors affected it. This cross-sectional study was conducted at Pasar Minggu Primary Health Care involving 142 type 2 diabetes mellitus patients taking metformin or metformin-sulfonylurea for > 6 months and aged > 36 years. Cognitive function was assessed using the validated Montreal Cognitive Assessment Indonesian version. The effects of metformin and metformin-sulfonylurea on cognitive decline showed no significant difference, even after controlling for covariates (aOR = 1.096; 95% CI = 0.523–2.297; p-value = 0.808). Multivariate analysis showed age (OR = 4.131; 95% CI = 1.271–13.428; p-value = 0.018) and education (OR = 2.746; 95% CI = 1.196–6.305; p-value = 0.017) affected cognitive function. Since a lower education and older age are likely to cause cognitive decline, health professionals are encouraged to work with public health experts to address these risk factors for cognitive function.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 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".