Is metformin the only culprit for cognitive impairment in diabetes?
Bibliographic record
Abstract
Background: As patients with diabetes are conventionally on a long-term prescription for metformin, it is important to identify any increase in their risk for developing cognitive disorders due to metformin. Hence, an attempt was made to study the cognitive impairment by using Montreal Cognitive Assessment test (MoCA) as a possible predictor of development of cognitive impairment in type 2 diabetes patients on metformin therapy. Methods: Four hundred type 2 diabetes patients on metformin were enrolled for this cross-sectional study, and data recorded. Cognitive test MoCA was administered and a score less than 26 was considered abnormal. Results: In this study, the participants on metformin had a statistically significant correlation with age > 65 years, duration of diabetes (>5 years), metformin dose (1 gm and more) and presence of diabetes complications. Ordinal regressions showed significant correlation between abnormal MoCA scores and older age, longer duration of DM, and presence of one of the DM complications. Conclusions: Amongst patients receiving medical therapy for control of type 2 diabetes, participants using metformin showed a very high prevalence rate of abnormal MoCA scores (85%). Increased duration of metformin intake leads to a decline in MoCA performance.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".