Mini-mental state exam versus Montreal Cognitive Assessment in patients with diabetic retinopathy
Bibliographic record
Abstract
BACKGROUND: Mini-mental state exam (MMSE) was used several times but no study has examined cognition on the Montreal Cognitive Assessment (MoCA) in diabetes and diabetic retinopathy (DR). In this study, we compared MMSE with MoCA in patients with DR and searched for an association between the severity of DR and cognitive impairment (CI). METHODS: This cross-sectional study comprised 120 consecutive patients with diabetes. Patients were divided into four groups as no DR, mild DR, severe nonproliferative DR (PDR) and PDR. Each group consisted 30 inviduals. CI was assessed using the MMSE and MoCA. RESULTS: The number of subjects with a score>21 were significantly lower on the MoCA than on the MMSE between groups (all P<0.05). The mean MoCA score was significantly lower than the MMSE score (P<0.001) There was a linear association between the grade of DR and a score<21 on both tests, CONCLUSION: MoCA provides more insight into the cognitive function in DR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.000 | 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".