Pretest and post test values of MoCA in Group A and B in Type 2 Diabetes Mellitus subjects
Bibliographic record
Abstract
Diabetes Mellitus (DM) is a chronic metabolic disorder characterized by hyperglycemia, insulin resistance, and impaired insulin secretion. Type 2 Diabetes Mellitus (T2DM) is not only a metabolic disorder but is also associated with an increased risk of cognitive dysfunction, affecting memory, attention, and executive functions. Cognitive Motor Dual Task Training (CMDTT) is designed to engage multiple procedural memory centers in the brain, including the basal ganglia, cerebellum, supplementary motor area, and premotor cortex, thereby enhancing both cognition and motor function.This randomized controlled study aimed to evaluate the effectiveness of CMDTT in improving cognitive function among individuals with T2DM. A total of 62 participants with T2DM were assessed using the Montreal Cognitive Assessment (MoCA) scale before and after the intervention. The experimental group (n=31) performed CMDTT along with aerobic training, while the control group (n=31) underwent conventional therapy comprising aerobic and resisted exercises. The findings demonstrated a significant improvement in cognitive function in the experimental group, with a statistically significant difference compared to the control group (p=0.0001). The study concludes that CMDTT is a more effective approach in enhancing cognitive function in individuals with 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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.003 |
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".