Efficacy of Balance Training and Motor Coordination Exercises on Mild Cognitive Impairment in Patients with Type 2 Diabetes Mellitus
Bibliographic record
Abstract
Abstract Background: Mild cognitive impairment, also known as central neuropathy, is a “new diabetic complication”. 10%–15% of diabetic patients having cognitive issues are converting to dementia. Aims and Objectives: This study evaluates the efficacy of balance training with motor coordination exercises on cognitive impairment and central reaction time. Methods: This pre–post experimental study was conducted on 30 ( n = 30) diabetic patients with cognitive impairment. Patients aged 35–55 years have glycated hemoglobin levels of 6.0%–8.0%. Montreal Cognitive Assessment Scale score (MoCA) score <24 with the presence of diabetes <5 years were included in the study. Patients were screened by the Addenbrooke Cognitive Examination Scale, Indian version (ACE-III), MoCA for cognitive functions and Stroop test for central reaction time. Outcome variables were measured at 2 points, on 1 st day and at the end of 5 th week. Patients with hypertension, neurodegenerative disorders, visual impairments, and hearing impairments were excluded. Results: After 5-week intervention, there was improvement in the mean score of ACE-III from 42.2 ± 5 to 48.8 ± 3 with ( P = 0.02), whereas MoCA means score improved from 19.3 ± 2 to 24.6 ± 2 ( P = 0.03) and mean score of Stroop test was improved from 60 s ± 2 to 8 s ± 2 ( P = 0.04). Conclusions: We conclude that there is improvement in memory, visuospatial skills, and concentration which further reflected upon aiding central reaction time; however, no significant improvement was observed in executive skills and abstract thinking.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".