The case-control study of the effect of repetitive transcranial magnetic stimulation on elderly mild cognitive impairment patients
Bibliographic record
Abstract
Objective:To observe the efficacy of repetitive transcranial magnetic stimulation ( rTMS) on elderly patients with mild cognitive impairment ( MCI) . Method:40 elderly MCI patients were randomly assigned to a real rTMS group ( n = 22) or a sham rTMS group ( n = 18) in double-blind,the neuropsychological assessments were performed before the rTMS treatment,after 4-week and 8-week treatment to evaluate the effect of rTMS. Wisconsin card sorting test ( WCST) were texted before and after 8-week treatment to evaluate the executive function. Results:Comparison of the neuropsychological performance within the real rTMS group:significant difference was found in Montreal cognitive assessment ( MoCA) ,similarity test,verbal fluent test,digitsymbol test,trail making test-A,associative learning test,episodic memory test and arithmetic test( F = 41. 916, 7. 891,4. 150,4. 483,24. 175,9. 589; P 0. 05 or P 0. 001) . At the same time,the subjects in the real rTMS group who completed the 8-week treatment did better in above tests than after 4-week treatment ( P 0. 01 or P 0. 001) ; WCST scores were obviously better than pre-treatment( P 0. 01 or P 0. 001) ,while the scores of copying test didn't increase after the treatment in the real rTMS group ( F = 3. 103,P = 0. 07) . In the sham rTMS group,no difference existed in the performance of neuropsychological tests and WCST test between pre-and post-treatment ( all P 0. 05) . Conclusion:rTMS is able to improve MCI elderly patients at learning memory and execution,8-week treatment can further improve the cognitive function of MCI than 4-week treatment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".