Short and Long-term Effects of rTMS Treatment on Alzheimer's Disease at Different Stages: A Pilot Study
Bibliographic record
Abstract
Repetitive transcranial magnetic stimulation (rTMS) uses a magnetic coil to induce an electric field in brain tissue. As a pilot study, we investigated the effect of rTMS treatment on 10 volunteers with Alzheimer's disease (AD) in a two-stage study. The first stage consisted of a double-blind crossover study with real and sham treatments. Each treatment block consisted of 13 sessions over 4 weeks. During each session, 2000 TMS pulses at 90%-100% of resting motor threshold were applied to dorsolateral prefrontal cortex bilaterally, and the patients were kept cognitively active by object/action naming during the treatment. The second stage was an open-label study, in which the same treatments were performed in 2-week blocks (10 sessions) approximately every 3 months as follow-up treatments on six of the volunteers, who completed the first stage of the study. Primary outcome measures were the Montreal Cognitive Assessment (MOCA) and the Alzheimer's Disease Assessment Scale-cognitive subscale. The secondary outcome measures were the Revised Memory and Behavior Checklist as well as our team's custom-designed cognitive assessments. The results showed a noticeably stronger improvement on all assessments during the real treatment as compared to the sham treatment. The changes in MOCA scores as well as our designed cognitive assessment were found to be statistically significant, with particularly strong results in the six volunteers who were in the early stages of the disease. The long-term trends observed in the second stage of the study also showed generally less decline than would be expected for their condition. It appears that rTMS can be an effective tool for improving the cognitive abilities of patients with early to moderate stages of AD. However, the positive effects of rTMS may persist for only up to a few weeks. Specific skills being practiced during rTMS treatment may retain their improvement for longer periods.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".