Surface Versus Penetrative rTMS Stimulation May Be More Effective for AD Patients with Cerebrovascular Disease
Bibliographic record
Abstract
Repetitive Transcranial Magnetic Stimulation (rTMS) has been applied as an investigational therapy for Alzheimer’s Disease (AD). The recent largest (N = 135) double-blind study with 6 months post-treatment follow-up investigating rTMS efficacy as a treatment for AD found about 72% of participants in each group of active and sham were positively responsive to rTMS (using Magstim AirFilm active and sham coils). Since the used sham coil produced about 25.3% of the peak active stimulus, it was hypothesized it could evoke a measurable response in AD patients. This study looks at the details of the above study’s sham responses to determine why and how such a response might occur and how cerebrovascular symptomatology may have impacted that response. In the above-mentioned study, 90 and 45 patients were randomly assigned to active and sham groups, respectively. Those with modified Hachinski Ischemic Scores (HIS) below and above 2 were labeled AD 2 and ADcvd 2 , respectively. Analysis of the primary outcome measure ADAS-Cog score change from baseline to post-treatment and follow-ups showed the ADcvd 2 in the sham group had a significantly ( p = .034) greater improvement or less decline at post-treatment and follow-up sessions compared to the ADcvd 2 in the active group. Additionally, the improvement of the ADcvd 2 sham compared to those in the active group persisted longer. Also, there was a significant ( p = .036) improvement for AD 2 individuals in the active compared to AD 2 sham stimulation group at 2-months post-treatment. Overall, the sham rTMS stimulus did evoke a measurable response which was more effective for ADcvd 2 in sham than ADcvd 2 in active support of a vascular mechanism likely linked to the shallower sham stimulus penetration.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".