Safety of transcranial magnetic stimulation in Parkinson's disease: A review of the literature
Bibliographic record
Abstract
BACKGROUND: Transcranial magnetic stimulation (TMS) has been used in both physiological studies and, more recently, the therapy of Parkinson's disease (PD). Prior TMS studies in healthy subjects and other patient populations demonstrate a slight risk of seizures and other adverse events. Our goal was to estimate these risks and document other safety concerns specific to PD patients. METHODS: We performed an English-Language literature search through PudMed to review all TMS studies involving PD patients. We documented any seizures or other adverse events associated with these studies. Crude risks were calculated per subject and per session of TMS. RESULTS: We identified 84 single pulse (spTMS) and/or paired-pulse (ppTMS) TMS studies involving 1091 patients and 77 repetitive TMS (rTMS) studies involving 1137 patients. Risk of adverse events was low in all protocols. spTMS and ppTMS risk per patient for any adverse event was 0.0018 (95% CI: 0.0002-0.0066) per patient and no seizures were encountered. Risk of an adverse event from rTMS was 0.040 (95% CI: 0.029-0.053) per patient and no seizures were reported. Other adverse events included transient headaches, scalp pain, tinnitus, nausea, increase in pre-existing pain, and muscle jerks. Transient worsening of Parkinsonian symptoms was noted in one study involving rTMS of the supplementary motor area (SMA). CONCLUSION: We conclude that current TMS and rTMS protocols do not pose significant risks to PD patients. We would recommend that TMS users in this population follow the most recent safety guidelines but do not warrant additional precautions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".