Low-Frequency Repetitive Transcranial Magnetic Stimulation over Right Dorsolateral Prefrontal Cortex in Parkinson’s Disease
Bibliographic record
Abstract
BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is a promising therapeutic tool for Parkinson's disease (PD), and many stimulation targets have been implicated. We aim to explore whether low-frequency rTMS over the right dorsolateral prefrontal cortex (DLPFC) improves motor and nonmotor symptoms of individuals with PD. METHODS: We conducted a randomized, single-blind, sham-controlled parallel trial to compare the effect of 10 consecutive daily sessions of 1 Hz rTMS over right DLPFC on individuals with idiopathic PD between active and sham rTMS group. Primary outcomes were changes in Unified Parkinson's Disease Rating Scale (UPDRS) part III and Nonmotor Symptom Questionnaire (NMSQ). Secondary outcomes were changes in UPDRS total score, Hamilton Rating Scale for Depression (HRSD), Pittsburgh Sleep Quality Index (PSQI), and Montreal Cognitive Assessment (MoCA). Assessments were completed at baseline, after treatment, and at 1 month, 3 months, and 6 months after treatment. RESULTS: A total of 33 participants with PD were randomized. All participants completed the study and no severe adverse effect was noticed. Compared to baseline, active rTMS showed significant improvements in UPDRS part III and NMSQ at 1 month. Change of scores on UPDRS part III, HRSD, and PSQI persisted for 3 months after rTMS intervention. The beneficial effect on cognitive performance assessed by MoCA was maintained for at least 6 months in the follow-up. No significant changes were observed in the group with sham rTMS. CONCLUSIONS: Low-frequency rTMS of right DLPFC could be a potential selection in managing motor and nonmotor symptoms in PD.
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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 | 0.000 |
| 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 | 0.000 |
| 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".