Transcranial Pulsed Current Stimulation (tPCS) in Parkinson’s Disease: A Pilot Trial
Bibliographic record
Abstract
ABSTRACT Background: Noninvasive stimulation techniques are a promising therapy due to the ease of administration and minimal side effects. We investigated the clinical, electrophysiological and side effects of transcranial pulsed current stimulation (tPCS) in patients with Parkinson’s disease (PD). Materials and Methods: Ten PD patients were called at monthly intervals in the OFF levodopa state. Patients received active tPCS for 20 minutes in the first visit and sham stimulation for 20 minutes in the second and were assessed for the levodopa response in the third. Clinical and bradykinesia scoring and gait and tremor analysis were done before and after stimulation/sham/levodopa in each visit. Scalp electroencephalography (EEG) was recorded for quantitative analysis during each visit. The interventions were compared between pre- and post-intervention. Results: A significant improvement with levodopa as compared to active and sham tPCS was seen in clinical scores. Upper limb postural tremor severity ( z-score = −2.410, p = 0.016) and the stride velocity variability during post active stimulation improved by 20.7% compared to post sham stimulation though the difference was statistically non-significant. KINARM testing showed a statistically significant difference in the reaction time (p = 0.036) when comparing pre- and post-tPCS active stimulation. EEG recording showed a transitory increase of electrical activity after tPCS, with the most significant increase seen in alpha bandpower ( p = 7.95*10 -07 ; z score: −4.93). Conclusions: tPCS was well tolerated in all patients. With minimal side effects, ease of administration and mild improvement in the electrophysiological parameters assessed, tPCS can be an alternative therapeutic option in patients with 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".