A durable gain in motor and non-motor symptoms of Parkinson’s Disease following repeated caloric vestibular stimulation: A single-case study
Bibliographic record
Abstract
OBJECTIVE: To gain 'first-in-man' evidence that repeated caloric vestibular stimulation (CVS), a non-invasive form of neuro-modulation, can induce a lasting and clinically-relevant reduction in Parkinson's Disease (PD) symptoms. METHODS: A 70 yr old male, diagnosed with PD 7 years prior to study enrolment, self-administered CVS at home 2×20 minutes per day for three months using a solid-state portable device. Standardised neuropsychological assessments of motor, cognitive, affective and independent function were carried out prior to stimulation, at the start and end of the sham (month 1) and active (months 2-3) phases, and 5 months post-stimulation. RESULTS: Relative to the pre-stimulation baseline, behavioural improvements that exceeded the minimal detectable change were observed on the EQ5D, Unified Parkinson's Disease Rating Scale, Schwab and England scale, 2 minute walk, Timed up and go, Non-motor symptom assessment scale for PD, Montreal cognitive assessment, Hospital depression scale and Epworth sleepiness scale. The level of change exceeded the threshold for a minimal clinically important difference on all scales for which a threshold has been published. By contrast, little improvement was seen during the sham (i.e., placebo) phase. CONCLUSION: Caloric vestibular stimulation may offer a novel, home-based method of relieving everyday symptoms of PD, and merits further evaluative study.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".