Transcranial magnetic resonance-guided focused ultrasound pallidothalamic tractotomy for patients with X-linked dystonia-parkinsonism: a study protocol
Bibliographic record
Abstract
Abstract Transcranial magnetic resonance-guided focused ultrasound (MRgFUS) is a noninvasive method for controlling tremor and has recently been used in patients with X-linked dystonia-parkinsonism (XDP). This study aims to determine the improvement in dystonia and parkinsonism in patients with XDP after MRgFUS pallidothalamic tractotomy. This prospective study will be conducted at the Philippine General Hospital, University of the Philippines Manila. The primary outcome measure is the change in the pre- and post-treatment XDP-Movement Disorder Society of the Philippines Scale scores. In addition, demographic and clinical data will be collected, including the Burke-Fahn-Marsden Dystonia Rating Scale, Part III of the Movement Disorder Society-Unified Parkinson’s disease Rating Scale score, XDP clinical and functional stage, the five-level EuroQol five-dimensional questionnaire, Montreal Cognitive Assessment scores, MRgFUS treatment parameters, and adverse events. Patients will be assessed within 24 hours of treatment, then at 2 weeks, 3 months, 6 months, 9 months, and 12 months post-treatment. This protocol was approved by the University of the Philippines Manila Research Ethics Board (UPMREB 2022-0271-01). Data collection began in January 2023. This protocol has been registered with ClinicalTrials.gov: Trial Registration number: NCT05592028.
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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 | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.008 |
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".