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Record W4414146929 · doi:10.1101/2025.09.07.25334597

Tasks for assessing dystonia in young people with cerebral palsy

2025· preprint· en· W4414146929 on OpenAlexaff
Emma Lott, Alyssa Rust, Leon Dure, Darcy Fehlings, Toni S. Pearson, Roser Pons

Bibliographic record

VenuemedRxiv · 2025
Typepreprint
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalUniversity of Toronto
Fundersnot available
KeywordsDystoniaCerebral palsyNeurological disorderSeverity of illnessMovement disordersDeep brain stimulation

Abstract

fetched live from OpenAlex

Background: Dystonia in childhood is typically associated with cerebral palsy (CP). Dystonia severity scales for CP require prolonged exam protocols with numerous tasks, often making them onerous for routine clinical use. Objective: To identify which individual tasks best approximate dystonia severity compared to the gold standard full protocol. Methods: In this cross-sectional study, comprehensive exam protocol videos were taken during routine care of ambulatory people with CP age 5 and up. Five pediatric dystonia experts reviewed individual tasks and the full protocol for dystonia using the Global Dystonia Severity Rating Scale. Experts' written scoring justifications were qualitatively analyzed to determine commonly cited features of dystonia. Results: When examining the difference in dystonia severity ratings between each task and the full protocol, seated upper extremity tasks had the lowest variance (p<0.05, F-test) and had lower score differences than the stand/walk/run and seated lower extremity tasks (p<0.05, repeated measures Friedman test). Experts most commonly identified the following movements as dystonic: wrist flexion (8.4% of all movement statements), finger flexion (7.3%), wrist ulnar deviation (6.8%), toe dorsiflexion (8.4%), ankle inversion (7.9%), and ankle plantarflexion (6.4%). Experts rated dystonic movements as more severe if they were consistently triggered by multiple stimuli (26.8% of all severity statements) or functionally impactful (20.7%). Conclusions: This can be both expensive (requiring many personnel hours) and exhausting for people with CP to execute. Furthermore, the longer these severity assessments take, the less feasible they are to execute during routine clinical care, making it difficult to clinically assess the impact of dystonia treatments. Therefore, of the many tasks currently used across dystonia severity assessments, it would be valuable to determine the subset of tasks most useful for assessing dystonia in young people with CP.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.020
GPT teacher head0.301
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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