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Record W4391508054 · doi:10.1101/2024.02.01.24302121

Physician Approaches to the Pharmacologic Treatment of Dystonia in Cerebral Palsy

2024· preprint· en· W4391508054 on OpenAlexaffabout
Emma Lott, Darcy Fehlings, Rose Gelineau‐Morel, Michael C. Kruer, Jonathan W. Mink, Sruthi P. Thomas, Steve J. Wisniewski, Bhooma R. Aravamuthan

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalUniversity of Toronto
FundersNational Institute of Neurological Disorders and StrokeAmerican Academy for Cerebral Palsy and Developmental Medicine
KeywordsDystoniaCerebral palsyPhysical medicine and rehabilitationMedicineNeurosciencePsychologyPsychiatry

Abstract

fetched live from OpenAlex

Abstract Objective To determine how physicians approach pharmacologic dystonia treatment in people with CP and assess physician readiness to participate in a randomized trial comparing existing pharmacologic dystonia treatments. Methods We administered a REDCap survey to physician members of the American Academy of Cerebral Palsy and Developmental Medicine and of the Child Neurology Society to assess which pharmacologic agents they use to treat dystonia in CP and their preferred indications and dosing. Results Of 479 physicians surveyed, 240 (50%) responded. Respondents treated functionally limiting (95%) and generalized (57%) dystonia and most commonly used six medications: baclofen (95%), trihexyphenidyl (79%), gabapentin (67%), carbidopa/levodopa (55%), clonazepam (55%), and diazepam (54%). Baclofen was preferred in people with co-existing spasticity (81%), gabapentin was preferred in people with co-existing pain (49%), and trihexyphenidyl was avoided in people with constipation (34%) or urinary retention (42%). Preferred dosing regimens followed published regimens for dystonia, when available, but otherwise followed published regimens for other CP symptoms (spasticity and seizures). Baclofen was preferred by 64% of respondents as first line treatment, but there was no clear consensus on second or third-line medications. Most respondents (51%) were comfortable randomizing their patients to receive any of the six most commonly used medications used to treat dystonia in CP. Conclusions This study summarizes current indications and dosing for the six most commonly used medications to treat dystonia in CP as per treating physicians in the US and Canada and also demonstrates physician support for a randomized trial comparing the effectiveness of these treatments. Article summary Dystonia is common and debilitating in people with CP, with little data on pharmacologic treatments. We describe physicians’ current approaches to using these treatments. What’s known on this subject Comparing the effectiveness of existing pharmacologic treatments for dystonia in CP is a research priority shared by clinicians and the community. However, current pharmacologic treatment practices are unknown. What this study adds Physicians in the US and Canada primarily prescribe a subset of six medications for the treatment of functionally limiting and generalized dystonia in CP: baclofen, trihexyphenidyl, gabapentin, carbidopa/levodopa, clonazepam, and diazepam. Contributors Statement Emma Lott helped design the study, carried out data analyses, and critically reviewed and revised the manuscript. Darcy Fehlings, Rose Gelineau-Morel, Michael Kruer, Jonathan Mink, Sruthi Thomas, and Steve Wisniewski helped design the study and critically reviewed and revised the manuscript. Bhooma Aravamuthan conceptualized and designed the study, supervised data collection and analysis, drafted the initial manuscript, and critically reviewed and revised the manuscript.

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)0.003
metaresearch head score (Gemma)0.011
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.123
GPT teacher head0.310
Teacher spread0.186 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

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