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Record W2772026949 · doi:10.3138/ptc.2016-76

Long-Term Resolution of Severe Ankle Contractures Using Botulinum Toxin, Serial Casting, Splinting, and Motor Retraining

2017· article· en· W2772026949 on OpenAlexvenueno aff
Joan Leung, Katarina Stroud

Bibliographic record

VenuePhysiotherapy Canada · 2017
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsRetrainingPhysical medicine and rehabilitationMedicineAnkleMuscle contractureTerm (time)Botulinum toxinComputer scienceSurgery

Abstract

fetched live from OpenAlex

Purpose: Serial casting for ankle contractures is traditionally performed in prone, a position that patients may not easily tolerate. Also, although serial casting is effective in correcting contracture, its effect dissipates quickly. This case report describes a procedure for performing casting for ankle contractures in a supine or sitting position. It also describes a process that enables the effect of serial casting to be maintained long term. Client Description: The client was an adult who had suffered traumatic brain injury and severe bilateral ankle contractures. Intervention: He received botulinum toxin and serial casting for his bilateral ankle contractures, one ankle at 8 months and the other at 13 months after the injury. He then underwent a programme of splinting and motor training. Measures and Outcome: The client gained more than 40° dorsiflexion for both ankles after receiving botulinum toxin injections and serial casting. The improvement in ankle range enabled him to progress to walking practice. Ankle splinting was gradually reduced. On discharge at 25 months post-injury, the ankle joint range was maintained. Implications: The use of botulinum toxin and serial casting, followed by an intensive programme of splinting and motor training, may be an option to consider for effective long-term resolution of severe contractures after acquired brain injury.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.899
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.298
Teacher spread0.276 · 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 teacher head, 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

Citations5
Published2017
Admission routes1
Has abstractyes

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