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Record W4317036455 · doi:10.3390/toxins15020081

Botulinum Toxin Treatment of Motor Disorders in Parkinson Disease—A Systematic Review

2023· review· en· W4317036455 on OpenAlexaboutno aff
Bahman Jabbari, Samira Marie Comtesse

Bibliographic record

VenueToxins · 2023
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsBotulinum toxinDystoniaMedicineMovement disordersPhysical medicine and rehabilitationParkinson's diseaseWeaknessFocal dystoniaDiseaseSurgeryPathologyPsychiatry

Abstract

fetched live from OpenAlex

This review provides an up-to-date literature account on the efficacy of Botulinum toxin treatment for common motor disorders of Parkinson Disease. The reviewed disorders include the common motor disorders in PD such as tremor, focal foot dystonia, rigidity and freezing of gait (FOG). In the area of Parkinson tremor, two newly described evaluation/injection techniques (Yale method in USA and Western University method in Canada) offer efficacy with low incidence of hand and finger weakness as side effects. Blinded studies conducted on foot dystonia of PD indicate that botulinum toxin injections into toe flexors are efficacious in alleviating this form of dystonia. Small, blinded studies suggest improvement of Parkinson rigidity after botulinum toxin injection; proof of this claim, however, requires information from larger, blinded clinical trials. In FOG, the improvement reported in open label studies could not be substantiated in blinded investigations. However, there is room for further controlled studies that include the proximal lower limb muscles in the injection plan and/or use higher doses of the injected toxin for this indication.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.400
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.052
GPT teacher head0.343
Teacher spread0.292 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations8
Published2023
Admission routes1
Has abstractyes

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