MétaCan
Menu
Back to cohort
Record W2076014070 · doi:10.3109/00207451003668408

RimabotulinumtoxinB Effects on Pain Associated with Cervical Dystonia: Results of Placebo and Comparator-Controlled Studies

2010· article· en· W2076014070 on OpenAlexaboutno aff
Mark Lew, Robert Chinnapongse, Yuxin Zhang, Meg Corliss

Bibliographic record

VenueInternational Journal of Neuroscience · 2010
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsPlaceboSpasmodic TorticollisCervical dystoniaBotulinum toxinMedicineRating scaleAnesthesiaClinical trialInternal medicineTorticollisSurgeryPsychology

Abstract

fetched live from OpenAlex

Response rate (RR) and mean improvement (MI) in the pain subscale of the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS-PS) from two placebo-controlled studies and one comparator-controlled study were evaluated to examine the effect of rimabotulinumtoxinB (BoNT-B) on cervical dystonia (CD) pain. Subjects receiving either of two doses of BoNT-B in the AN072-301 trial had an RR of 66% and 58% compared with 23% for placebo (p < .05). Subjects receiving BoNT-B in the AN072-302 trial had an RR of 49% compared with 19% for placebo (p < .05). Subjects receiving BoNT-B in the AN072-402 comparator-controlled trial had a significantly higher RR than those treated with BoNT-A (59% vs. 36%; p < .05). Additionally, subjects treated with BoNT-B in these placebo-controlled trials had significantly larger MIs than those treated with placebo (4.3 and 3.7 vs. 0.5 for AN072-301 and 3.6 vs. 0.1 for AN072-302; p < .05). Subjects treated with BoNT-B in the comparator-controlled trial demonstrated a numerically larger MI than those treated with BoNT-A (2.6 vs. 1.8; p = .1651). These results support the consideration of BoNT-B as an effective first-line botulinum toxin treatment for patients with CD who list pain as a primary complaint.

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)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.897
Threshold uncertainty score0.738

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
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 integrity0.0000.001
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 head0.021
GPT teacher head0.312
Teacher spread0.291 · 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 designBench or experimental
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

Citations22
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of NeuroscienceSame topicBotulinum Toxin and Related Neurological DisordersFrench-language works237,207