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Record W4413112216 · doi:10.1097/prs.0000000000012345

Improvement of Lower Facial Shape after Treatment with OnabotulinumtoxinA: Secondary Results from a Phase 2 Dose Escalation Study

2025· article· en· W4413112216 on OpenAlexaff
Steven Liew, Jason K. Rivers, Shannon Humphrey, Jean Carruthers, Shyi-Gen Chen, Beta Bowen, Elisabeth Lee, Mitchell F. Brin

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsSKiN HealthUniversity of British Columbia
Fundersnot available
KeywordsPhase (matter)PsychologyPhysics

Abstract

fetched live from OpenAlex

BACKGROUND: Masseter muscle prominence (MMP) contributes to a widened lower facial shape, considered aesthetically undesirable to some individuals. This study assessed lower facial shaping improvements with onabotulinumtoxinA. METHODS: In a phase 2, randomized, placebo-controlled study, onabotulinumtoxinA (24, 48, 72, or 96 U) or placebo was injected intramuscularly (3 sites per masseter) into subjects with bilaterally symmetric "marked" or "very marked" MMP on the Masseter Muscle Prominence Scale (MMPS). Changes from baseline at day 90 in lower facial width, mandibular facial angle, investigator-rated MMPS response, subject-perceived symptoms, psychosocial impact of lower face appearance, and satisfaction with lower face on the Lower Facial Shape Questionnaire were assessed. RESULTS: Among 187 subjects (mean age, 35.4 years; 81.8% female; and 79.7% Asian), significant reductions from baseline in lower facial width and mandibular angle were achieved with all onabotulinumtoxinA doses versus placebo at day 90 ( P < 0.001, each parameter), continuing through day 180. At day 90, greater improvements in MMPS grade (all doses) and MMP signs, psychosocial impacts, and satisfaction were observed. CONCLUSION: OnabotulinumtoxinA treatment improved lower facial shape in individuals with MMP, producing a more desirable ovoid appearance for at least 6 months, with greater patient satisfaction.

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 score0.769
Threshold uncertainty score0.933

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.014
GPT teacher head0.258
Teacher spread0.244 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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