Treatment of glabellar lines with Botox (onabotulinumtoxinA): Development, insights, and impact
Bibliographic record
Abstract
OnabotulinumtoxinA is an injectable medication that produces muscle relaxation through local chemical denervation at the neuromuscular junction. Discovery of onabotulinumtoxinA's aesthetic benefits occurred serendipitously in the 1980s at the intersection of several medical disciplines, including ophthalmology, neurology, otolaryngology, and dermatology. Patients receiving onabotulinumtoxinA for blepharospasm, hemifacial spasm, and dystonia noticed their periorbital wrinkles disappearing, particularly frown lines between the eyebrows called glabellar lines (GL). Aesthetic use of onabotulinumtoxinA necessitated rigorous training programs and vigilant monitoring by Allergan. Approval for the GL indication was based on 2 similarly designed, double-blind, randomized, multicenter clinical studies. Subjects with moderate to severe GL receiving onabotulinumtoxinA achieved significantly greater improvement in GL severity than those receiving placebo. In subsequent studies, more than 80% of subjects were satisfied with onabotulinumtoxinA treatment through day 60, and many reported looking approximately 4 years younger at weeks 4 and 12 than at baseline. OnabotulinumtoxinA has a rapid onset of action, and peak effect occurs between 30 and 60 days. The median duration of response for dynamic GL in the initial studies was 120 days and response progressively improved with subsequent treatments. OnabotulinumtoxinA was well tolerated, and the 2 most common adverse events, headache and blepharoptosis, tended to decrease in frequency with repeat treatment. The novel use of onabotulinumtoxinA for treating GL was an important step in addressing the clinical need for a noninvasive, straightforward, office-based procedure for facial lines that also left patients extremely satisfied with its treatment effects and represented the beginning of its widespread use for numerous aesthetic indications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".