OnabotulinumtoxinA Treatment of Mild Glabellar Lines in Repose
Bibliographic record
Abstract
BACKGROUND OnabotulinumtoxinA is an established treatment for glabellar frown lines, but its effects on lines at repose are less well documented. OBJECTIVE To assess the effect of onabotulinumtoxinA on elimination of mild lines at repose. METHODS Data from two randomized, double-blind, placebo-controlled studies were included. Elimination of mild lines at repose was defined as change from mild to none on the Facial Wrinkle Scale. RESULTS Analysis included 183 participants who received 20 U of onabotulinumtoxinA and 64 participants who received placebo, all with mild lines at repose at baseline. Participants were evaluated 7, 30, 60, 90, and 120 days posttreatment. Compared to placebo, onabotulinumtoxinA-treated participants were significantly more likely to have their lines at repose eliminated at each study day; [odds ratios ranged from 42.7 (95% confidence interval (CI)=12.9–141.9) at day 30 to 4.9 (95% CI=2.2–10.8) at day 120 (p<.0001 at each day)]. The highest response rate was observed at day 30 (68%). CONCLUSION OnabotulinumtoxinA has demonstrated the ability to eliminate mild glabellar lines at repose for a significant number of patients. This effect, albeit more subtle than the effect on dynamic or more severe glabellar lines, may be an important treatment goal for patients who seek a smoother appearance at repose. Drs. A. Carruthers and J. Carruthers are investigators and consultants for Allergan. Dr. Brin and Dr. Lei are employed by Allergan and receive direct salary compensation. Dr. Brin, Dr. Lei, and Ms. Eadie hold an equity interest in the companies in the form of stock, stock options, or both. Dr. Pogoda and Ms. Eadie have consulting contracts with Allergan.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".