Safety and Efficacy of Nonanimal Stabilized Hyaluronic Acid for Improvement of Mouth Corners
Bibliographic record
Abstract
BACKGROUND: Esthetic concern with downturned mouth corners ("mouth frown") is increasing in the aging baby-boomer generation. A new technique to offer structural support using the recently approved filler nonanimal stabilized hyaluronic acid (NASHA; Restylane, Q-med Inc., Uppsala, Sweden) is described. METHOD: Fifteen women with prominent downturned mouth corners met the inclusion criteria for the study. All were photographed before and at 1 week, 3 months, 4.5 months, and 6 months after treatment using a standardized clinical photographic system. NASHA was injected using a standardized technique with nerve block anesthesia to ensure patient comfort. RESULTS: All 15 women noted swelling, redness, and some local discomfort for several days after the injection. All noted an improvement in the downward angulation of their mouth corners at the first post-treatment visit, with at least partial improvement maintained through the 6-month post-treatment follow-up visit. CONCLUSIONS: NASHA injection to support the age-related downturn of lateral lip corners was effective, safe, and well tolerated in a small prospective study of middle-aged female subjects. Esthetic satisfaction was greatest in the first 3 months post-treatment, but 40% of subjects still noted improvement at the 6-month follow-up visit.
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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 | 0.000 | 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".