Bibliographic record
Abstract
INTRODUCTION: Dermal fillers are effective for temporary volume augmentation, especially for deep features like NLFs. This is due to volume expansion, with relatively little precision in placement. Neurotoxins are effective at treating rhytids, but can have undesirable effects on facial expression. Available fillers and neurotoxins are not always optimal for treating fine or long, linear wrinkles, such as necklace lines, transverse forehead wrinkles, and lip contouring. To address these clinical needs, a novel hyaluronic acid (HA) product has been developed which is comprised of a dehydrated, solid HA thread attached to a 27 gauge straight needle. The HA thread is implanted by being pulled into position by the needle, whereupon the thread hydrates and slowly reverts back to a gel. METHODS: A first-in-human prospective multi-center study was conducted in Canada. The primary endpoint was safety, and the secondary endpoints were aesthetic result as assessed by the Investigator, Independent Reviewer, and subject. Photographic documentation was captured by CanfieldScientific. NLFs were rated by a Wrinkle Severity Scale and any other area was rated by a Global Aesthetic Improvement Scale. Subjects received bilateral treatment in one area; NLF, forehead, perioral (including vermillion boarder), necklace lines or crow’s feet. One retreatment was allowed at the 2-week follow-up. Follow-ups were at 1, 3 and 6 months. RESULTS: 72 patients were enrolled and completed this study. At least 10 were enrolled in each of the 5 treatment areas. There were no severe or unanticipated adverse events. Overall, the adverse event rates were comparable or better than published rates for HA dermal fillers. Almost all subjects demonstrated improved aesthetic outcomes despite conservative implantation methods initially. Many subjects demonstrated aesthetic improvement between the 1 and 3month follow-ups. CONCLUSION: The results from this clinical study demonstrate that HA threads are safe, and can be effective in treating difficult areas such as necklace lines, horizontal forehead lines, vermillion boarders, as well as more common areas such as NLFs and crow’s feet. The product lends itself well to features that are linear in nature, whether fine or deep. HA threads are a highly novel, differentiated product that complements injectable fillers and neurotoxins for minimally invasive facial rejuvenation.
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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 | 0.000 | 0.000 |
| 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) | 0.006 | 0.001 |
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".