Clinical Comparison between Two Hyaluronic Acid–Derived Fillers in the Treatment of Nasolabial Folds
Bibliographic record
Abstract
BACKGROUND: Hyaluronic acid-derived injectible fillers are ideal to reduce the appearance of nasolabial folding because their effect is relatively long-lasting, the material is malleable and easy to use, and there is a very low incidence of allergic reaction. OBJECTIVE: To compare the tolerability and efficacy of two commercially available hyaluronic acid-based fillers, Hylaform (INAMED Aesthetics, Inc., Santa Barbara, CA, USA) and Restylane (Medicis Pharmaceutical Corporation, Scottsdale, AZ, USA), in the treatment of nasolabial folds. METHODS: Eight healthy adult female subjects underwent filler injection therapy for tissue augmentation of their nasolabial folds. Each subject was randomized to receive Restylane 0.7 mL to either the right or the left nasolabial fold and Hylaform 1.0 mL to the contralateral side. High-quality digital photography was performed both at baseline and at 12 weeks post-treatment. These photographs were assessed by four blinded, independent dermatologist reviewers for improvement. Subjects completed questionnaires to document tolerability and satisfaction. RESULTS: All subjects found the procedure to be tolerable and completely pain free after the use of oral infraorbital regional anesthesia blocks. The average subject satisfaction score was 3.00 of 5 for Hylaform and 3.78 of 5 for Restylane. The blinded, independent reviewer panel attributed an average improvement score of 2.86 of 5 for Hylaform and 3.78 of 5 for Restylane. CONCLUSION: Both Hylaform and Restylane are effective fillers for tissue augmentation of the nasolabial folds. Restylane demonstrated higher efficacy and subject satisfaction than Hylaform. With regional nerve blocks prior to injection, both agents are completely painless.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".