Randomized, Double‐Blind Comparison of the Efficacy of Two Hyaluronic Acid Derivatives, Restylane Perlane and Hylaform, in the Treatment of Nasolabial Folds
Bibliographic record
Abstract
BACKGROUND: Cross-linked hyaluronic acid gels may offer longer-lasting cosmetic correction and a lower risk of immunogenicity than other soft tissue augmentation agents. OBJECTIVE: To compare the efficacy and safety of a non-animal-stabilized hyaluronic acid gel (Restylane Perlane, Q-Med, Uppsala, Sweden) with that of a hylan B gel (Hylaform, Genzyme Corp., Cambridge, MA, USA), a cross-linked hyaluronic acid from chicken combs, for treatment of nasolabial folds. METHODS: One hundred fifty patients with moderate or severe nasolabial folds were randomized to contralateral treatment with Restylane Perlane and Hylaform. Efficacy was assessed using semi-objective outcome instruments at 3, 4.5, and 6 months after achievement of an "optimal cosmetic result". Patients subsequently underwent open-label bilateral retreatment with Restylane Perlane (if required) and were followed up for a further 6 months. RESULTS: The two products were equally effective in producing an optimal cosmetic result, although fewer treatment sessions were required with Restylane Perlane. At 6 months post-treatment, a higher proportion of patients showed a > or = 1-grade improvement in Wrinkle Severity Rating Scale (WSRS) score with Restylane Perlane (75%) than with Hylaform (38%). Restylane Perlane was considered superior in 64% of patients, whereas Hylaform was superior in 8% of patients. Treatment-related adverse events tended to be more frequent with Restylane Perlane. Local injection-site reactions were generally transient and mild or moderate in intensity and were no more frequent after Restylane Perlane retreatment. CONCLUSIONS: Restylane Perlane provides a more durable esthetic improvement than Hylaform and offers acceptable tolerability.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".