A randomized, split‐face, double‐blind, comparative study of the safety and efficacy of small‐ and large‐particle hyaluronic acid fillers for the treatment of nasolabial folds
Bibliographic record
Abstract
BACKGROUND: Injections of hyaluronic acid (HA) for tissue augmentation are one of the most common aesthetic treatments performed worldwide. However, few studies have compared the safety and efficacy of small- and large-particle HA (SP-HA; LP-HA). AIM: To assess and compare the safety and efficacy of SP-HA and LP-HA for the correction of nasolabial folds (NLFs). METHODS: A prospective, split-face, triple-blind study design was used. Ten female subjects were recruited. Patients underwent treatment at baseline, an optional touch up at Week 2, and a follow-up visit at Week 4. At weeks 2 and 4, a blinded reviewer assessed the patients using the Global Aesthetic Improvement Scale (GAIS) and Wrinkle Severity Rating Scale (WSRS); and subjects completed the Patient Satisfaction Questionnaire (PSQ). At all visits, 3-dimensional imagery and ultrasonography of patients' NLFs were captured. Adverse events (AEs) were evaluated by the Investigator and recorded by subjects in diaries. RESULTS: The GAIS response rate, defined as ≥ "improved" from baseline, was between 90 (2 weeks) and 100% (1 month) for SP-HA and was 100% for LP-HA, at both visits. Paired-samples t tests revealed significant differences in the change in WSRS scores between groups, at both visits (P < .01). Differences in the clinical effect and lifting capacity of both products were observed in 3-dimensional imagery and ultrasonography. Treatment volumes varied, with 61.32% more SP-HA being required than LP-HA for achieving a ≥ one-grade WSRS improvement. There were no severe AEs throughout the trial, nor AEs related to the investigational device. CONCLUSIONS: LP-HA demonstrates better efficacy for correcting bony resorption in the nasal pyriform region.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".