Streamlined Facial Rejuvenation: A Randomized Split-Face Trial of Premixed Intradermal Botulinum Toxin Type A and Hyaluronic Acid Biorevitalization
Bibliographic record
Abstract
BACKGROUND: Botulinum toxin type A (BoNT-A) effectively treats dynamic wrinkles but offers limited direct improvement in skin quality. Hyaluronic acid (HA)-based biorevitalization enhances hydration, firmness, and radiance; however, high-quality trials evaluating their combined use under controlled conditions are scarce. OBJECTIVES: To compare the efficacy and safety of a single-session, premixed intradermal BoNT-A with HA biorevitalization (NCTF 135HA) vs BoNT-A alone for facial rejuvenation. METHODS: In this prospective, randomized, double-blind, split-face trial, 52 participants (73.1% female; mean age 44.5 ± 4.7 years) received BoNT-A + NCTF 135HA on one facial side and BoNT-A alone contralaterally. Outcomes at Day 60 included Wrinkle Severity Rating Scale (WSRS), visual analog scales for hydration, firmness, radiance, and tone homogeneity, and Global Aesthetic Improvement Scale (GAIS) scores from blinded evaluators and patients. Patient satisfaction and safety were also assessed. RESULTS: Mean WSRS reduction was greater with the combination (Δ = 2.33 ± 0.70) vs BoNT-A alone (Δ = 1.34 ± 0.59; d = 1.35, P < .001). Hydration increased significantly only on the combination side (Δ = 3.71 ± 1.48; d = 2.35, P < .001), with larger gains also in firmness (d = 2.11), tone homogeneity (d = 1.51), and radiance (d = 1.16; all P < .001). GAIS scores favored the combination (patients: 2.21 ± 0.67 vs 0.81 ± 0.79; evaluators: 2.02 ± 0.73 vs 0.54 ± 0.69; P < .001). At Day 60, 86.5% noticed a side-to-side difference, 94.2% would repeat, and 94.2% would recommend the combination; comfort was rated tolerable by 67.3%. Adverse events were mild and transient (pinpoint bruising 78.8%, tightness 11.5%, swelling/erythema 13.5%). CONCLUSIONS: Premixed intradermal BoNT-A with NCTF 135HA achieved superior wrinkle reduction, enhanced skin quality, and greater patient satisfaction than BoNT-A alone, with minimal downtime and an excellent safety profile.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".