High‐velocity pneumatic injection of non‐crosslinked hyaluronic acid for skin regeneration and scar remodeling: A retrospective analysis of 115 patients
Bibliographic record
Abstract
BACKGROUND: Pneumatic-assisted high velocity jet injections are an alternative method for intradermal delivery of hyaluronic acid (HA) and demonstrated efficacy in dermal thickening and scar remodeling with minimal side effects. AIMS: We aimed to investigate the clinical efficacy comparing non-crosslinked HA (NCL-HA) and crosslinked HA (CL-HA) for aesthetic skin concerns. METHODS: We retrospectively analyzed charts of 115 patients treated with jet injected NCL-HA and CL-HA for skin rejuvenation, age-related laxity and rhytidosis, hypertrophic and acne scars and striae. Global Aesthetic Improvement Scale (GAIS) and the 5-grade patient satisfaction scale were used for assessment of the treatment efficacy at the 3-month follow-up. Efficacy was separately analyzed between patients receiving NCL-HA vs. CL-HA. Longevity of treatment effect was measured by the time to voluntary return for repeat treatment. RESULTS: An average of 2.8 treatments was completed per patient with a low incidence of side effects including bruises (7%) and temporary local edema (1%). Patients were highly-satisfied with the treatment results in all categories with the average satisfaction scores of 3.68 (NCL-HA) and 3.76 (CL-HA). An average GAIS score of 1.7 ("much improved") was calculated for neck, décolleté and perioral areas. An overall GAIS score averaged as 1.78 (NCL-HA) and 1.6 (CL-HA). Longevity of the effect averaged 13.1 months for NCL-HA and 13.2 months for CL-HA groups. CONCLUSION: Our retrospective data showed similar significant improvement of all aesthetic skin concerns in 115 subjects treated with either NCL-HA or CL-HA delivered intradermally by a high velocity jet-injector device with minimal downtime, pain or side-effects.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".