A Multicenter, Retrospective Evaluation of Tissue Stabilized-Guided Subcision in the Management of Cellulite
Bibliographic record
Abstract
BACKGROUND: The first FDA-cleared, long-lasting, minimally invasive device for improving the appearance of cellulite was recently launched in Canada as a novel, tissue stabilized-guided subcision (TS-GS) system (Cellfina, Merz North America, Inc., Raleigh, NC). Clinicians from 2 of the first Canadian sites offering this procedure were interested in evaluating treatment efficacy and patient satisfaction after its first year on the market. OBJECTIVES: The authors sought to evaluate the efficacy of TS-GS and the level of patient satisfaction associated with the procedure. METHODS: Medical charts of female patients treated with the TS-GS system in 2017 were retrospectively analyzed at 2 Canadian centers. Measurements at baseline and 3 months posttreatment were assessed for patient satisfaction and physician-rated efficacy. Patient satisfaction was assessed using a 5-point Likert-type scale, and efficacy was evaluated through physician review of 2-deminsional and 3-dimensional photography, the Nürnberger-Müller Scale for cellulite, and the Global Assessment of Improvement Scale. RESULTS: We reviewed 25 patient charts. At month 3, 95.6% of patients were satisfied with treatment results and physician evaluations revealed that on average, patients displayed a 1-point improvement in their cellulite grades. Moreover, Global Assessment of Improvement Scale scores indicated that all patients had visible improvement in the global appearance of cellulite. No serious adverse events were observed within 3 months postprocedure. CONCLUSIONS: The physician ratings, patient satisfaction, and photographic evidence support the efficacy of the TS-GS system to manage grades 1 to 3 cellulite in women's thighs and buttocks. These findings indicate the safety of the TS-GS system. Level of Evidence: 4.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".