Efficacy and safety of ATX‐101 as a treatment for submental fullness: A retrospective analysis of two aesthetic practices
Bibliographic record
Abstract
BACKGROUND: Submental fullness (SMF) is a common cosmetic concern that can have negative impact on one's self-esteem. ATX-101 has shown promise as a minimally invasive treatment for SMF correction in clinical trials. AIMS: To assess the safety and efficacy of ATX-101 for SMF correction. PATIENTS/METHODS: This was a retrospective review of 90 patients from two aesthetic practices who received ATX-101 injections for SMF (January 2016-August 2017). There were no exclusion criteria. Initial SMF severity was assigned using standardized photographs and a validated 5-point scale. Eighty one patients subsequently answered questionnaires regarding improvement, satisfaction, and adverse effects. Degree of SMF correction was also evaluated by the investigator and a blinded reviewer. RESULTS: Eighty one patients (mean initial submental fullness severity 1.6) received a mean of 1.84 ATX-101 treatment sessions using a median of 2.0 vials per treatment (mean 3.02, range 1-9). Mean Physician Global Aesthetic Improvement Scale scores were 2.73 and 2.25, after the first and second treatments, respectively (P = .04). Mean Subject Goal Aesthetic Improvement Scale scores were 2.7 and 2.25 after the first and second treatments, respectively (P = .01). Sixty-seven percentage of patients were "somewhat" or "very" satisfied. Adverse events were transient and limited to the treatment area. CONCLUSION: Patients achieved progressive improvement in SMF after the 1st and 2nd treatments, as judged by patients themselves, investigators, and blinded evaluators. These results of SMF correction suggest that significant benefit can be obtained with proper dosing at the initial visit. These data support the efficacy and safety profile of ATX-101 use for SMF correction.
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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 | 0.001 | 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".