Efficacy and safety of nanofractional radiofrequency in treatment of atrophic acne scars: A retrospective analysis of 5 years
Bibliographic record
Abstract
Objectives: The objective of the study was to evaluate the efficacy of nanofractional radiofrequency in the treatment of acne scars. Material and Methods: In this 5-year retrospective study, adults with atrophic acne scars on their cheeks underwent four monthly sessions of nanofractional radiofrequency treatment (Venus Viva™, Venus Concept Inc., Toronto, Canada). Follow-up occurred 2 months after the last session. Clinical photographs were assessed by physicians and patients, and two dermatologists performed independent subjective analysis. Side effects, including pain, erythema, post-inflammatory pigmentation, and burning, were recorded after each session. Results: In the analysis, 65 patients were included, with a mean age of 27.6 ± 5.6 years. Among them, 67.7% had Fitzpatrick skin type IV. The mean satisfaction score at the end of the study was 7.33 ± 1.31, and 55.4% of patients scored >7. Of the 24 patients with scars lasting less than 6 months, 70.8% experienced >75% improvement. For patients with macular scars (11 in total), 72.7% saw >75% improvement. Transient pain and swelling were observed in all patients, while 32 out of 65 reported a burning sensation lasting <2 h. Conclusion: Nanofractional radiofrequency is highly effective, with positive responses in macular to mild scars. Scar duration is inversely related to treatment response. It is safe with transient, controlled 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".