The Effect of Microneedling on Acne Scars
Bibliographic record
Abstract
The Effect of Microneedling on Acne ScarsMoataz Bellah M. El-Domyati MD, Rasha T. A. Abdel-Aziz MD, Maha Mohamed-Elsayed MSc. Department of Dermatology, STD’s and Andrology, Faculty of Medicine, Minia University, Minia, EgyptAbstractBackground: Postacne scarring is disfiguring. Multiple modalities for treatment of acne scars have emerged and microneedling with dermaroller is one of them.Objectives: To evaluate the efficacy of microneedling treatment for atrophic facial acne scars.Methods: Ten patients with different types of atrophic acne scars were subjected to three months of skin microneedling treatment (six sessions at two-week intervals). Patients were photographed at baseline as well as one and three months from the start of treatment.Results: Compared to the baseline, patients’ evaluations revealed significant clinical improvement in atrophic post-acne scars in response to skin microneedling (p= 0.02).Conclusion: Microneedling is a simple and cheap, means of treatment modality for acne scars remodulation with little downtime, satisfactory results and with the advantage of being a relatively risk-free.Key words: Acne scars, Microneedling.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".