Blunt cannula subcision is more effective than Nokor needle subcision for acne scars treatment
Bibliographic record
Abstract
BACKGROUND AND AIM: A comprehensive study comparing two different modalities, Nokor needle subcision (NNS) and blunt cannula subcision (BCS), for treatment of acne scars, has not been reported previously. The aim was to compare the effectiveness of these two methods based on patient's and doctor's satisfaction measures, in addition to the late complications 3 months postsubcision. METHOD OF INTERVENTION: Patients had 18-65 years old, with acne scars on both malar sides. They were treated at one malar side with NNS and with BCS at another side. They were monitored during the first week, at one and 3 months postintervention. Patient's and two dermatologist's satisfactions were compared during 3 months, for each modality and between modalities. RESULTS: From 34 patients, 29.4%, 55.9%, and 14.7% had mild, moderate, and severe acne scars, respectively. Ecchymosis, nodule formation post-NNS, and edema after BCS were the complications. Patients were satisfied with BCS during 3-month monitoring (P = .021), but not with NNS (P = .353). Physician-1 was satisfied from the outcome of both BCS and NNS procedures (P = .044 and .006, respectively). However, physician-2 was only satisfied with NNS at the month 3 than the month 1 (P = .002). All patients and physicians were significantly more satisfied with BCS than NNS (P = .000). Anyway, at the month 3, physician-2 had no significant different points of view about applied methods (P = .25). DISCUSSION: Considering the complications and satisfaction rates, BCS was more efficient than NNS for acne scar treatment. Then, we suggest BCS as a good replacement for NNS.
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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) | 0.001 | 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) | 0.003 | 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".