Early postoperative treatment of mastectomy scars using a fractional carbon dioxide laser: a randomized, controlled, split-scar, blinded study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Mastectomy leaves unsightly scarring, which can be distressing to patients. Laser therapy for scar prevention has been consistently emphasized in recent studies showing that several types of lasers, including fractional ablation lasers, are effective for reducing scar formation. Nonetheless, there are few studies evaluating the therapeutic efficacy of ablative CO2 fractional lasers (ACFLs). METHODS: This study had a randomized, comparative, prospective, split-scar design with blinded evaluation of mastectomy scars. Fifteen patients with mastectomy scars were treated using an ACFL. Half of each scar was randomized to "A," while the other side was allocated to group "B." Laser treatment was conducted randomly. Scars were assessed using digital photographs of the scar and Vancouver scar scale (VSS) scores. Histological assessments were also done. RESULTS: The mean VSS scores were 2.20±1.28 for the treatment side and 2.96±1.40 for the control side. There was a significant difference in the VSS score between the treatment side and the control side (P=0.002). The mean visual analog scale (VAS) scores were 4.13±1.36 for the treatment side and 4.67±1.53 for the control side. There was a significant difference in VAS score between the treatment side and the control side (P=0.02). CONCLUSIONS: This study demonstrated that early scar treatment using an ACFL significantly improved the clinical results of the treatment compared to the untreated scar, and this difference was associated with patient satisfaction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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) | 0.000 | 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 it