Fractional CO2 laser for the treatment of Peyronie’s disease
Bibliographic record
Abstract
Introduction: Fractional CO2 laser therapy is used to treat fibrosing conditions similar to Peyronie’s disease (PD). The aim of the study was to evaluate the safety and efficacy of using a fractional CO2 laser in the management of chronic phase PD. Methods: This was a single-site, non-randomized, open-label study using a fractional CO2 laser. Subjects underwent three treatment sessions every six weeks with a fractional CO2 device. Topical triamcinolone was applied immediately after each treatment. Between treatments, patients performed penile modeling three times daily. Penile curvature assessments, self-reported questionnaires, and adverse event screenings were completed at baseline, 24 weeks, and at 52 weeks. Results: Five patients were included in the study. The median baseline penile curvature was 37.0° (interquartile range [IQR] 33.0°, 53.0°), and at 52 weeks, this had reduced to a median curvature to 28.0° (IQR 17.50°, 44.0°, p=0.03), representing a median reduction in penile curvature by 24.3% (IQR 17.0%, 47.5%). The International Index of Erectile Function Overall scores were comparable at baseline and at 52 weeks (median: 59.0, IQR: 42.5, 66.5 vs. median: 60.0, IQR 53.5, 70.0 respectively, p=0.81). Patients did report significant improvement in overall Peyronies’ disease questionnaire (PDQ) scores from baseline to 52 weeks after laser treatment (median 26.0, IQR15.0, 29.5, vs. median: 14.0, IQR 7.0, 22.50, respectively, p=0.03). Four patients reported self-limiting side effects immediately after laser therapy that resolved spontaneously within two weeks. Conclusions: Fractional CO2 laser therapy may serve as a well-tolerated and minimally invasive therapy for PD in the future, with results at 52 weeks being encouraging.
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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 | 0.000 |
| 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 | 0.001 |
| 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".