Shock Wave Therapy for Peyronie’s Disease—Learning from the Past and Looking Into the Future
Bibliographic record
Abstract
Peyronie’s disease (PD) is a wound-healing disorder often characterized by the triad of penile pain, curvature, and sexual dysfunction at initial presentation.1 Peyronie’s plaque pathogenesis remains incompletely elucidated but is thought to arise from abnormal extracellular matrix production. Studies suggest that PD prevalence is as high as 9% in the general population and higher in patients with diabetes or after radical prostatectomy.2 A broad spectrum of treatments for PD are available including: surveillance, traction devices, intralesional injections and surgical interventions.3 There is an ever-growing interest in practical, low cost, state-of-the-art, minimally invasive approaches to manage this common problem. Low-energy extracorporal shockwave therapy (Li-ESWT) is a promising treatment modality in regenerative medicine. The precise mechanism of action behind it is largely unknown. The theory of mechano-transduction may explain its effect; direct mechanical stimulation of the tissues induces changes to the activity of cell membrane channels and modifies gene expression.4 Animal trials using Li-ESWT have indicated revascularization after a heart attack and stimulation of wound healing. Shockwaves are usually generated by applying electrohydraulic, electromagnetic, or piezoelectric energy. Whether shockwave treatment results in exclusively local effects or induces systemic alterations, remains unclear. Some studies demonstrated that shockwave treatment rapidly release substance P and prostaglandin E2.5 Other studies have reported nitric oxide (NO) and vascular endothelial growth factor as the principal mediators after mechanical stimulation.6,7
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".