Botulinum Neurotoxin and Its Potential Role in the Treatment of Erectile Dysfunction
Bibliographic record
Abstract
INTRODUCTION: Botulinum toxin type A (BoNT-A) has been used to treat several striated and smooth muscle disorders. During the past year, human and animal studies conducted in Egypt and Canada by two different groups of investigators have suggested a possible role for the intracavernosal injection of BoNT-A in the treatment of erectile dysfunction (ED). AIM: To discuss BoNT-A and its current medical uses, the rationale for its new potential use in the treatment of ED, and the available evidence and concerns. METHODS: A literature search was conducted. This review was based on the available studies presented at the European Society for Sexual Medicine, Sexual Medicine Society of North America, and International Society for Sexual Medicine meetings in 2016 by the two groups. MAIN OUTCOME MEASURES: Sinusoidal diameter; penile color Doppler study; Erection Hardness Score; Sexual Health Inventory for Men questionnaire; and Sexual Encounter Profile questions 2 and 3. RESULTS: Two human studies conducted by the authors and two animal studies (one from the authors' group and one from Canada) were reviewed. These seemed to suggest generally favorable outcomes with the use of BoNT-A in the treatment of ED. CONCLUSION: BoNT-A could be a potential therapy for ED. In addition to the findings of the three pilot studies, larger multicenter trials need to be conducted to further explore the true therapeutic efficacy and clinical safety of BoNT-A in the treatment of ED. Ghanem H, Raheem AA, AbdelRahman IFS, et al. Botulinum Neurotoxin and Its Potential Role in the Treatment of Erectile Dysfunction. Sex Med Rev 2018;6:135-142.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".