STRIVING TOWARDS A CONSENSUS-BASED PERI-OPERATIVE CARE PROTOCOL FOR PENILE IMPLANTS IN PHALLOPLASTY; A DELPHI APPROACH
Bibliographic record
Abstract
Abstract Objectives Over the years there has been an increase in the demand for penile implant procedures after phalloplasty in transgender men. These procedures require specific knowledge and surgical skills as the anatomy of the neophallus differs from that of the cisgender penis. Considering the high rates of complications and need for re-operations, surgeons in this field must strive to improve the surgical outcomes of these procedures. This study describes our approach to develop a consensus based protocol for peri-operative care for penile implants in trans gender men who have previously undergone phalloplasty. Methods A Delphi approach was used to construct and reach a consensus on a clinical guideline for pre, peri- and postoperative care surrounding penile prosthesis implantation surgery after phalloplasty. Surgeons who perform this procedure in this group specifically were recruited to participate. Results Surgeons from 6 European countries (Belgium, France, Germany, The Netherlands, Serbia and the United Kingdon), 2 North American countries (Canada, United States of America) and 1 South American country (Argentina) agreed to participate. An expert steering group convened for a panel discussion in order to formulate the first version of the guideline. Subsequently, the guideline was shared with the remaining participants voted anonymously in agreement or disagreement using 5-point Likert scales on each recommendation in the guideline. There are two rounds of voting, and consensus is reached when >80% of the panel agrees with each recommendation. Conclusions The Deplhi approach is a suitable way to reach an international consensus amongst experts in the field of gender affirming surgery. An international panel agreed to participate, affirming their recognition for such a protocol. Conflicts of Interest None of the authors have any conflicts of interest to disclose.
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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 | 0.352 | 0.242 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".