Gender‐affirming care in urology: emergency care of the gender‐affirming surgical patient—what the primary urologist needs to know
Bibliographic record
Abstract
OBJECTIVE: To present a narrative review of fundamental information needed to manage postoperative complications in patients who have undergone genital gender-affirming surgery (GAS). METHODS: A narrative review was performed using the following keywords: 'gender-affirming surgery', 'complications', 'emergency', 'postoperative'. Articles were included after being reviewed by two primary authors for relevance. Four clinicians with significant experience providing both primary and ongoing urological care to patients after GAS were involved in article selection and analysis. RESULTS: The most common feminising genital GAS performed is a vaginoplasty. The main post-surgical complications seen by urologists include wound healing complications, voiding dysfunction, postoperative bleeding, vaginal stenosis, acute vaginal prolapse and graft loss, rectovaginal fistula, and urethrovaginal fistula. The most common masculinising genital GAS options include metoidioplasty and phalloplasty. Complications for these surgeries include urethral strictures, urethral fistulae, and urethral diverticula. Penile implants may also accompany phalloplasties and their complications include infection, erosion, migration, and mechanical failure. CONCLUSION: Genital GAS is increasing, yet there are still many barriers that individuals face not only in accessing the surgeries, but in receiving follow-up care critical for optimal outcomes. Improved education and training programmes would be helpful to identify and manage postoperative complications. Broader cultural level changes are also important to ensure a safe, gender-inclusive environment for all patients.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".