Urinary Urgency and Urge Incontinence in a Transgender Man: A Case Study
Bibliographic record
Abstract
Background: The literature regarding lower urinary tract symptoms (LUTS) in the transgender and non-binary population is scarce. There are emerging data surrounding the impact of hormonal, surgical, and behavioral factors for this population; however, direct impact on pelvic floor function is still lacking. Case Description: This case report describes a 39-year-old transgender man referred to pelvic health rehabilitation for urinary urgency and urge urinary incontinence (UUI), which were limiting participation in occupational activities. The plan of care utilized a multimodal treatment approach, incorporating behavioral techniques, manual therapy, therapeutic exercise, and neuromodulation via sacral transcutaneous electrical nerve stimulation to improve functional outcomes. Outcomes: Clinically significant improvement on the National Institutes of Health Chronic Prostatitis Severity Index score from 13 to 3, reduction in urinary urgency from daily to weekly, and reduction in UUI from weekly to none were reported upon discharge. Functional outcomes included return to prior level of occupational participation. Discussion: This case report represents a successful course of pelvic health rehabilitation for LUTS in a transgender man. This case aims to begin bridging the significant gap in the literature regarding treatment of LUTS among transgender men with hormonal and post-operative considerations.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".