Long-term Follow-up of Exstrophy-epispadias Complex from a Lower-middle Income Country: A Case Report and Review of the Literature
Bibliographic record
Abstract
Bladder exstrophy-epispadias complex (EEC) is a rare congenital defect where the abdominal muscles and bones fail to close in the mid-pelvis. It is crucial to understand the health-related quality of life (QOL) of exstrophy patients who have undergone multiple correctional surgeries. We herein discuss a case of bladder EEC that was repaired through a series of procedures at a resource-limited hospital in Karachi, Pakistan. A 21-year-old male, who was born with EEC, underwent bladder augmentation, Mitrofanoff procedure, bladder neck reconstruction, ureter implantation and a right nephrectomy in a single one-stage procedure during late childhood for urinary incontinence. However, this required a further revision because the urinary incontinence persisted, with difficulty in catheterizing the Mitrofanoff channel. On follow-up after 10 years, our patient currently describes normal QOL with near-normal sexual function. Validated questionnaires for QOL, erectile dysfunction, incontinence and prostatic function were used to assess the patient's post-operative status in these domains. Through our report, we conclude that such patients can have a normal QOL by means of a holistic multidisciplinary management, which includes timely surgical corrections along with an additional focus on the psycho-social and sexual aspects of this condition.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".