Causes and management of urogenital fistulas
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: To reviewe the etiology and management of urogenital fistulas at a tertiary care referral center. METHODS: We retrospectively identified all patients with urogenital fistula referred to the King Fahad Medical City, Riyadh, Saudi Arabia, between January 2005 and July 2016 from electronic records. We collected data on age, parity, etiology and type of fistula, radiologic findings, management, and outcome. Results: Of the 32 patients with urogenital fistula identified, 17 (53.1%) had vesicovaginal fistula. The mean parity was 5.9 (0-15). Obstetric surgery was the most common etiology, accounting for 22 fistulas (68.8%). Twenty of these (90.9%) were complications of cesarean delivery, of which 16 (80%) were repeat cesarean delivery. Forty surgical repair procedures were performed: 20 (50%) via an abdominal approach, 11 (27.5%) via a vaginal approach, 7 (17.5) via a robotic approach, and 2 (5%) using cystoscopic fulguration. The primary surgical repair was successful in 23 patients (74%), the second repair in 5 (16.1%), and the third repair in one (3.1%). One fistula was cured after bladder catheterization, and 2 patients are awaiting their third repair. Conclusion: Unlike the etiology of urogenital fistulas in other countries, most fistulas referred to our unit followed repeat cesarean delivery: none were caused by obstructed labor, and only a few occurred after hysterectomy. Most patients were cured after the primary surgical repair.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it