Female Urinary Retention: Observations from a Retrospective Case Note Review
Bibliographic record
Abstract
Background and Objective There are no current guidelines to manage female retention patients. We aimed to see if a standardized approach could be used to manage these patients. Methods Between October 2014 and September 2016, all female patients with urinary retention admitted under a urology consultant were reviewed. Results A total of 46 females had a single episode of urinary retention whilst 19 females had recurrent episodes. The commonest cause for a single episode of retention was attributed to anesthesia (general/spinal) (n=9), constipation (n=9) and medication use (n=4). Most of these women (95%) voided on the first attempt fol-lowing catheter removal. In the absence of any neurological symptoms, pelvic ultrasound was the only investigation that revealed any underlying pathology in female retention patients. A pelvic mass was identi-fied in 3 (4.5%) patients. Conclusion Females with an isolated episode of retention, with an obvious precipitating cause identified during full history and examination, could proceed directly to a nurse-led trial of catheter removal without the need for any further urology review. Others should undergo a pelvic ultrasound and review by a urologist. In our opinion, females with recurrent unexplained episodes of urinary retention should be referred for a trial of sacral neuromodulation if considered appropriate.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".