The optimal form of urinary drainage after acute retention of urine
Bibliographic record
Abstract
OBJECTIVE: To assess the outcome of different forms of urinary drainage, particularly for urinary tract infection (UTI), operative findings and patient preference, in patients treated for acute urinary retention (AUR). PATIENTS AND METHODS: A feasibility trial was conducted of men presenting with AUR; after a short period of indwelling catheterization (IDC) patients were taught how to use clean intermittent self-catheterization (CISC). Patients who failed this were re-catheterized and taught to manage a valve, or failing this a leg bag, and then discharged home. The patients were followed to assess the occurrence of spontaneous voiding, UTI, findings at prostatectomy and patient satisfaction. RESULTS: The CISC group (34 men) had a higher rate of spontaneous voiding than the IDC group (16 men; 56% vs 25%). The incidence of UTI was 32% in the CISC and 75% in the IDC group. At TURP, 20% in the CISC group had a UTI, compared with 69% in the IDC group. Patients using CISC preferred it and had fewer complications than the IDC group. The CISC group had a similar ability to manage and similar acceptance of their method of drainage as the IDC group. CONCLUSION: CISC is managed and accepted well by patients who can use the technique and results in fewer UTIs. It should be considered in patients who present with AUR, and it may delay surgery.
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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 | 0.001 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".