Postoperative Voiding Dysfunction: The Preferred Method for Catheterization
Bibliographic record
Abstract
OBJECTIVES: Bladder drainage can be achieved by clean intermittent self-catheterization (CISC), transurethral indwelling catheterization (TIC), or with a suprapubic tube (SPT). The primary objective of this study was to determine patient preference for catheter type in the management of potential voiding dysfunction after pelvic organ prolapse (POP) surgery. METHODS: Between 2012 and 2016, patients scheduled for POP surgery were recruited into the study. Before surgery, patients were informed of the potential for postoperative voiding dysfunction and the catheter choices were discussed. Each patient's choice was recorded along with baseline information, surgery performed, and perioperative details. After surgery, voiding dysfunction, length of catheter use, scores on a catheter satisfaction questionnaire, as well as uroflowmetry and urine culture testing were assessed. RESULTS: Of those recruited to the study (N = 150), 6.7% chose CISC, 7.3% chose TIC, and 86% chose SPT. Catheter satisfaction score 1 week after surgery was significantly better for SPT compared with CISC and TIC (P = 0.005). In addition, at week 1, 33% of CISC, 25% of TIC, and 13% of SPT had a PVR of more than 30% (P = 0.002) on uroflowmetry, and 33% of CISC, 50% of TIC, and 24% of SPT had a positive urine culture (P = 0.05). CONCLUSIONS: This study has shown that patients prefer SPT over CISC and TIC for management of voiding dysfunction after POP surgery. Use of SPT showed better satisfaction rates, better uroflowmetry results, and lower infection rates 1 week after surgery. Patient preference is an important factor in this decision and can help facilitate a clinical approach.
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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 | 0.002 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".