Success rates of patients with poor emptying on clean intermittent catheterization.
Bibliographic record
Abstract
INTRODUCTION: Clean intermittent catheterization (CIC) theoretically reduces incontinence, urinary tract infections (UTIs) and lower urinary tract symptoms (LUTS) in the face of poor emptying. It is unclear whether all patients realize these benefits or if CIC is only helpful for some. MATERIALS AND METHODS: A retrospective review of 321 patients all of whom underwent urodynamic study prior to starting CIC for impaired emptying. Success was considered to be no incontinence, no UTIs, and no LUTS while performing CIC. Patients who did not meet these criteria or who stopped CIC for whatever reason were classified as failures. RESULTS: The mean duration of follow up was 4.3 years (+/- 4.4 years). Overall 51% of the cohort was classified as a success. Among those patients started on CIC to treat incontinence, recurrent UTIs or LUTS the success rate was 43%. We identified the comorbidity of diabetes mellitus, the use of anticholinergic medications, the need for a homecare nurse to perform the CIC, and a post-void residual (PVR) of <300 cc at initial urodynamics to be independently associated with failure on CIC. CONCLUSIONS: CIC resolved incontinence, recurrent UTIs, and LUTS in some but not all patients with impaired emptying. We identified characteristics associated with failure on CIC. Our study has provided some direction as to those individuals most and least likely to benefit from adopting this mode of bladder management for poor emptying.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".