Correlation of Urine Loss after Catheter Removal and Early Continence in Men Undergoing Radical Prostatectomy
Bibliographic record
Abstract
Background: To determine the correlation between urine loss in PAD-test after catheter removal, and early urinary continence (UC) in RP treated patients. Methods: Urine loss was measured by using a standardized, validated PAD-test within 24 h after removal of the transurethral catheter, and was grouped as a loss of <1, 1–10, 11–50, and >50 g of urine, respectively. Early UC (median: 3 months) was defined as the usage of no or one safety-pad. Uni- and multivariable logistic regression models tested the correlation between PAD-test results and early UC. Covariates consisted of age, BMI, nerve-sparing approach, prostate volume, and extraprostatic extension of tumor. Results: From 01/2018 to 03/2021, 100 patients undergoing RP with data available for a PAD-test and early UC were retrospectively identified. Ultimately, 24%, 47%, 15%, and 14% of patients had a loss of urine <1 g, 1–10 g, 11–50 g, and >50 g in PAD-test, respectively. Additionally, 59% of patients reported to be continent. In multivariable logistic regression models, urine loss in PAD-test predicted early UC (OR: 0.21 vs. 0.09 vs. 0.03; for urine loss 1–10 g vs. 11–50 g vs. >50 g, Ref: <1 g; all p < 0.05). Conclusions: Urine loss after catheter removal strongly correlated with early continence as well as a severity in urinary incontinence.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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 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".