FPSUND: a new clinical classification of urinary incontinence.
Bibliographic record
Abstract
Urinary incontinence is a frequent condition that is usually clinically classified into three main subgroups: urge, stress and mixed. The latter, which can account for up to 50% of the patients, is notoriously heterogeneous. It is one of the reasons why the reports of therapeutic approaches to treat incontinence vary in the medical literature and it also explains the difficulty to compare results between studies. In an attempt to address this problem and to clarify the field of urinary incontinence, we have developed new clinical classification of urinary incontinence (FPSUND) where each symptom related to incontinence is rated from 0 (no symptoms) to 3 (severe symptoms). In this acronym, "F" stands for frequency of micturition, "P" for the use of protection, "S" for the stress component of incontinence, "U" for urgency, "N" for the number of nocturnal micturition and "D" for the number of diurnal micturition. Urologists from nine different centers across Canada were asked to evaluate female patients suffering from urinary incontinence using the FPSUND classification. A total of 148 women, aged 18 to 70, suffering from urinary incontinence were thus enrolled in the study. A second, independent evaluation of the same patients was performed by registered nurses or by urodynamic technicians. The reproducibility of the classification between two observers, as measured by the Weighted Kappa score was excellent, with kappa scores between 0.47 and 0.74 (p<0.05). Overall, the users of the classification found it very easy to use in a clinical setting. We would like to propose the FPSUND classification of urinary incontinence as a useful mean to evaluate patients suffering from incontinence and as a way to assess treatment outcome.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".