2024 Canadian Urological Association guideline: Female stress urinary incontinence
Bibliographic record
Abstract
We decided to use a question-and-answer format to provide brief, accessible, and practical answers to common questions addressing the evaluation and management of FSUI.The guideline panel was created to provide representation from a mix of community and academic urologists and allied health professionals from across Canada, in keeping with the CUA guideline rules.Disagreements during the guideline process were resolved by consensus-building.Conflicts of interests for the authors are included at the end of the guideline.The views or interests of the CUA did not influence the final set of recommendations.The guideline panel was led by Dr. Kevin Carlson and Dr. Blayne Welk.The group first met virtually in December 2021.Objectives to guide the development of this document were agreed upon: 1) to be comprehensive without replicating existing evidence reviews; 2) to provide evidence-based and expert-based opinions on relevant topics within FSUI; and 3) to address the unique needs of Canadian urologists where appropriate.All guideline members were asked to submit relevant topics that could be addressed in a questionand-answer format, and the final list of questions was agreed upon by the panel.Further feedback was received from CUA members at the 2022 CUA annual meeting.Individual sections were assigned to members, with another panel member acting as primary reviewer.Members reviewed publications relevant to their question using a combination of PubMed, Medline, and/or EMBASE database searches, with an emphasis on identifying existing systematic reviews, and then evaluating any new evidence that was published after the existing review's search dates.No set limits based
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".