Approach to urinary incontinence in women. Diagnosis and management by family physicians.
Bibliographic record
Abstract
UNLABELLED: OBJECTIVE; To outline an approach to diagnosis and management of the types of urinary incontinence seen by family physicians. SOURCES OF INFORMATION: Recommendations for diagnosis are based on consensus guidelines. Treatment recommendations are based on level I and II evidence. Guidelines for referral are based on the authors' opinions and experience. MAIN MESSAGE: Diagnoses of stress, urge, or mixed urinary incontinence are easily established in family physicians' offices by history and gynecologic examination and sometimes a urinary stress test. There is little need for formal diagnostic testing. Management by family physicians (without need for specialist referral) includes lifestyle modification, pelvic floor muscle strengthening, bladder retraining, and pharmacotherapy with muscarinic receptor antagonists. Patients with pelvic organ prolapse might require specialist referral for consideration of pessaries or surgery, but family physicians can provide follow-up care. Women with more complex problems, such as severe prolapse or failed continence surgery, require referral. CONCLUSION: Urinary incontinence is a common condition in women. In most cases, it can be diagnosed and managed effectively by family physicians.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".