Bibliographic record
Abstract
CONTEXT: Urinary incontinence is a prevalent condition and treatment options can depend on what type of incontinence is present. OBJECTIVE: To systematically review the evidence about the most accurate way to determine the type of urinary incontinence during an office assessment. DATA SOURCES: A search of MEDLINE using Ovid (1966-July 2007) and EMBASE (1980-July 2007), and the bibliographies of retrieved articles to identify relevant studies. Search terms included urinary incontinence, diagnostic tests, medical history taking, physical examination, cough stress test, and urodynamics. STUDY SELECTION: English-language articles were identified that addressed the office diagnosis of urinary incontinence in adults, in which data was not limited to case reports. Cohort studies of patients undergoing history, physical examination, and/or office procedures (excluding urodynamics) for diagnosing the type of urinary incontinence were included. Case-control studies were considered when there was insufficient data available from cohort studies. The accepted reference standard for categorization of incontinence type was diagnosis confirmed by an expert, urodynamic studies, or both. DATA EXTRACTION: Two investigators independently appraised study quality and extracted relevant data. Minimum inclusion criteria were completion of an appropriate reference standard in all patients and the ability to extract relevant data. DATA SYNTHESIS: Forty articles were identified for inclusion. A random-effects model was used for quantitative synthesis. Minimal data was available for men. In women, simple questions modestly helped diagnose stress urinary incontinence (summary positive likelihood ratio [LR], 2.2; 95% confidence interval [CI], 1.6-3.2; summary negative LR, 0.39; 95% CI, 0.25-0.61) but are more helpful in diagnosing urge urinary incontinence (summary positive LR, 4.2; 95% CI, 2.3-7.6; summary negative LR, 0.48; 95% CI, 0.36-0.62). A positive bladder stress test may help diagnose stress urinary incontinence (summary LR, 3.1; 95% CI, 1.7-5.5); however, a negative test is not as useful (summary LR, 0.36; 95% CI, 0.21-0.60). A systematic assessment combining the history, physical examination, and results of bedside tests to establish a clinical diagnosis appears to be of modest value in diagnosing stress urinary incontinence (summary positive LR, 3.7; 95% CI, 2.6-5.2; summary negative LR, 0.20; 95% CI, 0.08-0.51). The systematic assessment is less helpful in diagnosing urge urinary incontinence (summary positive LR, 2.2; 95% CI, 0.55-8.7; summary negative LR, 0.63; 95% CI, 0.34-1.17). CONCLUSIONS: The most helpful component for diagnosing urge urinary incontinence is a history of urine loss associated with urgency. A bladder stress test may be helpful for diagnosing stress 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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".