Evaluation of Upright Magnetic Resonance Imaging in Female Genuine Stress Urinary Incontinence before and after MonarcR Bladder Neck Suspension: A Prospective Cohort Study
Bibliographic record
Abstract
AimCurrent methods used to assess patient suitability for bladder neck suspension prior to surgery are limited due to their inability to examine patients in physiologic positions.The purpose of this study was to examine the usefulness of upright magnetic resonance imaging (MRI) in the evaluation of patients with genuine stress urinary incontinence (GSUI) prior to undergoing Monarc R bladder neck suspension. Materials and MethodsTwenty-seven female patients with known GSUI were selected to participate in the study.Each patient was asked to complete an incontinence symptom score and then have 300 ml of sterile water instilled into their bladder.While standing in an upright MRI scanner a T2-weighted image at 0.6 tesla was then obtained while at rest and then undergoing standardized Valsalva maneuver.Special attention was then given to the downward movement of the H-line against the M-line.Measurements were taken to determine excursion of the H-line against the M-line.The procedure was then repeated for each patient three-months after surgery.The change in H-line excursion following surgery was compared to the change in symptom score using Spearman's rank correlation test. ResultsA positive correlation was found between the pre-and post-operative improvements in international consultation on incontinence questionnaire female lower urinary tract symptoms modules (ICIQ-FLUTS) and the post-operative reduction of excursion of the pelvic floor.These correlations were found to be statistically significant (p<0.001) using Spearman's rank correlation test. ConclusionA greater degree of pelvic floor prolapse visible on magnetic resonance imaging (MRI) with a standardized Valsalva maneuver prior to Monarc R bladder neck suspension surgery predicts for better patient symptom score outcomes as determined by ICIQ-FLUTS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".