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  • Title: Can we predict urinary stress incontinence by using demographic, clinical, imaging and urodynamic data?
    Author: Wlaźlak E, Surkont G, Shek KL, Dietz HP.
    Journal: Eur J Obstet Gynecol Reprod Biol; 2015 Oct; 193():114-7. PubMed ID: 26291686.
    Abstract:
    OBJECTIVE: It has been claimed that urethral hypermobility and resting urethral pressure can largely explain stress incontinence in women. In this study we tried to replicate these findings in an unselected cohort of women seen for urodynamic testing, including as many potential confounders as possible. STUDY DESIGN: This study is a retrospective analysis of data obtained from 341 women. They attended for urodynamic testing due to symptoms of pelvic floor dysfunction. We excluded from the analysis women with a history of previous anti-incontinence and prolapse surgery. All patients had a standardised clinical assessment, 4D transperineal pelvic floor ultrasound and multichannel urodynamic testing. Urodynamic stress incontinence (USI) was diagnosed by multichannel urodynamic testing. Its severity was subjectively graded as mild, moderate and severe. Candidate variables were: age, BMI, symptoms of prolapse, vaginal parity, significant prolapse (compartment-specific), levator avulsion, levator hiatal area, Oxford grading, midurethral mobility, maximum urethral pressure (MUP), maximum cough pressure and maximum Valsalva pressure reached. RESULTS: On binary logistic regression, the following parameters were statistically significant in predicting urodynamic stress incontinence: age (P=0.03), significant rectocele (P=0.02), max. abdominal pressure reached (negatively, P<0.0001), midurethral mobility (P=0.0004) and MUP (negatively, P<0.0001). On multivariate analysis, accounting for multiple interdependencies, the following predictors remained significant: max. abdominal pressure reached (negatively, P<0.0001), cough pressure (P=0.006), midurethral mobility (P=0.003) and MUP (negatively, P<0.0001), giving an R(2) of 0.24. CONCLUSIONS: Mid-urethral mobility and MUP are the main predictors of USI. Demographic and clinical data are at best weak predictors. Our results suggest the presence of major unrecognised confounders.
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