A Study of Clinical Predictors Associated With Intrinsic Sphincter Deficiency in Women With Stress Urinary Incontinence

PURPOSE: Recently, intrinsic sphincter deficiency (ISD) has been identified as one important factor in the outcome of stress urinary incontinence (SUI) related surgery. Clinical factors that can predict ISD are uncommon. The aim of this study was to determine predictive clinical factors for ISD in female patients with SUI. METHODS: The patients were classified into 3 groups according to the value of Valsalva leak point pressure (VLPP)>90 cm H(2)O (anatomical incontinence, AI), between 61 and 90 cm H(2)O (equivocal, EV), and <60 cm H(2)O (ISD). All groups underwent a full examination, history evaluation, physical examination, uroflowmetry, and complete urodynamic study. Univariate analysis was performed by chi-square or t-test for categorical variables, respectively. A multivariate study was performed by Pearson correlation analysis in order to get clinical predictors of VLPP<60 cm H(2)O. Statistical significance was set at P<0.05. RESULTS: There were 3 groups with a total of 189 patients: 56 patients (AI, 29.7%), 64 patients (EV, 33.8%), and 69 patients (ISD, 36.5%). The univariate analysis revealed a significant difference associated with maximal urethral closing pressure (P=0.03) and Stamey classification (P=0.006) between ISD and AI. The more severe the urinary symptom grade, the higher the frequency of ISD. However, the multivariate analysis showed the independent predictor of ISD is only present in grades II and III symptoms in the Stamey classification (P=0.001). CONCLUSIONS: It was found that the more severe the symptoms of urinary incontinence, the higher the possibility of ISD. In other words, the degree of urinary incontinence was found to be one relevant clinical factor in predicting ISD. This finding may help in evaluating and identifying the appropriate surgical technique for EV. Currently, absolute cutoff value to diagnose ISD has not yet been determined. More research is needed to identify clinical factors that can predict ISD.