Outcomes of Urethroplasty for Synchronous Anterior Urethral Stricture Utilizing the Trauma and Urologic Reconstruction Network of Surgeons Length, Segment and Etiology Anterior Urethral Stricture Classification System.

To describe the characteristics, management, and functional outcomes of patients with synchronous urethral stricture disease (SUSD) utilizing a multi-institutional cohort. Data were collected and assessed from a prospectively maintained, multi-institutional database. Patients who underwent anterior urethroplasty for urethral stricture disease (USD) were included and stratified by the presence or absence of SUSD. USD location and etiology were classified according to the Trauma and Urologic Reconstruction Network of Surgeons Length, Segment and Etiology Anterior Urethral Stricture Classification System. Anterior urethroplasty techniques were recorded for both strictures. Functional failure was compared between groups. One thousand nine hundred eighty-three patients were identified, of whom, 137/1983 (6.9%) had SUSD. The mean primary stricture length for patients with SUSD was 3.5 and 2.6 cm for the secondary stricture. Twelve anterior urethroplasty technique combinations were utilized in treating the 27 different combinations of SUSD. Functional failure was noted in 18/137 (13.1%) patients with SUSD vs 192/1846 (10.4%) patients with solitary USD, P = .3. SUSD was not associated with increased odds of functional failure. S classifications: S1b, P = .003, S2a, P = .001, S2b, P = .01 and S2c, P = .02 and E classifications: E3a, P = .004 and E6, P = .03, were associated with increased odds of functional failure. Repair of SUSD in a single setting does not increase the risk of functional failure compared to patients with solitary USD. Increasing S classification, S1b through S2c and E classifications E3a and E6 were associated with increased functional failure. This reinforces the importance of the Trauma and Urologic Reconstruction Network of Surgeons Length, Segment and Etiology Anterior Urethral Stricture Classification System as a necessary tool in large-scale multi-institutional analysis when assessing highly heterogenous patient populations.

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