Can time to failure predict the faulty component in artificial urinary sphincter device malfunctions?

Artificial urinary sphincter malfunctions can occur in any of the individual components. Preoperative identification of the malfunctioning component can be valuable for patient counseling and surgical planning. The optimal strategy for repair of failed artificial urinary sphincter components is debated given the relative rarity of the situation. The aim of the present study was to evaluate the relationship of time to failure with failed artificial urinary sphincter component and to compare our outcomes of specific component versus complete device replacement.

From 1983 to 2011, 1805 artificial urinary sphincter procedures were carried out at Mayo Clinic (Rochester, Minnesota, USA), of which 1072 patients underwent primary artificial urinary sphincter placement. Clinical variables, including time to failure, were evaluated for association with component failure. Bootstrap analysis was used to estimate the differences in time to reach a fixed percentage of component failure.

A total of 115 patients experienced device failure at a median follow up of 4.2 years. Urethral cuff, abdominal reservoir, scrotal pump and tubing malfunction occurred in 53 (4.9%), 26 (2.4%), 11 (1%) and 25 (2.3%) patients, respectively. Increasing age at the time of primary surgery was protective of cuff malfunction (hazard ratio 0.97, P = 0.04). Time to 3% urethral cuff failure outpaced other component failures (P < 0.05). Secondary failure-free rates after whole device versus specific component revisions were comparable (P = 0.38).

Clinical predictors for artificial urinary sphincter failure continue to be difficult to establish. Although single component versus entire device replacement have similar outcomes, if pursuing single component revision, we recommend cuff-first interrogation in devices in place for >3 years, as this represents the most likely component to fail.

International journal of urology : official journal of the Japanese Urological Association. 2017 Nov 26 [Epub ahead of print]

David Y Yang, Brian J Linder, Adam R Miller, Laureano J Rangel, Daniel S Elliott

Department of Urology, Mayo Clinic, Rochester, Minnesota, USA., Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA.

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