Using Artificial Intelligence to Predict Surgical Shunts in Men with Ischemic Priapism.

PURPOSE Ischemic priapism is a urological emergency that requires prompt intervention to preserve erectile function. Characteristics that influence escalation to surgical intervention remain unclear. Our objective was to identify factors and develop machine learning models to predict which men presenting with ischemic priapism will require shunting. METHODS We identified men with ischemic priapism admitted to the emergency department of our large county hospital between January 2010 and June 2019. We collected patient demographics, etiology, duration of priapism prior to intervention, interventions attempted, and escalation to shunting. Machine learning models were trained and tested using R to predict which patients require surgical shunting. RESULTS In total of 334 encounters of ischemic priapism were identified. The majority resolved with intracavernosal phenylephrine injection and/or cavernous aspiration (78%). Shunting was required in 10% of men. Median duration of priapism before intervention was longer for men requiring shunting than for men who did not (48 hours vs. 7 hours, p = 0.030). Patients with sickle cell disease as the etiology were less likely to require shunting compared to all other etiologies (2.2 vs. 15.2%, p = 0.035). CONCLUSION Men with longer duration of priapism before treatment more often underwent shunting, however phenylephrine injection and aspiration remained effective for priapism lasting greater than 36 hours. Having sickle cell disease as the etiology of priapism was protective against requiring shunting. We developed artificial intelligence models that performed with 87.2% accuracy and created an online probability calculator to determine which patients with ischemic priapism may require shunting.