Jacob F Oeding, Ayoosh Pareek, Micah J Nieboer, Nicholas G Rhodes, Christin A Tiegs-Heiden, Christopher L Camp, R Kyle Martin, Gilbert Moatshe, Lars Engebretsen, Joaquin Sanchez-Sotelo
PURPOSE: The purpose of this study was to develop a machine learning model capable of identifying subscapularis tears preoperatively based on imaging and physical exam findings. METHODS: Between 2010 and 2020, 202 consecutive shoulders underwent arthroscopic rotator cuff repair by a single surgeon. Patient demographics, physical examination findings (including range of motion, weakness with internal rotation, lift/push-off test, belly press test, and bear hug test), and imaging (including direct and indirect signs of tearing, biceps status, fatty atrophy, cystic changes, and other similar findings) were included for model creation...
September 14, 2023: Arthroscopy