Abstract While arthroscopic Bankart repair has become the most commonly performed procedure for anterior shoulder instability, recurrence rates remain unacceptably high in certain subgroups. This reality has driven decades of investigation into risk factors and predictive tools for failure. Early efforts, such as the Instability Severity Index Score, provided a simple preoperative framework combining demographic, clinical, and radiographic variables, but its predictive validity has been inconsistent. The development of the glenoid track concept and subsequent Glenoid Track Instability Management Score represented a shift toward integrating advanced imaging and bone loss assessment into decision‐making. More recently, the Pittsburgh Instability Tool has expanded this framework further, incorporating modern risk factors such as near‐track lesions, hyperlaxity, and the modifying role of Remplissage. Collectively, these tools reflect the ongoing evolution from single‐variable predictors toward multidimensional, algorithm‐based strategies that aim to deliver personalized care for patients with anterior shoulder instability.
Eoghan T. Hurley (Sun,) studied this question.
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