Development and internal validation of novel risk tools to predict subsequent shoulder surgery after proximal humerus fractures

Objective: To (1) identify predictors of subsequent surgery after initial treatment of proximal humerus fractures (PHFs) and (2) generate valid risk prediction tools to predict subsequent surgery. Methods: We identified patients ¡Ý50 years with PHF from 2004 to 2015 using health data sets in Ontario, Canada. We used procedural codes to classify patients into treatment groups of (1) surgical fixation, (2) shoulder replacement, and (3) conservative. We used procedural and diagnosis codes to capture subsequent surgery within 2 years after fracture. We developed regression models for two-thirds of each group to identify predictors of subsequent surgery and the regression equations to develop risk tools to predict subsequent surgery. We used the final third of each cohort to evaluate the discriminative ability of the risk tools using c-statistics. Results: We identified 20,897 patients with PHF, 2414 treated with fixation, 1065 with replacement, and 17,418 treated conservatively. Predictors of reoperation after fixation included bone grafting and nail or wire fixation versus plate fixation, whereas poor bone quality was associated with reoperation after initial replacement. In conservatively treated patients, more comorbidities were associated with subsequent surgery, whereas age 70+ and discharge home after presentation lowered the odds of subsequent surgery. The risk tools were able to discriminate with c-statistics of 0.75-0.88 (derivation) and 0.51-0.79 (validation). Conclusions: Our risk tools showed good to strong discriminative ability for patients treated conservatively and with fixation. These data may be used as the foundation to develop a clinically informative tool. Level of evidence: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.