Who does not respond to injury prevention warm-up programs? A secondary analysis of trial data from neuromuscular training programs in youth basketball, soccer, and physical education - Shanley, E.; Thigpen, C. A.; Collins, G. S.; Arden, N. K.; Noonan, T. J.; Wyland, D. J.; Kissenberth, M. J.; Bullock, G. S. (Journal of Orthopaedic & Sports Physical Therapy, 2022)
Objectives: To (1) evaluate an injury risk model that included modifiable and nonmodifiable factors into an arm injury risk prediction model in Minor League Baseball (MiLB) pitchers and (2) compare model performance separately for predicting the incidence of elbow and shoulder injuries. Design: Prospective cohort. Methods: A 10-year MiLB injury risk study was conducted. Pitchers were evaluated during preseason, and pitches and arm injuries were documented prospectively. Nonmodifiable variables included arm injury history, professional experience, arm dominance, year, and humeral torsion. Modifiable variables included BMI, pitch count, total range of motion, and horizontal adduction. We compared modifiable, nonmodifiable, and combined model performance by R2, calibration (best = 1.00), and discrimination (area under the curve [AUC]; higher number is better). Sensitivity analysis included only arm injuries sustained in the first 90 days. Results: In this study, 407 MiLB pitchers (141 arm injuries) were included. Arm injury incidence was 0.27 injuries per 1000 pitches. The arm injury model (calibration 1.05 [0.81-1.30]; AUC: 0.74 [0.69-0.80]) had improved performance compared to only using modifiable predictors (calibration: 0.91 [0.68-1.14]; AUC: 0.67 [0.62-0.73]) and only shoulder range of motion (calibration: 0.52 [0.29, 0.75]; AUC: 0.52 [0.46, 58]). Elbow injury model demonstrated improved performance (calibration: 1.03 [0.76-1.33]; AUC: 0.76 [0.69-0.83]) compared to the shoulder injury model (calibration: 0.46 [0.22-0.69]; AUC: 0.62 [95% CI: 0.55, 0.69]). The sensitivity analysis demonstrated improved model performance compared to the arm injury model. Conclusion: Arm injury risk is influenced by modifiable and nonmodifiable risk factors. The most accurate way to identify professional pitchers who are at risk for arm injury is to use a model that includes modifiable and nonmodifiable risk factors.