An epidemiological study of health, injury, and long term outcomes in baseball players

Thesis

Baseball injuries are a persistent and significant problem, with the greatest injury incidence to the elbow and shoulder. Baseball injuries can be prevented through a stepwise process that enables the identification of injury type, injury risk factors, etiology and injury mechanisms which is dependent upon high quality data. However, current injury risk and prediction research does not quantify the complexities related to athletic injuries. Therefore, the complex interaction of multiple risk factors and injury mechanisms are unclear and inhibits clinical examination and prevention. The primary aim of this thesis was to create an injury prediction model for shoulder and elbow injuries in a cohort of professional baseball pitchers. The secondary aims are to describe the musculoskeletal health and wellbeing of current and former baseball players and assess the clinical utility of the primary injury risk model.

I conducted a systematic scoping review of baseball health and wellbeing in 2019. It found that the greatest density of baseball research focused on injury incidence and prevalence. However, there was a paucity of research on the long-term health effect of baseball participation, health and wellbeing across all baseball playing standard, and injury prevention research.

I analyzed data of a survey of current and professional baseball players. Both current and former baseball players reported similar health related quality of life compared to the general population, high flourishing, and high physical activity. Former baseball players reported the greatest persistent joint pain prevalence to the shoulder and elbow, and decreased arm function compared to older total shoulder arthroplasty patients.

I conducted an interrupted time series analysis to assess the effectiveness of injury risk profiling and education on a five-year cohort of professional baseball players. Injury risk profiling and education decreased injury incidence by 33%.

I developed and internally validated an arm injury prediction model on a ten-year cohort of professional baseball pitchers. The prediction model demonstrated good discriminate ability and excellent calibration.

I developed and internally validated a humeral torsion prediction model on the same ten-year cohort of professional baseball pitchers. The prediction model demonstrated small error and excellent calibration.

I analyzed the clinical net benefit and utility of the developed injury prediction model in comparison to current evidence based practice. The prediction model demonstrated improved net benefit and utility compared to current practice standards.

Future research is needed to examine if findings are generalizable to different cohorts and playing standards, and the efficacy of this prediction model in a clinical setting

Authors: Bullock, G

• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: Net Benefit; Humeral Torsion; Decision Curves; Arm Burden; Prediction
• Subjects: Statistics; Prediction; Epidemiology