Kinematic and kinetic comparison between preprofessional pitchers from the Dominican Republic and the United States.

Introduction: Pitching biomechanical efficiency is defined as the association between pitch velocity and arm kinetics. Pitching mechanics inefficiency, an increase in arm kinetics without the resultant increase in pitch velocity, can lead to increased arm strain, increasing arm injury risk. The purpose of this study was to compare arm kinetics, elbow varus torque and shoulder force, in preprofessional United States (US) and Dominican Republic (DR) pitchers. Kinematics that are known to influence elbow varus torque and shoulder force as well as a representative of pitch velocity (hand velocity) were also compared. Methods: A retrospective review was performed on baseball pitchers from the DR and US who participated in biomechanical evaluations conducted by the University biomechanics laboratory personnel. Three-dimensional biomechanical analyses were performed on US (n = 37) and DR (n = 37) baseball pitchers. Potential differences between US and DR pitchers were assessed through analysis of covariance with 95% confidence intervals [95% confidence Interval (CI)]. Results: Preprofessional DR pitchers experienced increased elbow varus torque compared with their US counterparts [DR: 7.5 (1.1); US: 5.9 (1.1) %BWxH; Beta: -2.0 (95% CI: -2.7, -1.2) %BWxH], despite throwing fastballs with slower hand velocity [DR: 3,967.1 (939.4); US: 5,109.1 (613.8) °/s; Beta: 1,129.5 (95% CI: 677.5, 1,581.4) °/s]. DR and US pitchers demonstrated similar shoulder force [DR: 136.8 (23.8); US: 155.0 (25.7); Beta: 0.4 (95% CI: -1.2, 19.7) %BW]. Discussion: Increased elbow varus torque although decreased hand velocity suggests inefficient pitching mechanics among DR pitchers. Inefficient pitching mechanics and increased elbow torque should be considered when developing training programs and pitching plans for professional pitchers from the Dominican Republic.

Pitching Biomechanics Normative Values and Kinetic Differences by Competition Level.

Pitching kinematic and kinetic assessments require normative values to make valuable comparisons to athletic peers. The purpose of this research note was to report normative values of pitching kinematics and kinetics and to compare kinetics by competition level. A retrospective review was performed on three-dimensional baseball pitching biomechanical evaluations. Kinematics and kinetics were calculated. Pitchers were portioned into competition level groups. Kinetic group differences were assessed through analyses of variance with significance level p < 0.05. One-hundred and twenty pitchers were included. Elbow varus torque was greater in higher competition levels. Shoulder distraction force was greater in higher competition levels. All levels demonstrated similar maximum vertical push off ground reaction force (p = 0.960) and maximum vertical landing ground reaction force (p = 0.135). Higher competition level pitchers demonstrated improved pitching kinematic efficiency compared to lower-level pitchers. However, college and professional pitchers exhibited greater arm stress, which may be attributed to increased pitching velocity. These pitching biomechanical data can be used as normative comparisons when examining pitching mechanics at multiple competition levels throughout an athlete's baseball career. (Journal of Surgical Orthopaedic Advances 31(3):177-180, 2022).

Just How Confident Can We Be in Predicting Sports Injuries? A Systematic Review of the Methodological Conduct and Performance of Existing Musculoskeletal Injury Prediction Models in Sport.

BACKGROUND: An increasing number of musculoskeletal injury prediction models are being developed and implemented in sports medicine. Prediction model quality needs to be evaluated so clinicians can be informed of their potential usefulness. OBJECTIVE: To evaluate the methodological conduct and completeness of reporting of musculoskeletal injury prediction models in sport. METHODS: A systematic review was performed from inception to June 2021. Studies were included if they: (1) predicted sport injury; (2) used regression, machine learning, or deep learning models; (3) were written in English; (4) were peer reviewed. RESULTS: Thirty studies (204 models) were included; 60% of studies utilized only regression methods, 13% only machine learning, and 27% both regression and machine learning approaches. All studies developed a prediction model and no studies externally validated a prediction model. Two percent of models (7% of studies) were low risk of bias and 98% of models (93% of studies) were high or unclear risk of bias. Three studies (10%) performed an a priori sample size calculation; 14 (47%) performed internal validation. Nineteen studies (63%) reported discrimination and two (7%) reported calibration. Four studies (13%) reported model equations for statistical predictions and no machine learning studies reported code or hyperparameters. CONCLUSION: Existing sport musculoskeletal injury prediction models were poorly developed and have a high risk of bias. No models could be recommended for use in practice. The majority of models were developed with small sample sizes, had inadequate assessment of model performance, and were poorly reported. To create clinically useful sports musculoskeletal injury prediction models, considerable improvements in methodology and reporting are urgently required.

Biomechanical Analysis of the Throwing Athlete and Its Impact on Return to Sport.

Throwing sports remain a popular pastime and frequent source of musculoskeletal injuries, particularly those involving the shoulder and elbow. Biomechanical analyses of throwing athletes have identified pathomechanic factors that predispose throwers to injury or poor performance. These factors, or key performance indicators, are an ongoing topic of research, with the goals of improved injury prediction, prevention, and rehabilitation. Important key performance indicators in the literature to date include shoulder and elbow torque, shoulder rotation, kinetic chain function (as measured by trunk rotation timing and hip-shoulder separation), and lower-extremity mechanics (including stride characteristics). The current gold standard for biomechanical analysis of the throwing athlete involves marker-based 3-dimensional) video motion capture. Emerging technologies such as marker-less motion capture, wearable technology, and machine learning have the potential to further refine our understanding. This review will discuss the biomechanics of throwing, with particular attention to baseball pitching, while also delineating methods of modern throwing analysis, implications for clinical orthopaedic practice, and future areas of research interest. LEVEL OF EVIDENCE: V, expert opinion.

A Low-Cost, Rapidly Integrated Debubbler (RID) Module for Microfluidic Cell Culture Applications.

Microfluidic platforms use controlled fluid flows to provide physiologically relevant biochemical and biophysical cues to cultured cells in a well-defined and reproducible manner. Undisturbed flows are critical in these systems, and air bubbles entering microfluidic channels can lead to device delamination or cell damage. To prevent bubble entry into microfluidic channels, we report a low-cost, Rapidly Integrated Debubbler (RID) module that is simple to fabricate, inexpensive, and easily combined with existing experimental systems. We demonstrate successful removal of air bubbles spanning three orders of magnitude with a maximum removal rate (dV/dt)max = 1.5 mL min-1, at flow rates required to apply physiological wall shear stress (1-200 dyne cm-2) to mammalian cells cultured in microfluidic channels.