Epidemiology of Spine-Related Neurologic Injuries in Professional Baseball Players

Epidemiology of Lumbar Spine Conditions in Professional Baseball Players

STUDY DESIGN

A retrospective case series study.

OBJECTIVE

To analyze the epidemiology and burden of diagnoses of lumbar spinal conditions affecting Major League Baseball (MLB) and Minor League Baseball players.

SUMMARY OF BACKGROUND DATA

Lumbar spinal conditions are a common cause of low back pain in the general population and can be caused by participation in sports and athletics. Data concerning the epidemiology of these injuries in professional baseball players are limited.

METHODS

We collected deidentified MLB and Minor League Baseball data concerning lumbar spine conditions (lumbar disk herniations, lumbar degenerative disease, or pars conditions) from 2011 to 2017 using the MLB-commissioned Health and Injury Tracking System database. Data concerning days missed because of injury, need for surgery, and player participation and career-ending status were assessed. Injury rates were reported as injuries per 1000 athlete exposures in concordance with prior studies.

RESULTS

Over 2011-2017, 5948 days of play were missed because of 206 lumbar spine-related injuries, of which 60 (29.1%) were season ending. Twenty-seven (13.1%) of these injuries required surgery. The most common injury among both pitchers and position players were lumbar disk herniations (45, 44.1% and 41, 39.4%, respectively). More surgeries were performed for lumbar disk herniations and degenerative disk disease compared with pars conditions (74% and 18.5% vs. 3.7%). Injury rates for pitchers was significantly higher than those of other position players 0.111 per 1000 AEs versus 0.040 per 1000 AEs (P<0.0001). Injuries requiring surgery did not vary significantly by league, age group, or player position.

CONCLUSIONS

Lumbar spine-related injuries incurred substantial disability and days missed from play in professional baseball players. Lumbar disk herniations were the most common injury, and together with pars conditions led to higher rates of surgery compared with degenerative conditions.

LEVEL OF EVIDENCE

III.

Current State of Data and Analytics Research in Baseball

PURPOSE OF REVIEW

Baseball has become one of the largest data-driven sports. In this review, we highlight the historical context of how big data and sabermetrics began to transform baseball, the current methods for data collection and analysis in baseball, and a look to the future including emerging technologies.

RECENT FINDINGS

Machine learning (ML), artificial intelligence (AI), and modern motion-analysis techniques have shown promise in predicting player performance and preventing injury. With the advent of the Health Injury Tracking System (HITS), numerous studies have been published which highlight the epidemiology and performance implications for specific injuries. Wearable technologies allow for the prospective collection of kinematic data to improve pitching mechanics and prevent injury. Data and analytics research has transcended baseball over time, and the future of this field remains bright.