RESUMO
Background: Shoulder injuries are very common in athletes playing in the National Basketball Association (NBA). With increasing injury video uploads available online, we may be able to identify and systematically describe the mechanism of these injuries in these athletes. Purpose: To (1) determine the validity of video-based analysis to evaluate mechanisms of shoulder injuries in NBA players during the 2010-2020 seasons and (2) report on commonly sustained injuries, circumstances associated with injury, and number of games missed owing to injury. Study Design: Cross-sectional study; Level of evidence, 3. Methods: An injury report data set was queried for shoulder injuries among NBA players between the 2010-2011 season and the 2019-2020 season, and results were cross-referenced using YouTube.com to identify high-quality videos of the injuries. Out of 532 shoulder injuries in this time frame, video evidence from 39 (7.3%) were evaluated for mechanism of injury and other corresponding situational data. From the remaining shoulder injuries, a randomly selected control cohort of 50 injuries occurring in the same interval was assessed for descriptive injury data, incidence of recurrence, necessity for surgery, and number of games missed, to compare with corresponding data from injuries in the videographic evidence cohort. Results: In the videographic evidence cohort, the most common mechanism of injury was lateral contact to the shoulder (41%; P < .001), which was associated with an injury to the acromioclavicular joint (30.8%; P < .001). Injuries occurred more often when the team was on offense (58.9%; P < .001) versus defense. Players who required surgery missed 33 more games on average than players who did not require surgery (P < .001). For the injured players, a 33% incidence of reinjury was identified in the 12 months after their initial injury. As compared with the control cohort, no significant differences were noted in injury laterality, recurrence rates, necessity for surgical management, time in the season, or number of games missed. Conclusion: Despite its low yield of 7.3%, video-based analysis may be a useful tool to determine the mechanism of shoulder injuries in the NBA, given the similarities of injury characteristics as compared with the control group.
RESUMO
Background: In the National Basketball Association (NBA), lower extremity injuries account for over 70% of games missed, with ankle injuries being the most common. High-quality video analysis has been successful for studying injury mechanism. Purpose: To (1) determine the validity of video-based analysis as a method to evaluate ankle injury mechanisms in NBA players and (2) analyze the circumstances associated with injury, games missed due to injury, and associated costs in player salary due to time missed. Study Design: Case series; Level of evidence, 4. Methods: Ankle injuries were identified using an injury report database, and corresponding videos were searched using YouTube.com to access high-quality video evidence of these injuries during the 2015-2020 NBA regular season. We reviewed 822 injuries, of which 93 had corresponding videos (video subset), in our final analysis. Variables including number of games missed, necessity for surgical treatment, and injury recurrence were reported for the entire cohort. In the video subset, the mechanism of injury and other corresponding situational data were evaluated. Results: The most common mechanism of injury occurred via ankle inversion (83.9%; n = 78; P < .001). These injuries were significantly associated with indirect contact with the player's ankle (79.6%; n = 74; P < .001). There were significant differences based on player position, within both the video subset (P = .008) and the entire cohort (P < .001), with guards being injured the most frequently. The average number of games missed due to injury was 7 games in the video subset and 5 games in the entire cohort (P = .14). There were significant differences between the groups in average player salary per game ($133,878 [video subset] versus $87,577 [entire cohort]; P < .001). Conclusion: Despite its low yield of 11.3%, video analysis proved to be a useful tool to determine ankle injury mechanisms as well as the distribution of injuries based on player position. However, this methodology was subject to selection bias, as evidenced by a $50,000 increase in player salary among the video cohort. These findings should be considered when using video analysis in future studies.
