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Background: Concussions have previously been shown to have persistent neurological changes represented by altered reaction time and postural stability in high-level athletes. The effects of concussions on professional basketball players’ performance and subsequent injuries during the 90 days after return to play (RTP) have not been investigated. Purpose/Hypothesis: the purpose of this study was to evaluate player statistical performance and risk of musculoskeletal (MSK) injury within 90 days of RTP from a diagnosed concussion. It was hypothesized that within the 90 days after RTP from a concussion, players would be at a greater risk for MSK injury with an associated decrease in player statistical performance. Study Design: Descriptive epidemiology study. Methods: Concussions sustained by National Basketball Association (NBA) players between the 2015-2016 and 2021-2022 seasons, excluding the 2019-2020 season, were evaluated using a publicly available database. The database was queried to identify any MSK injury in the 90-day post-RTP period after a concussion, along with time loss after subsequent injury. Performance statistics were obtained from each player’s preindex season and postindex season, as well as defined time points within the 90-day post-RTP period. Each concussed player was matched 1 to 1 with a nonconcussed control using position, win shares, player efficiency rating, and points per game. MSK injury incidence and player statistics in the concussion group were compared with controls using unpaired Student t tests. Results: A total of 70 concussions were identified in 70 professional basketball players and included in this analysis. A total of 49 players sustained an MSK injury in the 90-day post-RTP period (70%). Compared with controls, the odds of sustaining an MSK injury in the concussed cohort were 11.3 times greater (95% CI, 5.04-25.2; P < .001). Games missed after subsequent MSK injury were similar between the concussed and control groups (P = .687). Comparisons over the 90-day post-RTP period did not reveal any significant changes in points per game, minutes per game, or true shooting percentage (P > .05). When compared with controls, no changes in performance statistics were significantly different (P > .05). Conclusion: Our analysis demonstrates that basketball players who sustain concussions are at a significantly increased risk for subsequent MSK injury within the 90-day post-RTP period but not player performance. Knowledge of this increased risk of MSK injury in concussed athletes can help guide concussion management for proper RTP and targeted rehabilitation in professional basketball players.

Background: Shoulder and elbow function is essential to basic basketball actions. Outside of anterior shoulder instability, injuries in these joints are not well characterized in National Basketball Association (NBA) players. Purpose: To describe the epidemiology and associated risk factors of shoulder and elbow injuries in NBA players and identify factors that influence player performance upon return to play. Study Design: Descriptive epidemiology study. Methods: Historical injury data from the 2015-2020 NBA seasons were retrieved from Pro Sports Transactions, a public online database. An injury was defined as a health-related concern resulting in an absence of ≥1 NBA games. Primary measures included pre- and postinjury player efficiency rating (PER) and true shooting percentage (TS%) with interquartile ranges (IQRs), stratified by extremity dominance. Multivariate logistic regression analyses with stepwise regression were performed to identify risk factors associated with return-to-play performance. Results: A total of 192 shoulder and elbow injuries were sustained among 126 NBA athletes, with incidence rates of 1.11 per 1000 game exposures (GEs) and 0.30 per 1000 GEs, respectively. Sprain/strain and general soreness were the most common injury types in both the shoulder and the elbow. In the 2 years after injury, baseline PER was achieved in all groups, except for players with dominant shoulder injuries (baseline PER, 16 [IQR, 14-18] vs 2-year PER, 13 [IQR 11-16]; P = .012). Younger age was associated with quicker return to baseline PER (odds ratio, 0.77 [95% CI, 0.67-0.88]). Shoulder and elbow injuries did not negatively influence TS% upon return to play (baseline TS%, 0.55% [IQR, 0.51%-0.58%] vs 1-year TS%, 0.55% [IQR, 0.52%-0.58%]; P = .13). Conclusion: Dominant shoulder injuries negatively influenced PER during the first 2 seasons upon return to play in NBA players. Therefore, expectations that players with this type of injury immediately achieve baseline statistical production should be tempered. Shooting accuracy appears to remain unaffected after shoulder or elbow injury.

Background: Ankle injuries are more common in the National Basketball Association (NBA) compared with other professional sports. Purpose/Hypothesis: The purpose of this study was to report the incidence and associated risk factors of ankle injuries in NBA athletes. It was hypothesized that factors associated with an increased physiologic burden, such as minutes per game (MPG), usage rate, and associated lower extremity injury, would be associated with increased ankle injury risk and time loss. Study Design: Descriptive epidemiology study. Methods: Ankle injury data from the 2015-2016 through 2020-2021 NBA seasons were evaluated. The truncated 2019-2020 season due to the COVID-19 pandemic was omitted. The primary outcome was the incidence of ankle injuries, reported per 1000 game-exposures (GEs). Secondary analysis was performed to identify risk factors for ankle injuries through bivariate analysis and multivariable logistic regression of player demographic characteristics, performance statistics, injury characteristics, and previous lower extremity injuries. Factors influencing the time loss after injury were assessed via a negative binomial regression analysis. Results: A total of 554 ankle injuries (4.06 injuries per 1000 GEs) were sustained by NBA players over 5 NBA seasons, with sprain/strain the most common injury type (3.71 injuries per 1000 GEs). The majority of ankle injury events (55%) resulted in 2 to 10 game absences. The likelihood of sustaining an ankle injury was significantly associated with a greater number of games played (P = .029) and previous injury to the hip, hamstring, or quadriceps (P = .004). Increased length of absence due to ankle injury was associated with greater height (P = .019), MPG (P < .001), usage rate (P = .025), points per game (P = .011), and a prior history of foot (P = .003), ankle (P < .001), and knee injuries (P < .001). Conclusion: The incidence of ankle injuries was 4.06 per 1000 GEs in professional basketball players. Games played and prior history of hip, hamstring, or quadriceps injuries were found to be risk factors for ankle injuries. Factors associated with physiologic burden such as MPG and usage rate were associated with an increased time loss after injury.

Objectives: Injuries to the foot and ankle are more common in National Basketball Association (NBA) basketball compared to other professional sports. The goal of this study is to report the incidence and associated risk factors of foot and ankle injuries in the NBA athletes. Methods: Foot and ankle injury data from the 2015-16 through 2020-21 NBA seasons was queried and verified using a publicly available database. The truncated 2019-20 season was omitted from this study due to the COVID-19 pandemic. The primary outcome was the incidence of foot and ankle injuries, reported per 1000 game exposures (GEs). Secondary analysis was performed to identify risk factors for ankle injuries through bivariate analysis and multivariable logistic regression of player demographics, performance statistics, injury characteristics, and previous lower extremity injuries. Additionally, factors influencing the length of absence were assessed via negative binomial regression. Results: There were 728 structural foot and ankle injuries (5.34 per 1000 GEs) sustained by NBA players over 5 NBA seasons, with sprain/strain as the most common injury type (4.27 per 1000 GEs) (Table 1). The majority of ankle injury events (55%) resulted in 2-10 game absences (Table 4). The likelihood of sustaining an ankle injury was significantly associated with a greater number of games played, previous upper leg injury, and more games missed due to injury (Table 2). Increased length of absence due to ankle injury was significantly associated with greater height, minutes per game, usage rate, points per game, total rebounds per game, and a prior history of foot, ankle, and knee injuries (Table 3). Conclusions: The incidence of foot and ankle injuries was 5.34 per 1000 GEs in professional basketball players. Games played and previous history of upper leg injuries were found to be risk factors for ankle injuries. Factors associated with physiologic burden such as minutes per game and usage rate were associated with an increased severity of injury.