Sports Injury Forecasting and Complexity: A Synergetic Approach

ObjectivesTo describe and compare the epidemiology of competition injuries in unarmed combat sports (ie, boxing, judo, taekwondo and wrestling) in three consecutive Olympic Games.MethodsProspective cohort study using injury data from the IOC injury surveillance system and exposure data from official tournament records at three consecutive Olympic Games (ie, Beijing 2008, London 2012 and Rio de Janeiro 2016). Competition injury incidence rates per 1000 min of exposure (IIRME) were calculated with 95% CIs using standard formulae for Poisson rates.ResultsThe overall IIRME was 7.8 (95% CI 7.0 to 8.7). The IIRME in judo (9.6 (95% CI 7.8 to 11.7)), boxing (9.2 (95% CI 7.6 to 10.9)) and taekwondo (7.7 (95% CI 5.6 to 10.5)) were significantly higher than in wrestling (4.8 (95% CI 3.6 to 6.2)). The proportion of injuries resulting in >7 days absence from competition or training was higher in wrestling (39.6%), judo (35.9%) and taekwondo (32.5%) than in boxing (21.0%). There was no difference in injury risk by sex, weight category or tournament round, but athletes that lost had significantly higher IIRME compared with their winning opponents (rate ratio 3.59 (95% CI 2.68 to 4.79)).ConclusionOlympic combat sport athletes sustained, on average, one injury every 2.1 hours of competition. The risk of injury was significantly higher in boxing, judo and taekwondo than in wrestling. About 30% of injuries sustained during competition resulted in >7 days absence from competition or training. There is a need for identifying modifiable risk factors for injury in Olympic combat sports, which in turn can be targeted by injury prevention initiatives to reduce the burden of injury among combat sport athletes.

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“…Future studies are therefore strongly encouraged to adopt frameworks that incorporates this inherent complexity. [41][42][43][44]…”

Section: Recommendations and Implicationsmentioning

confidence: 99%

Injury incidence, severity and profile in Olympic combat sports: a comparative analysis of 7712 athlete exposures from three consecutive Olympic Games

et al. 2020

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“…However, some experts consider the majority of available evidence inadequate to support the use of sport injury risk screening results in making clinical decisions (Hegedus and Cook, 2015;Bahr, 2016). Other experts believe reductionist study designs and data analyses should be replaced with a complex systems approach for development of injury prevention strategies (Quatman et al, 2009;Bittencourt et al, 2016;Kenzie et al, 2017;Fonseca et al, 2020). A reductionist approach involves a search for isolated risk factors that cause injury (Bittencourt et al, 2016), whereas a complex systems approach involves a search for high-order variables that represent the collective function of multiple interacting system elements that lead to the emergence of injury susceptibility (Fonseca et al, 2020).…”

Section: Potential For Improved Risk Screening and Individualized Interventionsmentioning

confidence: 99%

“…Other experts believe reductionist study designs and data analyses should be replaced with a complex systems approach for development of injury prevention strategies (Quatman et al, 2009;Bittencourt et al, 2016;Kenzie et al, 2017;Fonseca et al, 2020). A reductionist approach involves a search for isolated risk factors that cause injury (Bittencourt et al, 2016), whereas a complex systems approach involves a search for high-order variables that represent the collective function of multiple interacting system elements that lead to the emergence of injury susceptibility (Fonseca et al, 2020). For example, a Composite Asymmetry value derived from multiple WBRA performance metrics has been shown to provide better SRC history discrimination than any single asymmetry metric (Wilkerson et al, 2020(Wilkerson et al, , 2021a.…”

Section: Potential For Improved Risk Screening and Individualized Interventionsmentioning

confidence: 99%

“…Traditional reductionistic study designs, combined with parametric data analyses that treat IIV as measurement error, have probably limited the ability of many prior investigations to detect subtle and heterogenous impairments that could explain the association of SRC with elevated musculoskeletal injury incidence (Quatman et al, 2009;Kenzie et al, 2017). Reductionism refers to an attempt to reduce a complex problem into components that can purportedly be studied separately for attainment of an understanding of the whole phenomenon (Quatman et al, 2009;Bittencourt et al, 2016), whereas a complex systems approach involves a search for high-order composite variables that represent the collective function of multiple interacting elements (Kenzie et al, 2017;Fonseca et al, 2020). Rather than seeking to identify isolated risk factors that may be a primary cause of subsequent injury, a complex systems approach involves identification of patterns among interacting factors that lead to the emergence of elevated injury susceptibility (Bittencourt et al, 2016).…”

Section: Neural Basis For Inconsistency Of Perceptual-motor Performancementioning

confidence: 99%

“…Rather than seeking to identify isolated risk factors that may be a primary cause of subsequent injury, a complex systems approach involves identification of patterns among interacting factors that lead to the emergence of elevated injury susceptibility (Bittencourt et al, 2016). A single assessment (e.g., pre-participation physical examination) is incompatible with a complex systems approach, which requires data from multiple time points to obtain a better representation of global behavior (Fonseca et al, 2020). With regard to assessment of within-session IIV, the data derived from a single measurement session could be affected by factors that vary over time, such as motivation, fatigue, stress, emotions, or pain.…”

Section: Neural Basis For Inconsistency Of Perceptual-motor Performancementioning

confidence: 99%

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A Novel Approach to Assessment of Perceptual-Motor Efficiency and Training-Induced Improvement in the Performance Capabilities of Elite Athletes

Wilkerson

Nabhan

Perry

2021

Front. Sports Act. Living

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Standard clinical assessments of mild traumatic brain injury are inadequate to detect subtle abnormalities that can be revealed by sophisticated diagnostic technology. An association has been observed between sport-related concussion (SRC) and subsequent musculoskeletal injury, but the underlying neurophysiological mechanism is not currently understood. A cohort of 16 elite athletes (10 male, 6 female), which included nine individuals who reported a history of SRC (5 male, 4 female) that occurred between 4 months and 8 years earlier, volunteered to participate in a 12-session program for assessment and training of perceptual-motor efficiency. Performance metrics derived from single- and dual-task whole-body lateral and diagonal reactive movements to virtual reality targets in left and right directions were analyzed separately and combined in various ways to create composite representations of global function. Intra-individual variability across performance domains demonstrated very good SRC history classification accuracy for the earliest 3-session phase of the program (Reaction Time Dispersion AUC = 0.841; Deceleration Dispersion AUC = 0.810; Reaction Time Discrepancy AUC = 0.825, Deceleration Discrepancy AUC = 0.794). Good earliest phase discrimination was also found for Composite Asymmetry between left and right movement directions (AUC = 0.778) and Excursion Average distance beyond the minimal body displacement necessary for virtual target deactivation (AUC = 0.730). Sensitivity derived from Youden's Index for the 6 global factors ranged from 67 to 89% and an identical specificity value of 86% for all of them. Median values demonstrated substantial improvement from the first 3-session phase to the last 3-session phase for Composite Asymmetry and Excursion Average. The results suggest that a Composite Asymmetry value ≥ 0.15 and an Excursion Average value ≥ 7 m, provide reasonable qualitative approximations for clinical identification of suboptimal perceptual-motor performance. Despite acknowledged study limitations, the findings support a hypothesized relationship between whole-body reactive agility performance and functional connectivity among brain networks subserving sensory perception, cognitive decision-making, and motor execution. A complex systems approach appears to perform better than traditional data analysis methods for detection of subtle perceptual-motor impairment, which has the potential to advance both clinical management of SRC and training for performance enhancement.

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Forecasting neuromuscular recovery after anterior cruciate ligament injury: Athlete recovery profiles with generalized additive modeling

Jordan

Morris

Barnert³

et al. 2022

Journal Orthopaedic Research

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A retrospective analysis of longitudinally collected athlete monitoring data was conducted to generate a model of neuromuscular recovery after anterior cruciate ligament (ACL) injury and reconstruction (ACLR). Neuromuscular testing data including countermovement jump (CMJ) force‐time asymmetries and knee extensor strength (maximum voluntary contractionext) asymmetries (between‐limb asymmetry index—AI) were obtained from athletes with ACLR using semitendinosus (ST) autograft (n = 29; AI measurements: n = 494), bone patellar tendon bone autograft (n = 5; AI measurements: n = 88) and noninjured controls (n = 178; AI measurements: n = 3188). Explosive strength measured as the rate of torque development was also calculated. CMJ force‐time asymmetries were measured over discrete movement phases (eccentric deceleration phase, concentric phase). Separate additive mixed effects models (additive mixed effects model [AMM]) were fit for each AI with a main effect for the surgical technique and a smooth term for the time since surgery (days). The models explained between 43% and 91% of the deviance in neuromuscular recovery after ACLR. The mean time course was generated from the AMM. Comparative neuromuscular recovery profiles of an athlete with an accelerated progression and an athlete with a delayed progression after a serious multiligament injury were generated. Clinical Significance: This paper provides a new perspective on the utility of longitudinal athlete monitoring including routine testing to develop models of neuromuscular recovery after ACLR that can be used to characterize individual progression throughout rehabilitation.

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Sports Injury Forecasting and Complexity: A Synergetic Approach

Cited by 61 publications

References 79 publications

Injury incidence, severity and profile in Olympic combat sports: a comparative analysis of 7712 athlete exposures from three consecutive Olympic Games

Injury incidence, severity and profile in Olympic combat sports: a comparative analysis of 7712 athlete exposures from three consecutive Olympic Games

A Novel Approach to Assessment of Perceptual-Motor Efficiency and Training-Induced Improvement in the Performance Capabilities of Elite Athletes

Forecasting neuromuscular recovery after anterior cruciate ligament injury: Athlete recovery profiles with generalized additive modeling

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