Team Logo Predicts Concussion Risk: Lessons in Protecting a Vulnerable Sports Community from Misconceived, but Highly Publicized Epidemiologic Research

Limitations of Separating Athletes into High or Low-Risk Groups based on a Cut-Off. A Clinical Commentary

Background

Athlete injury risk assessment and management is an important, yet challenging task for sport and exercise medicine professionals. A common approach to injury risk screening is to stratify athletes into risk groups based on their performance on a test relative to a cut-off threshold. However, one potential reason for ineffective injury prevention efforts is the over-reliance on identifying these 'at-risk' groups using arbitrary cut-offs for these tests and measures. The purpose of this commentary is to discuss the conceptual and technical issues related to the use of a cut-off in both research and clinical practice.

Clinical Question

How can we better assess and interpret clinical tests or measures to enable a more effective injury risk assessment in athletes?

Key Results

Cut-offs typically lack strong biologic plausibility to support them; and are typically derived in a data-driven manner and thus not generalizable to other samples. When a cut-off is used in analyses, information is lost, leading to potentially misleading results and less accurate injury risk prediction. Dichotomizing a continuous variable using a cut-off should be avoided. Using continuous variables on its original scale is advantageous because information is not discarded, outcome prediction accuracy is not lost, and personalized medicine can be facilitated.

Clinical Application

Researchers and clinicians are encouraged to analyze and interpret the results of tests and measures using continuous variables and avoid relying on singular cut-offs to guide decisions. Injury risk can be predicted more accurately when using continuous variables in their natural form. A more accurate risk prediction will facilitate personalized approaches to injury risk mitigation and may lead to a decline in injury rates.

Level of Evidence

5.

Interaction of Surface Type, Temperature, and Week of Season on Concussion Risk in the National Football League: A Bayesian Analysis

BACKGROUND

Artificial turf fields and environmental conditions may influence sports concussion risk, but existing research is limited by uncontrolled confounding factors, limited sample size, and the assumption that risk factors are independent of one another. The purpose of this study was to examine how playing surface, time of season, and game temperature relate to diagnosed concussion risk in the National Football League (NFL).

METHODS

This retrospective cohort study examined data from the 2012 to the 2019 NFL regular season. We fit Bayesian negative binomial regression models to relate how playing surface, game temperature, and week of the season independently related to diagnosed concussion risk and any interactions among these factors.

RESULTS

We identified 1096 diagnosed concussions in 1830 games. There was a >99% probability that concussion risk was reduced on grass surface (median incidence rate ratio [IRR] = 0.78 [95% credible interval: 0.68, 0.89]), >99% probability that concussion risk was lower at higher temperatures (IRR = 0.85 [0.76,0.95] for each 7.9 °C), and >91% probability that concussion risk increased with each week of the season (IRR = 1.02 [1.00,1.04]). There was an >84% probability for a surface × temperature interaction (IRR = 1.01 [0.96, 1.28]) and >75% probability for a surface × week interaction (IRR = 1.02 [0.99, 1.05]).

CONCLUSIONS

Diagnosed concussion risk is increased on artificial turf compared with natural grass, and this is exacerbated in cold weather and, independently, later in the season. The complex interplay between these factors necessitates accounting for multiple factors and their interactions when investigating sports injury risk factors and devising mitigation methods.

Do Climate and Environmental Characteristics Influence Concussion Incidence in Outdoor Contact Sports? A Systematic Review

OBJECTIVE

To obtain a comprehensive understanding of the implications of environmental and climate factors on sport-related concussion incidence in outdoor contact sports.

DATA SOURCES

MEDLINE (via Ovid), Embase (via Elsevier), CINAHL Complete (via EBSCOhost), SPORTDiscus (via EBSCOhost), and Scopus (via Elsevier).

STUDY SELECTION

Studies that report incidence of sport-related concussion, assess data from athletes participating in outdoor contact sports, report on 1 or more climate or environmental factors, and report a diagnosis of concussion performed by a licensed medical professional were included. Reasons for exclusion included no report on extrinsic or environmental factors, no data on sport-related concussion incidence, and self-report of concussion diagnosis.

DATA EXTRACTION

This systematic review was conducted using Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines using 2 reviewers at each phase and a third reviewer for conflict resolution.

DATA SYNTHESIS

A total of 7558 articles were reviewed, and 20 met the inclusion criteria. There was moderate to strong strength of evidence concluding no difference between surface type (grass versus artificial) on sport-related concussion risk. Moderate to strong strength of evidence was found supporting no difference in sport-related concussion incidence based on game location (home versus away). There was no consensus on the effects of altitude or temperature on sport-related concussion incidence. One high-quality study found a decreased risk of sport-related concussion when playing in wet versus dry conditions. Heterogenous populations and data collection methods prevented extraction and meta-analysis.

CONCLUSIONS

Although a consensus on specific environmental and climate factors that influence sport-related concussion incidence was limited, the majority of studies were of high quality and gave insight into opportunities for future investigation. Administrators of large injury surveillance databases should consider including specific environmental and climate factors to provide investigators with robust data sets to better understand potential associations with sport-related concussion.

Bad Altitude: Categorizing Elevation Produces Spurious Association With Concussions in the National Football League (NFL)

OBJECTIVE: To assess whether prior analyses, where there was a relationship between altitude and concussion rates in American football, would replicate using a larger data set and altitude as a continuous variable. DESIGN: Cohort study replication. METHODS: We analyzed data from all NFL regular season games from 2012-2019. Concussions were identified from public databases and NFL injury reports. The altitude of each stadium was identified using mapping software. Concussion rates were calculated for each stadium and plotted against continuous altitude. We calculated crude rate ratios for several categorical cut points and used logistic and Poisson regression models to assess associations with continuous altitudes. RESULTS: We identified 867 players (1103 player seasons) who sustained 1159 concussions during the time period 2012-2019. All continuous plots and models showed no evidence of any association between concussions and altitude. A Poisson model found an IRR of 1.00 (95% CI, 0.99-1.01) for every 100-ft increase in altitude. A 644-ft cut point (used in previous studies) produced a significant difference (incidence rate ratio [IRR], 0.71; 95% CI, 0.54-0.94) in 2012-2013, but this did not replicate in 2014-2019 (IRR, 0.99; 95% CI, 0.84-1.14). CONCLUSION: We found no association between altitude and concussion rates in the NFL when altitude was analyzed continuously rather than inappropriately categorized. Our findings should increase skepticism of any effect of altitude on concussions at the elevations at which most American football is played, as well as clinical interventions based on that theory. It also underscores the importance of keeping continuous variables continuous wherever possible. J Orthop Sports Phys Ther 2022;52(10):694-701. Epub: 27 July 2022. doi:10.2519/jospt.2022.11220.

Applying the Bradford Hill Criteria for Causation to Repetitive Head Impacts and Chronic Traumatic Encephalopathy

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with a history of repetitive head impacts (RHI). CTE was described in boxers as early as the 1920s and by the 1950s it was widely accepted that hits to the head caused some boxers to become "punch drunk." However, the recent discovery of CTE in American and Australian-rules football, soccer, rugby, ice hockey, and other sports has resulted in renewed debate on whether the relationship between RHI and CTE is causal. Identifying the strength of the evidential relationship between CTE and RHI has implications for public health and medico-legal issues. From a public health perspective, environmentally caused diseases can be mitigated or prevented. Medico-legally, millions of children are exposed to RHI through sports participation; this demographic is too young to legally consent to any potential long-term risks associated with this exposure. To better understand the strength of evidence underlying the possible causal relationship between RHI and CTE, we examined the medical literature through the Bradford Hill criteria for causation. The Bradford Hill criteria, first proposed in 1965 by Sir Austin Bradford Hill, provide a framework to determine if one can justifiably move from an observed association to a verdict of causation. The Bradford Hill criteria include nine viewpoints by which to evaluate human epidemiologic evidence to determine if causation can be deduced: strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment, and analogy. We explored the question of causation by evaluating studies on CTE as it relates to RHI exposure. Through this lens, we found convincing evidence of a causal relationship between RHI and CTE, as well as an absence of evidence-based alternative explanations. By organizing the CTE literature through this framework, we hope to advance the global conversation on CTE mitigation efforts.

Risk of Dementia After Hospitalization Due to Traumatic Brain Injury: A Longitudinal Population-Based Study

BACKGROUND AND OBJECTIVES

Traumatic brain injury (TBI) is considered a potential modifiable dementia risk factor. We aimed to determine whether TBI actually increases the risk of dementia when adjusting for other relevant dementia risk factors.

METHODS

This was a national prospective longitudinal cohort study that included random and representative population samples from different parts of Finland of patients 25 through 64 years of age from 1992 to 2012. Major TBI was defined as a diagnosis of traumatic intracranial hemorrhage and hospital length of stay (LOS) ≥3 days and minor TBI was defined as a diagnosis of concussion and hospital LOS ≤1 day. Dementia was defined as any first hospital contact with a diagnosis of dementia, first use of an antidementia drug, or dementia as an underlying or contributing cause of death. Follow-up was until death or end of 2017.

RESULTS

Of 31,909 participants, 288 were hospitalized due to a major TBI and 406 were hospitalized due to a minor TBI. There was a total of 976 incident dementia cases during a median follow-up of 15.8 years. After adjusting for age and sex, hospitalization due to major TBI (hazard ratio [HR] 1.51, 95% CI 1.03-2.22), but not minor TBI, increased the risk of dementia. After additional adjustment for educational status, smoking status, alcohol consumption, physical activity, and hypertension, the association between major TBI and dementia weakened (HR 1.30, 95% CI 0.86-1.97). The risk factors most strongly attenuating the association between major TBI and dementia were alcohol consumption and physical activity.

DISCUSSION

There was an association between hospitalized major TBI and incident dementia. The association was diluted after adjusting for confounders, especially alcohol consumption and physical activity. Hospitalization due to minor TBI was not associated with an increased risk of dementia.

CLASSIFICATION OF EVIDENCE

This study provides Class I evidence that major TBI is associated with incident dementia.

Consider the woodpecker: The contested more-than-human ethics of biomimetic technology and traumatic brain injury

Chronic Traumatic Encephalopathy, or CTE, is a neurodegenerative disease caused by traumatic brain injury and most frequently associated with contact sports such as American Football. Perhaps surprisingly, the woodpecker - an animal apparently immune to the effects of head impacts - has increasingly figured into debates surrounding CTE. On the one hand, the woodpecker is described as being contra-human and used to underscore the radical inappropriateness of humans playing football. On the other, there have been attempts to mitigate against the risk of CTE through the creation of biomimetic technologies inspired by woodpeckers. In this article I examine the highly politicized encounters between humans and woodpeckers and discuss how the politics of re-/dis-/en-tanglement during these interspecies relations is rendered meaningful. I show here, first, that those who seek to keep the human and the woodpecker apart envisage social overhaul while biomimetic technologies are put to work for the status quo. Second, I stress that different forms of entanglement have diverse sociopolitical consequences. I conclude by suggesting that the case of the woodpecker troubles a strand of contemporary scholarship in Science and Technology Studies that argues that biotechnologies are inherently transformatory and that foregrounding entanglement and interspecies relations is ethically generative. Instead, a discursive separation of nature and culture may be innovative.

High altitude modulates concussion incidence, severity, and recovery in young athletes

BACKGROUND

High altitude may affect concussion, but prior studies are limited . We tested whether high altitude affects sport-related concussion (SRC) incidence, severity, and recovery.

METHODS

Twenty-five thousand eight hundred fifteen baseline and post-injury Immediate Post-Concussion Assessment and Cognitive Testing results were compiled from Florida and Colorado, low (27 m or 62 m) and high (1,640 m or 1,991 m) altitude locations, respectively. Incidence, severity, and recovery of injury were compared between altitudes.

RESULTS

High altitude was associated with increased suspected concussion incidence (adjusted OR, 2.04 [95% CI, 1.86 to 2.24];P < .0001). However, high altitude was associated with lower concussion severity measured by Severity Index (SI) (adjusted OR, 0.42 [95% CI, 0.37 to 0.49];P < .0001). High altitude was associated with decreased recovery from post-concussive symptoms in the migraine (β, -2.72 [95% CI, -3.31 to -2.13]; P < .0001), cognitive (β, -1.88 [95% CI, -2.40 to -1.36]; P < .0001), and sleep symptom clusters (β, -0.30 [95% CI, -0.52 to -0.08]; P = .007). Athletes with initial SI≥8 showed prolonged neurocognitive dysfunction at high altitude (HR, 1.38 [95% CI, 1.06 to 1.81]; P = .02).

CONCLUSIONS

High altitude was associated with increased suspected concussions and prolonged recovery but less severe initial injury.

Development of a Revised Conceptual Framework of Physical Training for Use in Research and Practice

A conceptual framework has a central role in the scientific process. Its purpose is to synthesize evidence, assist in understanding phenomena, inform future research and act as a reference operational guide in practical settings. We propose an updated conceptual framework intended to facilitate the validation and interpretation of physical training measures. This revised conceptual framework was constructed through a process of qualitative analysis involving a synthesis of the literature, analysis and integration with existing frameworks (Banister and PerPot models). We identified, expanded, and integrated four constructs that are important in the conceptualization of the process and outcomes of physical training. These are: (1) formal introduction of a new measurable component 'training effects', a higher-order construct resulting from the combined effect of four possible responses (acute and chronic, positive and negative); (2) explanation, clarification and examples of training effect measures such as performance, physiological, subjective and other measures (cognitive, biomechanical, etc.); (3) integration of the sport performance outcome continuum (from performance improvements to overtraining); (4) extension and definition of the network of linkages (uni and bidirectional) between individual and contextual factors and other constructs. Additionally, we provided constitutive and operational definitions, and examples of theoretical and practical applications of the framework. These include validation and conceptualization of constructs (e.g., performance readiness), and understanding of higher-order constructs, such as training tolerance, when monitoring training to adapt it to individual responses and effects. This proposed conceptual framework provides an overarching model that may help understand and guide the development, validation, implementation and interpretation of measures used for athlete monitoring.

The Effects of On-Field Heat Index and Altitude on Concussion Assessments and Recovery Among NCAA Athletes

BACKGROUND

Recent literature has indicated altitude may be a protective factor for concussion but it is unknown whether altitude or heat index affects recovery.

OBJECTIVE

To examine whether on-field heat index and altitude at the time of injury alter acute (< 48 h) concussion assessments, days-to-asymptomatic, and days-to-return-to-play in collegiate athletes following concussion.

METHODS

Collegiate athletes (n = 187; age = 19.7 ± 1.4 years; male = 70.6%) underwent baseline assessments across 30 universities and experienced a concussion in this retrospective cohort study. Altitude (m) and heat index (°C) at the time and location of injury were determined using valid online database tools. Acute concussion assessments included the Sport Concussion Assessment Tool (SCAT) symptom inventory, Balance Error Scoring System (BESS), and the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT). We used multiple linear regression models to determine whether heat index and altitude predicted each acute assessment outcome, days-to-asymptomatic, and days-to-return-to-play.

RESULTS

Collegiate athletes were concussed at a 181.1 m (range - 0.6 to 2201.9 m) median altitude and 17.8 °C (range - 6.1 to 35.6 °C) median heat index. Altitude did not predict (p ≥ 0.265) any outcomes. Every one-degree increase in heat index reduced days-to-asymptomatic (p = 0.047; R² = 0.06) and days-to-return-to-play (p = 0.006; R² = 0.09) by 0.05 and 0.14 days, respectively. Heat index and altitude did not explain significant variance in SCAT, BESS, and ImPACT composite scores (p's = 0.20-0.922).

CONCLUSION

Our findings suggest that on-field altitude and heat index at the time of injury do not contribute to clinically meaningful changes on acute assessments or concussion recovery. On-field altitude and heat index do not appear to significantly alter assessment outcomes or clinical recovery, suggesting that environmental factors at altitudes below < 2500 m are negligible outcomes for researchers and clinicians to consider post-concussion.

Training Load and Injury Part 2: Questionable Research Practices Hijack the Truth and Mislead Well-Intentioned Clinicians

BACKGROUND

In this clinical commentary, we highlight issues related to conceptual foundations and methods used in training load and injury research. We focus on sources of degrees of freedom that can favor questionable research practices such as P hacking and hypothesizing after the results are known, which can undermine the trustworthiness of research findings.

CLINICAL QUESTION

Is the methodological rigor of studies in the training load and injury field sufficient to inform training-related decisions in clinical practice?

KEY RESULTS

The absence of a clear conceptual framework, causal structure, and reliable methods can promote questionable research practices, selective reporting, and confirmation bias. The fact that well-accepted training principles (eg, overload progression) are in line with some study findings may simply be a consequence of confirmation bias, resulting from cherry picking and emphasizing results that align with popular beliefs. Identifying evidence-based practical applications, grounded in high-quality research, is not currently possible. The strongest recommendation we can make for the clinician is grounded in common sense: "Do not train too much, too soon"-not because it has been confirmed by studies, but because it reflects accepted generic training principles.

CLINICAL APPLICATION

The training load and injury research field has fundamental conceptual and methodological weaknesses. Therefore, making decisions about planning and modifying training programs for injury reduction in clinical practice, based on available studies, is premature. Clinicians should continue to rely on best practice, experience, and well-known training principles, and consider the potential influence of contextual factors when planning and monitoring training loads. J Orthop Sports Phys Ther 2020;50(10):577-584. Epub 1 Aug 2020. doi:10.2519/jospt.2020.9211.

Acute:Chronic Workload Ratio: Conceptual Issues and Fundamental Pitfalls

The number of studies examining associations between training load and injury has increased exponentially. As a result, many new measures of exposure and training-load-based prognostic factors have been created. The acute:chronic workload ratio (ACWR) is the most popular. However, when recommending the manipulation of a prognostic factor in order to alter the likelihood of an event, one assumes a causal effect. This introduces a series of additional conceptual and methodological considerations that are problematic and should be considered. Because no studies have even tried to estimate causal effects properly, manipulating ACWR in practical settings in order to change injury rates remains a conjecture and an overinterpretation of the available data. Furthermore, there are known issues with the use of ratio data and unrecognized assumptions that negatively affect the ACWR metric for use as a causal prognostic factor. ACWR use in practical settings can lead to inappropriate recommendations, because its causal relation to injury has not been established, it is an inaccurate metric (failing to normalize the numerator by the denominator even when uncoupled), it has a lack of background rationale to support its causal role, it is an ambiguous metric, and it is not consistently and unidirectionally related to injury risk. Conclusion: There is no evidence supporting the use of ACWR in training-load-management systems or for training recommendations aimed at reducing injury risk. The statistical properties of the ratio make the ACWR an inaccurate metric and complicate its interpretation for practical applications. In addition, it adds noise and creates statistical artifacts.

Statement on methods in sport injury research from the 1st METHODS MATTER Meeting, Copenhagen, 2019

High quality sports injury research can facilitate sports injury prevention and treatment. There is scope to improve how our field applies best practice methods—methods matter (greatly!). The 1st METHODS MATTER Meeting, held in January 2019 in Copenhagen, Denmark, was the forum for an international group of researchers with expertise in research methods to discuss sports injury methods. We discussed important epidemiological and statistical topics within the field of sports injury research. With this opinion document, we provide the main take-home messages that emerged from the meeting.

Statement on Methods in Sport Injury Research From the First METHODS MATTER Meeting, Copenhagen, 2019

High-quality sports injury research can facilitate sports injury prevention and treatment. There is scope to improve how our field applies best-practice methods-methods matter (greatly!). The first METHODS MATTER meeting, held in January 2019 in Copenhagen, Denmark, was the forum for an international group of researchers with expertise in research methods to discuss sports injury methods. We discussed important epidemiological and statistical topics within the field of sports injury research. With this opinion document, we provide the main take-home messages that emerged from the meeting. Meeting participants agreed that the definition of sport injury depends on the research question and context. It was considered essential to be explicit about the goal of the research effort and to use frameworks to illustrate the assumptions that underpin measurement and the analytical strategy. Complex systems were discussed to illustrate how potential risk factors can interact in a nonlinear way. This approach is often a useful alternative to identifying single risk factors. Investigating changes in exposure status over time is important when analyzing sport injury etiology, and analyzing recurrent injury, subsequent injury, or injury exacerbation remains challenging. The choice of statistical model should consider the research question, injury measure (eg, prevalence, incidence), type and granularity of injury data (categorical or continuous), and study design. Multidisciplinary collaboration will be a cornerstone for future high-quality sport injury research. Working outside professional silos in a diverse, multidisciplinary team benefits the research process, from the formulation of research questions and designs to the statistical analyses and dissemination of study results in implementation contexts. This article has been copublished in the British Journal of Sports Medicine and the Journal of Orthopaedic & Sports Physical Therapy. J Orthop Sports Phys Ther 2020;50(5):226-233. doi:10.2519/jospt.2020.9876.

Modeling the Risk of Team Sport Injuries: A Narrative Review of Different Statistical Approaches

Injuries are a common occurrence in team sports and can have significant financial, physical and psychological consequences for athletes and their sporting organizations. As such, an abundance of research has attempted to identify factors associated with the risk of injury, which is important when developing injury prevention and risk mitigation strategies. There are a number of methods that can be used to identify injury risk factors. However, difficulty in understanding the nuances between different statistical approaches can lead to incorrect inferences and decisions being made from data. Accordingly, this narrative review aims to (1) outline commonly implemented methods for determining injury risk, (2) highlight the differences between association and prediction as it relates to injury and (3) describe advances in statistical modeling and the current evidence relating to predicting injuries in sport. Based on the points that are discussed throughout this narrative review, both researchers and practitioners alike need to carefully consider the different types of variables that are examined in relation to injury risk and how the analyses pertaining to these different variables are interpreted. There are a number of other important considerations when modeling the risk of injury, such as the method of data transformation, model validation and performance assessment. With these technical considerations in mind, researchers and practitioners should consider shifting their perspective of injury etiology from one of reductionism to one of complexity. Concurrently, research implementing reductionist approaches should be used to inform and implement complex approaches to identifying injury risk. However, the ability to capture large injury numbers is a current limitation of sports injury research and there has been a call to make data available to researchers, so that analyses and results can be replicated and verified. Collaborative efforts such as this will help prevent incorrect inferences being made from spurious data and will assist in developing interventions that are underpinned by sound scientific rationale. Such efforts will be a step in the right direction of improving the ability to identify injury risk, which in turn will help improve risk mitigation and ultimately the prevention of injuries.

How (not) to interpret a non-causal association in sports injury science

OBJECTIVE

To discuss the interpretability of non-causal associations to sports injury development exemplified via the relationship between navicular drop (ND) and running-related injury (RRI) in novice runners using neutral shoes.

DESIGN

1-year prospective cohort study.

SETTING

Denmark.

PARTICIPANTS

926 novice runners, representing 1852 feet, were included.

MAIN OUTCOME MEASURE

The outcome was "a musculoskeletal complaint of the lower extremity or back caused by running, which restricted the amount of running for at least a week".

RESULTS

Fewer feet with small ND than those feet with a reference ND sustained injuries at 50 (risk difference (RD) = -4.1% [95%CI = -7.9%;-0.4%]) and 100 km (RD = -5.3% [95%CI = -9.9%;-0.7%]). Similarly, fewer feet with a large ND sustained injuries than the feet with a reference drop at 250 (RD = -7.6% [95%CI = -14.9%;-0.3%]) and 500 km (RD = -9.8% [95%CI = -19.1%;-0.4%]).

CONCLUSION

Non-causal associations can help to identify sub-groups of athletes at an increased or decreased risk of sports injury. Based on the current results, those with a small or large navicular drop sustain fewer injuries than those with a reference drop. Importantly, navicular drop does not cause RRIs, but influences the relationship between training load and RRI. This illustrates that non-causal associations are unsuitable to respond to the question: Why do sports injury develop?