scispace - formally typeset
Search or ask a question
Journal ArticleDOI

Cumulative Effects Associated With Recurrent Concussion in Collegiate Football Players: The NCAA Concussion Study

TL;DR: This study suggests thatPlayers with a history of previous concussions are more likely to have future concussive injuries than those with no history; 1 in 15 players with a concussion may have additional concussions in the same playing season; and previous concussion may be associated with slower recovery of neurological function.
Abstract: ContextApproximately 300 000 sport-related concussions occur annually in the United States, and the likelihood of serious sequelae may increase with repeated head injury.ObjectiveTo estimate the incidence of concussion and time to recovery after concussion in collegiate football players.Design, Setting, and ParticipantsProspective cohort study of 2905 football players from 25 US colleges were tested at preseason baseline in 1999, 2000, and 2001 on a variety of measures and followed up prospectively to ascertain concussion occurrence. Players injured with a concussion were monitored until their concussion symptoms resolved and were followed up for repeat concussions until completion of their collegiate football career or until the end of the 2001 football season.Main Outcome MeasuresIncidence of concussion and repeat concusion; type and duration of symptoms and course of recovery among players who were injured with a concussion during the seasons.ResultsDuring follow-up of 4251 player-seasons, 184 players (6.3%) had a concussion, and 12 (6.5%) of these players had a repeat concussion within the same season. There was an association between reported number of previous concussions and likelihood of incident concussion. Players reporting a history of 3 or more previous concussions were 3.0 (95% confidence interval, 1.6-5.6) times more likely to have an incident concussion than players with no concussion history. Headache was the most commonly reported symptom at the time of injury (85.2%), and mean overall symptom duration was 82 hours. Slowed recovery was associated with a history of multiple previous concussions (30.0% of those with ≥3 previous concussions had symptoms lasting >1 week compared with 14.6% of those with 1 previous concussion). Of the 12 incident within-season repeat concussions, 11 (91.7%) occurred within 10 days of the first injury, and 9 (75.0%) occurred within 7 days of the first injury.ConclusionsOur study suggests that players with a history of previous concussions are more likely to have future concussive injuries than those with no history; 1 in 15 players with a concussion may have additional concussions in the same playing season; and previous concussions may be associated with slower recovery of neurological function.
Citations
More filters
Journal ArticleDOI
TL;DR: Mildtraumatic brain injury occurring among soldiers deployed in Iraq is strongly associated with PTSD and physical health problems 3 to 4 months after the soldiers return home, and after adjustment for PTSD and depression, mild traumatic brain injury was no longer significantly associated with these physical health outcomes or symptoms, except for headache.
Abstract: Of 2525 soldiers, 124 (4.9%) reported injuries with loss of consciousness, 260 (10.3%) reported injuries with altered mental status, and 435 (17.2%) reported other injuries during deployment. Of those reporting loss of consciousness, 43.9% met criteria for post-traumatic stress disorder (PTSD), as compared with 27.3% of those reporting altered mental status, 16.2% with other injuries, and 9.1% with no injury. Soldiers with mild traumatic brain injury, primarily those who had loss of consciousness, were significantly more likely to report poor general health, missed workdays, medical visits, and a high number of somatic and postconcussive symptoms than were soldiers with other injuries. However, after adjustment for PTSD and depression, mild traumatic brain injury was no longer significantly associated with these physical health outcomes or symptoms, except for headache. Conclusions Mild traumatic brain injury (i.e., concussion) occurring among soldiers deployed in Iraq is strongly associated with PTSD and physical health problems 3 to 4 months after the soldiers return home. PTSD and depression are important mediators of the relationship between mild traumatic brain injury and physical health problems.

2,436 citations

Journal ArticleDOI
TL;DR: The 4th International Conference on Concussion in Sport held in Zurich, November 2012 was attended by Paul McCrory, Willem H Meeuwisse, Mark Aubry, Jiří Dvořák, Ruben J Echemendia, Lars Engebretsen, Karen Johnston, Jeffrey S Kutcher, Martin Raftery, Allen Sills and Kathryn Schneider.

2,293 citations

Journal ArticleDOI
TL;DR: This paper is a revision and update of the recommendations developed following the 1st (Vienna 2001), 2nd (Prague 2004) and 3rd (Zurich 2008) International Consensus Conferences on Concussions in Sport and is based on the deliberations at the 4th International Conference on Concussion in Sport held in Zurich, November 2012.
Abstract: The new 2012 Zurich Consensus statement is designed to build on the principles outlined in the previous documents and to develop further conceptual understanding of this problem using a formal consensus-based approach. A detailed description of the consensus process is outlined at the end of this document under the Background section. This document is developed primarily for use by physicians and healthcare professionals who are involved in the care of injured athletes, whether at the recreational, elite or professional level.

2,269 citations

Journal ArticleDOI
TL;DR: This work reviews 48 cases of neuropathologically verified CTE recorded in the literature and document the detailed findings of CTE in 3 professionalathletes, 1 football player and 2 boxers.
Abstract: Since the 1920s, it has been known that the repetitive brain trauma associated with boxing may produce a progressive neurological deterioration, originally termed dementia pugilistica, and more recently, chronic traumatic encephalopathy (CTE). We review 48 cases of neuropathologically verified CTE recorded in the literature and document the detailed findings of CTE in 3 profession althletes, 1 football player and 2 boxers. Clinically, CTE is associated with memory disturbances, behavioral and personality changes, parkinsonism, and speech and gait abnormalities. Neuropathologically, CTE is characterized by atrophy of the cerebral hemispheres, medial temporal lobe, thalamus, mammillary bodies, and brainstem, with ventricular dilatation and a fenestrated cavum septum pellucidum. Microscopically, there are extensive tau-immunoreactive neurofibrillary tangles, astrocytic tangles, and spindle-shaped and threadlike neurites throughout the brain. The neurofibrillary degeneration of CTE is distinguished from other tauopathies by preferential involvement of the superficial cortical layers, irregular patchy distribution in the frontal and temporal cortices, propensity for sulcal depths, prominent perivascular, periventricular, and subpial distribution, and marked accumulation of tau-immunoreactive astrocytes. Deposition of beta-amyloid, most commonly as diffuse plaques, occurs in fewer than half the cases. Chronic traumatic encephalopathy is a neuropathologically distinct slowly progressive tauopathy with a clear environmental etiology.

2,049 citations


Cites background from "Cumulative Effects Associated With ..."

  • ...These studies indicate that safe return to play guidelines might require at least 4 to 6 weeks to facilitate more complete recovery and to protect from reinjury, as a second concussion occurs much more frequently in the immediate period after a concussion (106, 110)....

    [...]

Journal ArticleDOI
19 Nov 2003-JAMA
TL;DR: In this paper, a study of 1631 football players from 15 US colleges found that players with concussions exhibited more severe symptoms (mean GSC score 20.93 [95% confidence interval {CI, 15.65-26.21] points higher than that of controls), cognitive impairments (mean SAC score 2.94 [ 95% CI, 1.41 to 2.06], cognitive functioning improved to baseline levels within 5 to 7 days (day 7 SAC mean difference, −0.33;
Abstract: ContextLack of empirical data on recovery time following sport-related concussion hampers clinical decision making about return to play after injury.ObjectiveTo prospectively measure immediate effects and natural recovery course relating to symptoms, cognitive functioning, and postural stability following sport-related concussion.Design, Setting, and ParticipantsProspective cohort study of 1631 football players from 15 US colleges. All players underwent preseason baseline testing on concussion assessment measures in 1999, 2000, and 2001. Ninety-four players with concussion (based on American Academy of Neurology criteria) and 56 noninjured controls underwent assessment of symptoms, cognitive functioning, and postural stability immediately, 3 hours, and 1, 2, 3, 5, 7, and 90 days after injury.Main Outcome MeasuresScores on the Graded Symptom Checklist (GSC), Standardized Assessment of Concussion (SAC), Balance Error Scoring System (BESS), and a neuropsychological test battery.ResultsNo player with concussion was excluded from participation; 79 players with concussion (84%) completed the protocol through day 90. Players with concussion exhibited more severe symptoms (mean GSC score 20.93 [95% confidence interval {CI}, 15.65-26.21] points higher than that of controls), cognitive impairment (mean SAC score 2.94 [95% CI, 1.50-4.38] points lower than that of controls), and balance problems (mean BESS score 5.81 [95% CI, –0.67 to 12.30] points higher than that of controls) immediately after concussion. On average, symptoms gradually resolved by day 7 (GSC mean difference, 0.33; 95% CI, −1.41 to 2.06), cognitive functioning improved to baseline levels within 5 to 7 days (day 7 SAC mean difference, −0.03; 95% CI, −1.33 to 1.26), and balance deficits dissipated within 3 to 5 days after injury (day 5 BESS mean difference, −0.31; 95% CI, −3.02 to 2.40). Mild impairments in cognitive processing and verbal memory evident on neuropsychological testing 2 days after concussion resolved by day 7. There were no significant differences in symptoms or functional impairments in the concussion and control groups 90 days after concussion.ConclusionsCollegiate football players may require several days for recovery of symptoms, cognitive dysfunction, and postural instability after concussion. Further research is required to determine factors that predict variability in recovery time after concussion. Standardized measurement of postconcussive symptoms, cognitive functioning, and postural stability may enhance clinical management of athletes recovering from concussion.

1,484 citations


Cites background from "Cumulative Effects Associated With ..."

  • ...We previously found that the largest percentage of collegiate football players were withheld from competition for an average of less than 5 days after concussion.(25) The disparity between our data on average recovery time and concurrent reports on time withheld from play after concussion raises concerns based on the common assumption that resuming competition before reaching full recovery may increase the risks of recurrent injury, cumulative impairment, or even catastrophic outcome....

    [...]

  • ...Recent epidemiological and prospective clinical studies estimate that approximately 3% to 8% of high school and collegiate football players sustain a concussion each season.(10,13,15-25) More concerning is the trend toward an increasing rate of concussion in collegiate football over the last 7 years....

    [...]

References
More filters
Journal ArticleDOI
TL;DR: In this article, an extension of generalized linear models to the analysis of longitudinal data is proposed, which gives consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence.
Abstract: SUMMARY This paper proposes an extension of generalized linear models to the analysis of longitudinal data. We introduce a class of estimating equations that give consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence. The estimating equations are derived without specifying the joint distribution of a subject's observations yet they reduce to the score equations for multivariate Gaussian outcomes. Asymptotic theory is presented for the general class of estimators. Specific cases in which we assume independence, m-dependence and exchangeable correlation structures from each subject are discussed. Efficiency of the proposed estimators in two simple situations is considered. The approach is closely related to quasi-likelih ood. Some key ironh: Estimating equation; Generalized linear model; Longitudinal data; Quasi-likelihood; Repeated measures.

17,111 citations

Journal ArticleDOI
TL;DR: A class of generalized estimating equations (GEEs) for the regression parameters is proposed, extensions of those used in quasi-likelihood methods which have solutions which are consistent and asymptotically Gaussian even when the time dependence is misspecified as the authors often expect.
Abstract: Longitudinal data sets are comprised of repeated observations of an outcome and a set of covariates for each of many subjects. One objective of statistical analysis is to describe the marginal expectation of the outcome variable as a function of the covariates while accounting for the correlation among the repeated observations for a given subject. This paper proposes a unifying approach to such analysis for a variety of discrete and continuous outcomes. A class of generalized estimating equations (GEEs) for the regression parameters is proposed. The equations are extensions of those used in quasi-likelihood (Wedderburn, 1974, Biometrika 61, 439-447) methods. The GEEs have solutions which are consistent and asymptotically Gaussian even when the time dependence is misspecified as we often expect. A consistent variance estimate is presented. We illustrate the use of the GEE approach with longitudinal data from a study of the effect of mothers' stress on children's morbidity.

7,080 citations

Book
01 Jan 2001
TL;DR: In this paper, the authors present a model for estimating the effect of random effects on a set of variables in a linear mixed model with the objective of finding the probability of a given variable having a given effect.
Abstract: Preface. Preface to the First Edition. 1. Introduction. 1.1 Models. 1.2 Factors, Levels, Cells, Effects And Data. 1.3 Fixed Effects Models. 1.4 Random Effects Models. 1.5 Linear Mixed Models (Lmms). 1.6 Fixed Or Random? 1.7 Inference. 1.8 Computer Software. 1.9 Exercises. 2. One-Way Classifications. 2.1 Normality And Fixed Effects. 2.2 Normality, Random Effects And MLE. 2.3 Normality, Random Effects And REM1. 2.4 More On Random Effects And Normality. 2.5 Binary Data: Fixed Effects. 2.6 Binary Data: Random Effects. 2.7 Computing. 2.8 Exercises. 3. Single-Predictor Regression. 3.1 Introduction. 3.2 Normality: Simple Linear Regression. 3.3 Normality: A Nonlinear Model. 3.4 Transforming Versus Linking. 3.5 Random Intercepts: Balanced Data. 3.6 Random Intercepts: Unbalanced Data. 3.7 Bernoulli - Logistic Regression. 3.8 Bernoulli - Logistic With Random Intercepts. 3.9 Exercises. 4. Linear Models (LMs). 4.1 A General Model. 4.2 A Linear Model For Fixed Effects. 4.3 Mle Under Normality. 4.4 Sufficient Statistics. 4.5 Many Apparent Estimators. 4.6 Estimable Functions. 4.7 A Numerical Example. 4.8 Estimating Residual Variance. 4.9 Comments On The 1- And 2-Way Classifications. 4.10 Testing Linear Hypotheses. 4.11 T-Tests And Confidence Intervals. 4.12 Unique Estimation Using Restrictions. 4.13 Exercises. 5. Generalized Linear Models (GLMs). 5.1 Introduction. 5.2 Structure Of The Model. 5.3 Transforming Versus Linking. 5.4 Estimation By Maximum Likelihood. 5.5 Tests Of Hypotheses. 5.6 Maximum Quasi-Likelihood. 5.7 Exercises. 6. Linear Mixed Models (LMMs). 6.1 A General Model. 6.2 Attributing Structure To VAR(y). 6.3 Estimating Fixed Effects For V Known. 6.4 Estimating Fixed Effects For V Unknown. 6.5 Predicting Random Effects For V Known. 6.6 Predicting Random Effects For V Unknown. 6.7 Anova Estimation Of Variance Components. 6.8 Maximum Likelihood (Ml) Estimation. 6.9 Restricted Maximum Likelihood (REMl). 6.10 Notes And Extensions. 6.11 Appendix For Chapter 6. 6.12 Exercises. 7. Generalized Linear Mixed Models. 7.1 Introduction. 7.2 Structure Of The Model. 7.3 Consequences Of Having Random Effects. 7.4 Estimation By Maximum Likelihood. 7.5 Other Methods Of Estimation. 7.6 Tests Of Hypotheses. 7.7 Illustration: Chestnut Leaf Blight. 7.8 Exercises. 8. Models for Longitudinal data. 8.1 Introduction. 8.2 A Model For Balanced Data. 8.3 A Mixed Model Approach. 8.4 Random Intercept And Slope Models. 8.5 Predicting Random Effects. 8.6 Estimating Parameters. 8.7 Unbalanced Data. 8.8 Models For Non-Normal Responses. 8.9 A Summary Of Results. 8.10 Appendix. 8.11 Exercises. 9. Marginal Models. 9.1 Introduction. 9.2 Examples Of Marginal Regression Models. 9.3 Generalized Estimating Equations. 9.4 Contrasting Marginal And Conditional Models. 9.5 Exercises. 10. Multivariate Models. 10.1 Introduction. 10.2 Multivariate Normal Outcomes. 10.3 Non-Normally Distributed Outcomes. 10.4 Correlated Random Effects. 10.5 Likelihood Based Analysis. 10.6 Example: Osteoarthritis Initiative. 10.7 Notes And Extensions. 10.8 Exercises. 11. Nonlinear Models. 11.1 Introduction. 11.2 Example: Corn Photosynthesis. 11.3 Pharmacokinetic Models. 11.4 Computations For Nonlinear Mixed Models. 11.5 Exercises. 12. Departures From Assumptions. 12.1 Introduction. 12.2 Misspecifications Of Conditional Model For Response. 12.3 Misspecifications Of Random Effects Distribution. 12.4 Methods To Diagnose And Correct For Misspecifications. 12.5 Exercises. 13. Prediction. 13.1 Introduction. 13.2 Best Prediction (BP). 13.3 Best Linear Prediction (BLP). 13.4 Linear Mixed Model Prediction (BLUP). 13.5 Required Assumptions. 13.6 Estimated Best Prediction. 13.7 Henderson's Mixed Model Equations. 13.8 Appendix. 13.9 Exercises. 14. Computing. 14.1 Introduction. 14.2 Computing Ml Estimates For LMMs. 14.3 Computing Ml Estimates For GLMMs. 14.4 Penalized Quasi-Likelihood And Laplace. 14.5 Exercises. Appendix M: Some Matrix Results. M.1 Vectors And Matrices Of Ones. M.2 Kronecker (Or Direct) Products. M.3 A Matrix Notation. M.4 Generalized Inverses. M.5 Differential Calculus. Appendix S: Some Statistical Results. S.1 Moments. S.2 Normal Distributions. S.3 Exponential Families. S.4 Maximum Likelihood. S.5 Likelihood Ratio Tests. S.6 MLE Under Normality. References. Index.

2,742 citations


"Cumulative Effects Associated With ..." refers methods in this paper

  • ...We controlled for potential confounders using a multivariate generalized Poisson regression model for the rate of concussion.(38-40) This model was implemented using a generalized-estimatingequations approach to account for repeated concussions in the same athlete and clustering of athletes by school....

    [...]

Journal ArticleDOI
19 Nov 2003-JAMA
TL;DR: In this paper, a study of 1631 football players from 15 US colleges found that players with concussions exhibited more severe symptoms (mean GSC score 20.93 [95% confidence interval {CI, 15.65-26.21] points higher than that of controls), cognitive impairments (mean SAC score 2.94 [ 95% CI, 1.41 to 2.06], cognitive functioning improved to baseline levels within 5 to 7 days (day 7 SAC mean difference, −0.33;
Abstract: ContextLack of empirical data on recovery time following sport-related concussion hampers clinical decision making about return to play after injury.ObjectiveTo prospectively measure immediate effects and natural recovery course relating to symptoms, cognitive functioning, and postural stability following sport-related concussion.Design, Setting, and ParticipantsProspective cohort study of 1631 football players from 15 US colleges. All players underwent preseason baseline testing on concussion assessment measures in 1999, 2000, and 2001. Ninety-four players with concussion (based on American Academy of Neurology criteria) and 56 noninjured controls underwent assessment of symptoms, cognitive functioning, and postural stability immediately, 3 hours, and 1, 2, 3, 5, 7, and 90 days after injury.Main Outcome MeasuresScores on the Graded Symptom Checklist (GSC), Standardized Assessment of Concussion (SAC), Balance Error Scoring System (BESS), and a neuropsychological test battery.ResultsNo player with concussion was excluded from participation; 79 players with concussion (84%) completed the protocol through day 90. Players with concussion exhibited more severe symptoms (mean GSC score 20.93 [95% confidence interval {CI}, 15.65-26.21] points higher than that of controls), cognitive impairment (mean SAC score 2.94 [95% CI, 1.50-4.38] points lower than that of controls), and balance problems (mean BESS score 5.81 [95% CI, –0.67 to 12.30] points higher than that of controls) immediately after concussion. On average, symptoms gradually resolved by day 7 (GSC mean difference, 0.33; 95% CI, −1.41 to 2.06), cognitive functioning improved to baseline levels within 5 to 7 days (day 7 SAC mean difference, −0.03; 95% CI, −1.33 to 1.26), and balance deficits dissipated within 3 to 5 days after injury (day 5 BESS mean difference, −0.31; 95% CI, −3.02 to 2.40). Mild impairments in cognitive processing and verbal memory evident on neuropsychological testing 2 days after concussion resolved by day 7. There were no significant differences in symptoms or functional impairments in the concussion and control groups 90 days after concussion.ConclusionsCollegiate football players may require several days for recovery of symptoms, cognitive dysfunction, and postural instability after concussion. Further research is required to determine factors that predict variability in recovery time after concussion. Standardized measurement of postconcussive symptoms, cognitive functioning, and postural stability may enhance clinical management of athletes recovering from concussion.

1,484 citations


"Cumulative Effects Associated With ..." refers methods in this paper

  • ...Additionally, 17 of the participating schools were randomly assigned to an “assessment group” and were asked to use a brief battery of concussion assessment tools.(35) Members of the research team retrospectively graded concussion severity using the information regarding symptom duration on the concussion index....

    [...]

Journal Article
TL;DR: Improved guidelines for clinical management of concussion may be formulated as the functional significance and duration of these postinjury neurometabolic derangements are better delineated.
Abstract: OBJECTIVE: To review the underlying pathophysiologic processes of concussive brain injury and relate these neurometabolic changes to clinical sports-related issues such as injury to the developing brain, overuse injury, and repeated concussion DATA SOURCES: Over 100 articles from both basic science and clinical medical literature selected for relevance to concussive brain injury, postinjury pathophysiology, and recovery of function DATA SYNTHESIS: The primary elements of the pathophysiologic cascade following concussive brain injury include abrupt neuronal depolarization, release of excitatory neurotransmitters, ionic shifts, changes in glucose metabolism, altered cerebral blood flow, and impaired axonal function These alterations can be correlated with periods of postconcussion vulnerability and with neurobehavioral abnormalities While the time course of these changes is well understood in experimental animal models, it is only beginning to be characterized following human concussion CONCLUSIONS/RECOMMENDATIONS: Following concussion, cerebral pathophysiology can be adversely affected for days in animals and weeks in humans Significant changes in cerebral glucose metabolism can exist even in head-injured patients with normal Glasgow Coma Scores, underscoring the need for in-depth clinical assessment in an effort to uncover neurocognitive correlates of altered cerebral physiology Improved guidelines for clinical management of concussion may be formulated as the functional significance and duration of these postinjury neurometabolic derangements are better delineated

1,318 citations


"Cumulative Effects Associated With ..." refers background in this paper

  • ...Although this theory has yet to be confirmed in a human model, animal research has identified acute metabolic dysfunction following cerebral concussion that might explain the increased neuronal vulnerability that can exist for several days following injury.(26-30) The purposes of this study were to examine the association between history of previous concussions and likelihood of experiencing recurrent concussions and to compare time to recovery following concussion between athletes with a history of previous concussion compared with those without a history of previous concussion....

    [...]

  • ...The increased lactate is believed to leave neurons more vulnerable to secondary ischemic injury and has been considered a possible predisposition to repeat injury.(26,27) Later steps in this physiologic Table 3....

    [...]

Related Papers (5)