Update on the Epidemiology of Concussion/Mild Traumatic Brain Injury

Voss, Jameson D.; Connolly, J.; Schwab, Karen; Scher, Ann I.

doi:10.1007/s11916-015-0506-z

Cited by 128 publications

(97 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…34 Moreover, code 959.01 is also associated with a high number of false negatives, 34 the CDC-recommended codes have low sensitivity, 34 and a substantial proportion of MTBIs still do not result in any medical consultation at all. 1 Thus, we used the CDC- recommended codes to identify MTBI because these codes are widely used in the literature. Until future algorithms for identifying MTBI using administrative data are developed, we feel that it was appropriate to use these codes so that our results are comparable with other studies in this area.…”

Section: Discussionmentioning

confidence: 99%

“…The Nationwide Emergency Department Sample (NEDS), 13 part of the Healthcare Cost and Utilization Project (HCUP), managed by the U.S. Agency for Healthcare Research and Quality, 1 was analyzed using data from January 1, 2006 through December 31, 2012. The NEDS tracks information about ED visits across the U.S. and is the largest all-payer ED database available in the country with data available beginning in 2006.…”

Section: Methodsmentioning

confidence: 99%

“…1 MTBI is one of the most common neurological conditions in the world, 2 and is a serious public health problem in the U.S. 3 In 2010, a combined total of 2.5 million TBI-related emergency department visits, hospitalizations and deaths were reported. These TBIs were either an isolated injury, with TBI as the only injury, or present along with other injuries.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Epidemiology of Isolated Versus Nonisolated Mild Traumatic Brain Injury Treated in Emergency Departments in the United States, 2006-2012: Sociodemographic Characteristics

Cancelliere

Coronado

Taylor³

et al. 2017

Journal of Head Trauma Rehabilitation

View full text Add to dashboard Cite

Objectives To describe the frequencies and rates of MTBI ED visits, and analyze the trend across the years; and to compare sociodemographic characteristics of visits by MTBI type (i.e., MTBI as the only injury, or present along with other injuries). Design Population-based descriptive study using data from the Nationwide Emergency Department Sample (NEDS, 2006–2012). Methods Joinpoint regression was used to calculate the average annual percent changes (AAPCs) of MTBI incidence rates. Characteristics between isolated and non-isolated visits were compared, and the odds ratios were reported. Results The rate per 100,000 population of MTBI ED visits in the U.S. increased significantly from 569.4 in 2006 to 807.9 in 2012. The highest rates were observed in 0–4 year olds, followed by 15–24 year old males, and ≥65 year old females; the lowest rates were among 45–64 year olds. The majority (70%) of all visits were non-isolated, and occurred more frequently in residents of metropolitan areas. Falls were the leading external cause. Most visits were privately insured or covered by Medicare/Medicaid, and the injury occurred on weekdays in predominantly metropolitan hospitals in the South region. Conclusions The burden of MTBI in U.S. EDs is high. Most MTBI ED visits present with other injuries. Awareness of sociodemographic factors associated with non-isolated MTBI may help improve diagnosis in U.S. EDs. This information has implications for resource planning and MTBI screening in EDs.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Epidemiology of Isolated Versus Nonisolated Mild Traumatic Brain Injury Treated in Emergency Departments in the United States, 2006-2012: Sociodemographic Characteristics

Cancelliere

Coronado

Taylor³

et al. 2017

Journal of Head Trauma Rehabilitation

View full text Add to dashboard Cite

show abstract

“…Concussion spans all age groups and includes specialised subpopulations such as athletes and military personnel (1,2). Despite the high prevalence and societal burden, concussion pathophysiology is unclear (3).…”

Section: Introductionmentioning

confidence: 99%

An investigation of neuroinjury biomarkers after sport-related concussion: from the subacute phase to clinical recovery

et al. 2018

View full text Add to dashboard Cite

Objectives: To characterise a panel of neuroinjury-related blood biomarkers after sport-related concussion (SRC). We hypothesised significant differences in biomarker profiles between athletes with SRC and healthy controls at both subacute and medical clearance time points. Methods: Thirty-eight interuniversity athletes were recruited over two athletic seasons (n = 19 SRC; n = 19 healthy matched-control). High-sensitivity immunoassay was used to evaluate 11 blood analytes at both the subacute phase after SRC and at medical clearance. Results: Univariate analysis identified elevated circulating peroxiredoxin-6 (PRDX-6) in athletes with SRC compared to healthy controls at the subacute time point. Multivariate analyses yielded similar results in the subacute phase, but identified both PRDX-6 and T-tau as significant contributors to class separation between athletes with SRC and controls at medical clearance. Conclusions: Our results are consistent with the increasing recognition that physiological recovery after SRC extends beyond clinical recovery. Blood biomarkers appear to be useful in elucidating the biology of brain restitution after SRC. However, their implementation requires mindfulness of factors such as academic stress, exercise, and injury heterogeneity. ARTICLE HISTORY

show abstract

“…Approximately 70% of TBI cases are caused by sudden acceleration/deceleration of the head resulting from falls, traffic and sport accidents, among others[1]. Over 85% of TBIs are mild, also called concussion, and result in large part from playing contact sports [2]. The physical forces of impact can be measured, recorded and analyzed in the context of the biological response.…”

mentioning

confidence: 99%

Big Data in traumatic brain injury; promise and challenges

Agoston

Langford

2017

Concussion

View full text Add to dashboard Cite

Traumatic brain injury (TBI) is a spectrum disease of overwhelming complexity, the research of which generates enormous amounts of structured, semi-structured and unstructured data. This resulting big data has tremendous potential to be mined for valuable information regarding the “most complex disease of the most complex organ”. Big data analyses require specialized big data analytics applications, machine learning and artificial intelligence platforms to reveal associations, trends, correlations and patterns not otherwise realized by current analytical approaches. The intersection of potential data sources between experimental TBI and clinical TBI research presents inherent challenges for setting parameters for the generation of common data elements and to mine existing legacy data that would allow highly translatable big data analyses. In order to successfully utilize big data analyses in TBI, we must be willing to accept the messiness of data, collect and store all data and give up causation for correlation. In this context, coupling the big data approach to established clinical and pre-clinical data sources will transform current practices for triage, diagnosis, treatment and prognosis into highly integrated evidence-based patient care.

show abstract

Update on the Epidemiology of Concussion/Mild Traumatic Brain Injury

Cited by 128 publications

References 41 publications

Epidemiology of Isolated Versus Nonisolated Mild Traumatic Brain Injury Treated in Emergency Departments in the United States, 2006-2012: Sociodemographic Characteristics

Epidemiology of Isolated Versus Nonisolated Mild Traumatic Brain Injury Treated in Emergency Departments in the United States, 2006-2012: Sociodemographic Characteristics

An investigation of neuroinjury biomarkers after sport-related concussion: from the subacute phase to clinical recovery

Big Data in traumatic brain injury; promise and challenges

Contact Info

Product

Resources

About