Sex &amp; gender considerations in concussion research

Mollayeva, Tatyana; El-Khechen-Richandi, Graziella; Colantonio, Angela

doi:10.2217/cnc-2017-0015

Cited by 86 publications

(69 citation statements)

References 51 publications

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“…ere are various reasons as to why females experience more symptoms and greater severity of symptoms after suffering a concussion compared with their male counterparts. Biomechanical differences seem to contribute to symptom status due to disparities in the neck musculature and head/neck stability in females making them more susceptible to injury [6]. Males also have greater cortical neuronal densities, while females have a greater number of neuropils [11].…”

Section: Agementioning

confidence: 99%

“…ere is also evidence that females report more symptoms and a greater severity of symptoms than males after suffering a concussion because it is more socially acceptable for women to admit vulnerability than it is for men [6]. However, Broshek et al [11] reported that females do in fact experience more severe postconcussion symptoms than males and that poorer outcomes are not simply due to cultural-based sex differences in symptom reporting.…”

Section: Agementioning

confidence: 99%

“…Understanding how age, gender, and certain comorbid conditions affect the symptomology of a concussion is an essential aspect of concussion management [10]. e idea that sex plays a role in symptom presentation and recovery after a concussion is a consistent pattern in the literature [6]. In one study, females self-reported significantly more symptoms following a concussion than males [11].…”

Section: Introductionmentioning

confidence: 99%

“…In teenagers and young adults between the ages of 15 and24, sport-related concussions (SRCs) are second to motor vehicle accidents [5]. In sex-comparable sports, the data also reveal higher rates of concussions in females than males [6]. Headache and dizziness are the most common concussion symptoms, with some of the other wellknown symptoms being confusion, light sensitivity, nausea, fatigue, and amnesia [7].…”

Section: Introductionmentioning

confidence: 99%

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Interaction between Age, Sex, and Mental Health Status as Precipitating Factors for Symptom Presentation in Concussed Individuals

Lariviere

Bureau

Marshall³

et al. 2019

Journal of Sports Medicine

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Concussions are among the most common neurological conditions, with emergency departments and sports injury clinics seeing hundreds of patients each year. The consideration of risk factors such as age, sex, and comorbid conditions are very important when looking at individual physiological and psychological outcomes after a concussion. The purpose of this study was to look at four comorbid conditions (depression, anxiety, behavioural disorder, or learning disability) and identify any interactions with age and sex in symptom presentation after suffering a concussion. A total of 4,865 participants from the CCMI (Complete Concussion Management Inc.) dataset were used with 1,577 self-identified with a diagnosis of anxiety, depression, a behavioural disorder, or a learning disability. Fixed-factor analyses of variance were used with age and sex as fixed, grouping factors and symptom total and severity as dependent measures. For the individuals who did not have one of the 4 mental health conditions (3,288 control participants), symptom total and symptom severity increased with age (p<0.05), and females showed more symptoms and a higher symptom severity than males across all ages (p<0.05). A diagnosis of anxiety or depression exacerbated total symptoms and symptom severity from 25–50% above control levels in the 19 and under age groups, while depression or anxiety exacerbated total symptoms and severity by 10–15% in males more than females over 20. A diagnosis of a behavioural disorder or a learning disability exacerbated symptom severity by approximately 50% above control levels in 13–19–year-old females and in males of 30 years and older. This study highlights how the presence of a mental health condition may alter concussion symptom presentation dependent on age and sex. The identification of risk factors and how they may interact can be of great value to health care providers who manage concussion symptoms and recovery.

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Section: Agementioning

confidence: 99%

Section: Agementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Interaction between Age, Sex, and Mental Health Status as Precipitating Factors for Symptom Presentation in Concussed Individuals

Lariviere

Bureau

Marshall³

et al. 2019

Journal of Sports Medicine

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“…We have also reported the effects of neurofeedback on these changes during the acute recovery period (Ims & Kerasidis, 2018). Studies have identified gender differences in the incidence, severity, and recovery time from sport concussion injury, all increased in females (Cantu, 2010;Hamson-Utley et al, 2013;Miyashita, Diakogeorgiou, & VanderVegt, 2016;Mollayeva, El-Khechen-Richandi, & Colantonio, 2018;Tanveer, Zecavati, Delasobera, & Oyegbile, 2017). The objective of this investigation is to explore gender differences in volumetric qEEG analysis after sport concussion injury in high school athletes.…”

Section: Introductionmentioning

confidence: 99%

Proceedings of the 2018 ISNR Annual Conference

Research¹

2018

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Validation of a Machine Learning Brain Electrical Activity–Based Index to Aid in Diagnosing Concussion Among Athletes

et al. 2021

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IMPORTANCE An objective, reliable indicator of the presence and severity of concussive brain injury and of the readiness for the return to activity has the potential to reduce concussion-related disability. OBJECTIVE To validate the classification accuracy of a previously derived, machine learning, multimodal, brain electrical activity-based Concussion Index in an independent cohort of athletes with concussion. DESIGN, SETTING, AND PARTICIPANTS This prospective diagnostic cohort study was conducted at 10 clinical sites (ie, US universities and high schools) between February 4, 2017, and March 20, 2019. A cohort comprising a consecutive sample of 207 athletes aged 13 to 25 years with concussion and 373 matched athlete controls without concussion were assessed with electroencephalography, cognitive testing, and symptom inventories within 72 hours of injury, at return to play, and 45 days after return to play. Variables from the multimodal assessment were used to generate a Concussion Index at each time point. Athletes with concussion had experienced a witnessed head impact, were removed from play for 5 days or more, and had an initial Glasgow Coma Scale score of 13 to 15. Participants were excluded for known neurologic disease or history within the last year of traumatic brain injury. Athlete controls were matched to athletes with concussion for age, sex, and type of sport played. MAIN OUTCOMES AND MEASURES Classification accuracy of the Concussion Index at time of injury using a prespecified cutoff of 70 or less (total range, 0-100, where Յ70 indicates it is likely the individual has a concussion and >70 indicates it is likely the individual does not have a concussion). RESULTS Of 580 eligible participants with analyzable data, 207 had concussion (124 male participants [59.9%]; mean [SD] age, 19.4 [2.5] years), and 373 were athlete controls (187 male participants [50.1%]; mean [SD] age, 19.6 [2.2] years). The Concussion Index had a sensitivity of 86.0% (95% CI, 80.5%-90.4%), specificity of 70.8% (95% CI, 65.9%-75.4%), negative predictive value of 90.1% (95% CI, 86.1%-93.3%), positive predictive value of 62.0% (95% CI, 56.1%-67.7%), and area under receiver operator characteristic curve of 0.89. At day 0, the mean (SD) Concussion Index among athletes with concussion was significantly lower than among athletes without concussion (75.0 [14.0] vs 32.7 [27.2]; P < .001). Among athletes with concussion, there was a significant increase in the Concussion Index between day 0 and return to play, with a mean (SD) paired difference between these time points of −41.2 (27.0) (P < .001). CONCLUSIONS AND RELEVANCE These results suggest that the multimodal brain activity-based Concussion Index has high classification accuracy for identification of the likelihood of concussion at time of injury and may be associated with the return to control values at the time of recovery. The (continued) Key Points Question Can the previously derived, machine learning, multimodal, brain electrical activity-based Concussion Index be prospectively ...

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Sex & gender considerations in concussion research

Cited by 86 publications

References 51 publications

Interaction between Age, Sex, and Mental Health Status as Precipitating Factors for Symptom Presentation in Concussed Individuals

Interaction between Age, Sex, and Mental Health Status as Precipitating Factors for Symptom Presentation in Concussed Individuals

Proceedings of the 2018 ISNR Annual Conference

Validation of a Machine Learning Brain Electrical Activity–Based Index to Aid in Diagnosing Concussion Among Athletes

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