Men more than three times as likely to die from a brain injury

A new analysis of U.S. mortality data reveals the disproportionate impact of traumatic brain injuries (TBI) on older adults, males and certain racial and ethnic groups.

The findings indicate that suicides remain the most common cause of TBI-related deaths, followed by unintentional falls, and specific groups are disproportionately affected by these tragedies.

Men, in particular, were found to be most likely to die from a TBI, more than three times the rate of women (30.5 versus 9.4). The reasons observed were multifactorial and could reflect differences in injury severity following a fall or motor vehicle crash, to the interaction of sex and age, with TBI outcomes in men worsening with age, while postmenopausal women fare better than men of similar age.

“While anyone is at risk for getting a TBI, some groups have a higher chance than others of dying from one. We identified specific populations who are most affected,” said lead author Alexis Peterson at the Centers for Disease Control and Prevention.

“In addition to men, older adults are especially at risk, with unintentional falls being a major cause of TBI-related death. American Indian or Alaska Native people also have higher rates of these fatal injuries.

“These findings highlight the importance of tailored prevention strategies to reach groups who may be at higher risk and the role healthcare providers can play in reducing TBI-related deaths through early intervention and culturally sensitive care.”

TBI remains a leading cause of injury-related death in the U.S. In 2020, TBIs were associated with around a quarter of all injury-related deaths. These injuries can result from a bump, blow, or jolt to the head that disrupts normal brain function, whether unintentional (such as motor vehicle crashes or accidental falls), self-inflicted harm, or related to an assault.

Using data from the National Vital Statistics System, the new analysis identified 69,473 TBI-related deaths among U.S. residents during 2021, an average of 190 deaths per day. The age-adjusted TBI-related mortality rate was 19.5 per 100,000, representing an 8.8 per cent increase from 2020.

Through statistical modelling, the researchers examined the simultaneous effect of multiple factors such as geographic region, sex, race and ethnicity, and age, on TBI-related mortality.

“By assessing patients who may be at higher risk for TBI, especially due to falls or mental health challenges, healthcare providers can make timely referrals and recommend culturally tailored interventions to prevent further injury or death,” said Peterson.

Public health efforts should focus on addressing the underlying causes of TBI-related deaths, such as unintentional falls and mental health crises, to help prevent further loss of life.

“TBIs remain a significant public health concern, especially among older adults, men, and certain racial and ethnic groups,” says Peterson.

“CDC has proven resources that healthcare providers can use to not only reduce health disparities that increase the risk for TBI but also improve care for anyone affected by a TBI.”

The authors note the Covid-19 pandemic could have influenced TBI-related death trends in 2021. They also acknowledge several limitations of this analysis, including potential misclassification or incomplete documentation of causes on death certificates, which may lead to inaccuracies in estimating TBI-related deaths.

Research leads to new insights on preventing brain injury after cardiac arrest

Researchers have identified changes in immune cells just six hours after cardiac arrest that predict patient recovery, pointing to a drug that improved neurological outcomes in preclinical studies.

Despite improvements in CPR and rates of getting patients to the hospital, only about 10 per cent of people ultimately survive after out-of-hospital cardiac arrest (OHCA).

Once in the hospital, most patients who have had a cardiac arrest die of brain injury, and no medications are currently available to prevent this outcome.

A team led by researchers is seeking to address this. Using samples from patients who have had an OHCA, the team uncovered changes in immune cells just six hours after cardiac arrest that can predict brain recovery 30 days later.

They pinpointed a particular population of cells that may provide protection against brain injury and a drug that can activate these cells, which they tested in preclinical models.

“Cardiac arrest outcomes are grim, but I am optimistic about jumping into this field of study because, theoretically, we can treat a patient at the moment injury happens,” said co-senior and corresponding author Edy Kim, at Brigham and Women’s Hospital.

“Immunology is a super powerful way of providing treatment. Our understanding of immunology has revolutionised cancer treatment, and now we have the opportunity to apply the power of immunology to cardiac arrest.”

As a resident physician in the Brigham’s cardiac intensive care unit, Kim noticed that some cardiac arrest patients would have high levels of inflammation on their first night in the hospital and then rapidly improve, while other patients would continue to decline and eventually die.

In order to understand why some patients survive and others do not, Kim and colleagues began to build a biobank—a repository of cryopreserved cells donated by patients with consent from their families just hours after their cardiac arrest.

The researchers used a technique known as single-cell transcriptomics to look at the activity of genes in every cell in these samples. They found that one cell population—known as diverse natural killer T (dNKT) cells—increased in patients who would have a favourable outcome and neurological recovery.

The cells appeared to be playing a protective role in preventing brain injury.

To further test this, Kim and colleagues used a mouse model, treating mice after cardiac arrest with sulfatide lipid antigen, a drug that activates the protective NKT cells. They observed that the mice had improved neurological outcomes.

The researchers note that there are many limitations to mouse models, but making observations from human samples first could increase the likelihood of successfully translating their findings into intervention that can help patients.

Further studies in preclinical models are needed, but their long-term goal is to continue to clinical trials in people to see if the same drug can offer protection against brain injury if given shortly after cardiac arrest.

“This represents a completely new approach, activating T cells to improve neurological outcomes after cardiac arrest,” said Kim.

“And a fresh approach could lead to life-changing outcomes for patients.”

Collaborative solutions in rehabilitation: Tackling MSK and brain injury comorbidities

Approximately 2.41 billion individuals globally are affected by conditions requiring rehabilitation (Cieza et al., 2020), with musculoskeletal (MSK)rehabilitation constituting for nearly two-thirds of this.

MSK disorders are notably widespread, impacting approximately 14.9 million individuals in the UK (Vos et al., 2015).

Also, MSK patients represent one of the largest groups waiting for outpatient appointments within the National Health Service (NHS) (Joesph et al., 2014).

The need for MSK rehabilitation is not a new problem, with the World Health Organization (WHO) having coined the period from 2000 to 2010 as the “bone and joint decade,” reflecting the critical need to research and invest in this area (Woolf & Pfleger, 2003).

In individuals with brain injuries, the prevalence of MSK disorders is notably higher (Cieza et al., 2020), with 79 per cent of traumatic brain injury (TBI) patients having reported MSK complaints (Brown et al., 2011).

As 10 per cent of the NHS budget is devoted to acquired brain injury (Menon et al., 2018), this is a major consideration.

In response to these challenges, FLX Health developed an at-home solution, designed to reduce reliance on physiotherapy appointments, where patients may experience wait times of up to 132 days (Equipsme, 2019).

This initiative is expected to alleviate pressure on healthcare systems by decreasing the prevalence of MSK disorders and their associated impacts on disability (Ma et al., 2014).

This illustrates the potential of the FLX application to address the longstanding challenges in the healthcare sector and how rehabilitation needs innovative advancements to address public need.

MSK disorders can significantly diminish an affected individuals’ quality of life through experienced pain, limiting social engagement, and hindering their earning potential (Liseth Hansen et al., 2023; Hancock et al., 2024; Li et al., 2024).

Among various MSK disorders, lower back pain stands out as the most common, reported as the leading health condition necessitating rehabilitation in 134 of 204 countries (Cieza et al., 2020).

Due to often ambiguous underlying causes, diagnosing lower back pain can be complicated, making it harder to treat (Hartvigsen et al., 2018).

This health condition is only likely to rise due to an ageing population, where lower back pain remains a common reason for early retirement, resulting in further economic implications.

This at-home solution for MSK health issues restores natural movement patterns that may be affected by modern lifestyles.

With 31.3 per cent of the global population not meeting the advised physical activity guidelines, promoting movement through applications like FLX could mitigate the associated risks, such as non-communicable diseases, poor physical and cognitive function, mental ill health and weight gain (Strain et al., 2024).

Moreover, evidence suggests that increased exercise frequency correlates with reduced recurrence of back pain, reinforcing the importance of physical activity in managing MSK disorders and the need for applications like FLX to facilitate healthy ageing (Hancock et al., 2024).

The co-morbidity of MSK injury and brain injury presents unique challenges, as those with brain injuries experience more bodily pain and diminished health status compared to the general population (Galea et al., 2019; Brown et al., 2011).

Various hypotheses explore the neurological mechanisms linking brain injury to MSK disorders, including unresolved neuromuscular impairments (McCann et al., 2022), sensorimotor deficits (Edwards et al., 2022) and changes in motor cortex function (Dubose et al., 2017), all of which necessitate the need for additional investigation.

Therefore, FLX Heath and Kompass launched a project, supported by an NIHR FAST i4i grant to investigate the use of the FLX app within a brain injury population.

It sought to explore the feasibility of enhancing movement within this population, leveraging the combined expertise of the two companies.

This project demonstrated the benefit of technological interventions, with the FLX app providing an at-home solution for MSK issues, and Kompass developing an Outcome Measures Wizard to track the range of metrics that were tracked over the course of the study.

MSK disorders represent a heterogeneous group of disorders, necessitating the use of various outcome measures (OMs) to assess the efficacy of treatment (Woolf et al., 2010).

Also, when assessing the varying extents of a Traumatic Brain Injury (TBI), various OMs have been identified for use (Shulka et al., 2011).

In addition to this, the level of disability due to brain injury can be assessed in numerous ways such as physical measures, mood measures, social measures, and many more.

However, quantitative analysis of MSK and brain injury has lacked significantly (Zhuang et al., 2022), the need for a technological intervention to track the range of quantitative outcome measures is apparent.

The Outcome Measures Wizard fulfilled this perfectly and within the trial of the FLX application within a brain injury population, a range of outcome measures including EQ5D scores and mood measures were successfully tracked.

This demonstrates the utility of technology, firstly in providing the intervention and also in measuring its impact.

Conclusion

Technological development in MSK and brain injury is necessary to improve rehabilitative interventions and to track quantitative outcome measures.

This is pertinent considering the need and effect of rehabilitation in these two areas.

The collaboration between FLX Health and Kompass is testament to the success of interdisciplinary collaboration, demonstrating technological progress through the outcomes of their partnership.

Article Credit

Charlotte Naylor, Research Assistant- Kompass

Sarah Lake, Research Assistant- Kompass

FLX Health- Rob Lewis and Martin Haines

Kompass- Dr Penny Trayner

References 

Brown, S., Hawker, G., Beaton, D., & Colantonio, A. (2011). Long-term musculoskeletal complaints after traumatic brain injury. Brain Injury, 25(5), 453–461. https://doi.org/10.3109/02699052.2011.556581

Cieza, A., Causey, K., Kamenov, K., Hanson, S. W., Chatterji, S., & Vos, T. (2020). Global estimates of the need for rehabilitation based on the Global Burden of Disease study 2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet, 396(10267), 2006–2017. https://doi.org/10.1016/s0140-6736(20)32340-0

Dubose, D. F., Herman, D. C., Jones, D. L., Tillman, S. M., Clugston, J. R., Pass, A., Hernandez, J. A., Vasilopoulos, T., Horodyski, M., & Chmielewski, T. L. (2017). Lower Extremity Stiffness Changes after Concussion in Collegiate Football Players. Medicine and science in sports and exercise, 49(1), 167–172. https://doi.org/10.1249/MSS.0000000000001067

Edwards, D., Williams, J., Carrier, J. & Davies, J. (2022). Technologies used to facilitate remote rehabilitation of adults with deconditioning, musculoskeletal conditions, stroke, or traumatic brain injury: an umbrella review. JBI Evidence Synthesis, 20(8), pp. 1927-1968. https://doi.org/10.11124/JBIES-21-00241

Equipsme. (2019). Patients waiting months to see a physiotherapist in England.https://www.equipsme.com/blog/patients-waiting-months-to-see-a-physiotherapist-in-england/

Galea, O.A., O’Leary, S.P. & Treleaven, J.M. (2019). Persistent impairment based symptoms post mild traumatic brain injury: Does a standard symptom scale detect them?, Musculoskeletal Science and Practice, 41, pp. 15-22. https://doi.org/10.1016/j.msksp.2019.02.002.

Hancock, M.J., Pocovi, N.C., Lin, C.W., French, S.D., Graham, P.L., Van Dongen, J.M., Latimer, J., Merom, D., Tiedemann, A., Maher, C.G., Clavisi, O. & Tong, S.Y.K. (2024). Effectiveness and cost-effectiveness of an individualised, progressive walking and education intervention for the prevention of low back pain recurrence in Australia (WalkBack): a randomised controlled trial. The Lancet, 404 (10448), pp. 134-144. https://doi.org/10.1016/S0140-6736(24)00755-4

Hartvigsen, J., Hancock, M.J., Kongsted, A., Louw, Q., Ferreira, M.L., Genevay, S., Hoy, D., Karppinen, J., Pransky, G., Sieper, J., Smeets, R.J. & Underwood, M. (2018). What low back pain is and why we need to pay attention. The Lancet, 391 (10137). https://doi.org/10.1016/S0140-6736(18)30480-X

Joseph, C., Morrissey, D., Abdur-Rahman, M., Hussenbux, A., & Barton, C. (2014). Musculoskeletal triage: a mixed methods study, integrating systematic review with expert and patient perspectives. Physiotherapy, 100(4), 277-289.

Li, Y., Wang, K., Jigeer, G., Jensen, G., Tucker, K. L., Lv, Y., Shi, X., & Gao, X. (2024). Healthy Lifestyle and the Likelihood of Becoming a Centenarian. JAMA network open, 7(6), e2417931. https://doi.org/10.1001/jamanetworkopen.2024.17931

Liseth Hansen, J.A., Fast, T. & Reidar Wangen. K. (2023). Productivity Loss Across Socioeconomic Groups Among Patients With Low Back Pain or Osteoarthritis: Estimates Using the Friction-Cost Approach in Norway. Pharmacoeconomics, 41(9). pp. 1079-1091. https://doi.org/https://doi.org/10.1007%2Fs40273-023-01269-4

Ma, V.Y., Chan, L. & Carruthers, K.J. (2014). Incidence, Prevalence, Costs, and Impact on Disability of Common Conditions Requiring Rehabilitation in the United States: Stroke, Spinal Cord Injury, Traumatic Brain Injury, Multiple Sclerosis, Osteoarthritis, Rheumatoid Arthritis, Limb Loss, and Back Pain. Archives of Physical Medicine and Rehabilitation, 95(5).  https://doi.org/10.1016/j.apmr.2013.10.032.

McCann, R., Schussler, E., Martinez, J., & Ramirez, V. (2022). The Effect of Concussion History on Lower Extremity Injury Risk in College Athletes: A Systematic Review and Meta-Analysis. International journal of sports physical therapy, 17(5), pp. 753–765. https://doi.org/10.26603/001c.36810

Menon, D., et al. (2018). Acquired Brain Injury and Neurorehabilitation Time For Change: All-Party Parliamentary Group on Acquired Brain Injury Report.https://cdn.ymaws.com/ukabif.org.uk/resource/resmgr/campaigns/appg-abi_report_time-for-cha.pdf

Shukla, D., Devi, B. I., & Agrawal, A. (2011). Outcome measures for traumatic brain injury. Clinical neurology and neurosurgery, 113(6), 435-441.

Strain, T., Flaxman, S., Guthold, R., Semenova, E., Cowan, M., Riley, L.M., Bull, F.C. & Stevens, A. (2024). National, regional, and global trends in insufficient physical activity among adults from 2000 to 2022: a pooled analysis of 507 population-based surveys with 5·7 million participants. The Lancet. https://doi.org/10.1016/S2214-109X(24)00150-5

Vos, T., Barber, R. M., Bell, B., Bertozzi-Villa, A., Biryukov, S., Bolliger, I., Charlson, F., Davis, A., Degenhardt, L., Dicker, D., Duan, L., Erskine, H., Feigin, V. L., Ferrari, A. J., Fitzmaurice, C., Fleming, T., Graetz, N., Guinovart, C., Haagsma, J., … Murray, C. J. L. (2015). Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. The Lancet, 386 (9995), pp. 743–800. https://doi.org/10.1016/s0140-6736(15)60692-4

Woolf, A.D. & Pfleger, B. (2003). Burden of major musculoskeletal conditions. Bulletin of the World Health Organization, 81(9), pp. 646-656. https://pubmed.ncbi.nlm.nih.gov/14710506/

Woolf, A.D., Vos, T. & March, L. (2010). How to measure the impact of musculoskeletal conditions. Best Practice & Research Clinical Rheumatology, 24(6), pp.723-732. https://doi.org/10.1016/j.berh.2010.11.002.

Zhuang, M., Concannon, D. & Manley, E. (2022). A Framework for Evaluating Dashboards in Healthcare. IEEE Transactions on Visualization and Computer Graphics, 28(4), pp. 1715-1731. doi: 10.1109/TVCG.2022.3147154.