Traumatic brain injury: progress and challenges in prevention, clinical care, and research

Abstract

Traumatic brain injury (TBI) has the highest incidence of all common neurological disorders, and poses a substantial public health burden. TBI is increasingly documented not only as an acute condition but also as a chronic disease with long-term consequences, including an increased risk of late-onset neurodegeneration. The first Lancet Neurology Commission on TBI, published in 2017, called for a concerted effort to tackle the global health problem posed by TBI. Since then, funding agencies have supported research both in high-income countries (HICs) and in low-income and middle-income countries (LMICs). In November 2020, the World Health Assembly, the decision-making body of WHO, passed resolution WHA73.10 for global actions on epilepsy and other neurological disorders, and WHO launched the Decade for Action on Road Safety plan in 2021. New knowledge has been generated by large observational studies, including those conducted under the umbrella of the International Traumatic Brain Injury Research (InTBIR) initiative, established as a collaboration of funding agencies in 2011. InTBIR has also provided a huge stimulus to collaborative research in TBI and has facilitated participation of global partners. The return on investment has been high, but many needs of patients with TBI remain unaddressed. This update to the 2017 Commission presents advances and discusses persisting and new challenges in prevention, clinical care, and research.

In LMICs, the occurrence of TBI is driven by road traffic incidents, often involving vulnerable road users such as motorcyclists and pedestrians. In HICs, most TBI is caused by falls, particularly in older people (aged ≥65 years), who often have comorbidities. Risk factors such as frailty and alcohol misuse provide opportunities for targeted prevention actions. Little evidence exists to inform treatment of older patients, who have been commonly excluded from past clinical trials—consequently, appropriate evidence is urgently required. Although increasing age is associated with worse outcomes from TBI, age should not dictate limitations in therapy. However, patients injured by low-energy falls (who are mostly older people) are about 50% less likely to receive critical care or emergency interventions, compared with those injured by high-energy mechanisms, such as road traffic incidents.

Mild TBI, defined as a Glasgow Coma sum score of 13–15, comprises most of the TBI cases (over 90%) presenting to hospital. Around 50% of adult patients with mild TBI presenting to hospital do not recover to pre-TBI levels of health by 6 months after their injury. Fewer than 10% of patients discharged after presenting to an emergency department for TBI in Europe currently receive follow-up. Structured follow-up after mild TBI should be considered good practice, and urgent research is needed to identify which patients with mild TBI are at risk for incomplete recovery.

The selection of patients for CT is an important triage decision in mild TBI since it allows early identification of lesions that can trigger hospital admission or life-saving surgery. Current decision making for deciding on CT is inefficient, with 90–95% of scanned patients showing no intracranial injury but being subjected to radiation risks. InTBIR studies have shown that measurement of blood-based biomarkers adds value to previously proposed clinical decision rules, holding the potential to improve efficiency while reducing radiation exposure. Increased concentrations of biomarkers in the blood of patients with a normal presentation CT scan suggest structural brain damage, which is seen on MR scanning in up to 30% of patients with mild TBI. Advanced MRI, including diffusion tensor imaging and volumetric analyses, can identify additional injuries not detectable by visual inspection of standard clinical MR images. Thus, the absence of CT abnormalities does not exclude structural damage—an observation relevant to litigation procedures, to management of mild TBI, and when CT scans are insufficient to explain the severity of the clinical condition.

Although blood-based protein biomarkers have been shown to have important roles in the evaluation of TBI, most available assays are for research use only. To date, there is only one vendor of such assays with regulatory clearance in Europe and the USA with an indication to rule out the need for CT imaging for patients with suspected TBI. Regulatory clearance is provided for a combination of biomarkers, although evidence is accumulating that a single biomarker can perform as well as a combination. Additional biomarkers and more clinical-use platforms are on the horizon, but cross-platform harmonisation of results is needed. Health-care efficiency would benefit from diversity in providers.

In the intensive care setting, automated analysis of blood pressure and intracranial pressure with calculation of derived parameters can help individualise management of TBI. Interest in the identification of subgroups of patients who might benefit more from some specific therapeutic approaches than others represents a welcome shift towards precision medicine. Comparative-effectiveness research to identify best practice has delivered on expectations for providing evidence in support of best practices, both in adult and paediatric patients with TBI.

Progress has also been made in improving outcome assessment after TBI. Key instruments have been translated into up to 20 languages and linguistically validated, and are now internationally available for clinical and research use. TBI affects multiple domains of functioning, and outcomes are affected by personal characteristics and life-course events, consistent with a multifactorial bio-psycho-socio-ecological model of TBI, as presented in the US National Academies of Sciences, Engineering, and Medicine (NASEM) 2022 report. Multidimensional assessment is desirable and might be best based on measurement of global functional impairment. More work is required to develop and implement recommendations for multidimensional assessment. Prediction of outcome is relevant to patients and their families, and can facilitate the benchmarking of quality of care. InTBIR studies have identified new building blocks (eg, blood biomarkers and quantitative CT analysis) to refine existing prognostic models. Further improvement in prognostication could come from MRI, genetics, and the integration of dynamic changes in patient status after presentation.

Neurotrauma researchers traditionally seek translation of their research findings through publications, clinical guidelines, and industry collaborations. However, to effectively impact clinical care and outcome, interactions are also needed with research funders, regulators, and policy makers, and partnership with patient organisations. Such interactions are increasingly taking place, with exemplars including interactions with the All Party Parliamentary Group on Acquired Brain Injury in the UK, the production of the NASEM report in the USA, and interactions with the US Food and Drug Administration. More interactions should be encouraged, and future discussions with regulators should include debates around consent from patients with acute mental incapacity and data sharing. Data sharing is strongly advocated by funding agencies. From January 2023, the US National Institutes of Health will require upload of research data into public repositories, but the EU requires data controllers to safeguard data security and privacy regulation. The tension between open data-sharing and adherence to privacy regulation could be resolved by cross-dataset analyses on federated platforms, with the data remaining at their original safe location. Tools already exist for conventional statistical analyses on federated platforms, however federated machine learning requires further development. Support for further development of federated platforms, and neuroinformatics more generally, should be a priority.

This update to the 2017 Commission presents new insights and challenges across a range of topics around TBI: epidemiology and prevention (section 1); system of care (section 2); clinical management (section 3); characterisation of TBI (section 4); outcome assessment (section 5); prognosis (Section 6); and new directions for acquiring and implementing evidence (section 7). Table 1 summarises key messages from this Commission and proposes recommendations for the way forward to advance research and clinical management of TBI.

Figure 1:. Global incidence and prevalence of traumatic brain injury compared with other common neurological diseases

Data are from multiple sources. Incidence is quantified as the number of cases per year, and prevalence as the number of cases at a given time point. The numbers provided are best estimates. However, it should be recognised that data collection and reporting are inconsistent across different parts of the world, and that data reported for the various diseases do not always reflect exactly the same time period. Modified from a draft provided by Carl Long, NeuroTrauma Sciences.

Figure 2:. Between-country variations in mechanism of traumatic brain injury according to the Human Development Index

Figure modified from Clark et al with permission. HDI=Human Development Index. RTI=road traffic incident.

Figure 3:. Estimated frequency of hospital discharges and deaths in cases of traumatic brain injury by age group in Europe

Figure created using data from Majdan et al.

Figure 4:. Advances and remaining challenges in the provision of health care for people with traumatic brain injury along the trauma chain

Continuity of care along the chain of trauma health care is of paramount importance to achieve good outcomes. If pre-hospital care is inadequate, secondary damage might be so severe that outcome will be poor, no matter how good the in-hospital treatment might be. Conversely, benefits accrued from excellent in-hospital treatment might be lost if they are not consolidated by good post-acute care. Note that many challenges relate to transitions across the links of the trauma chain. TBI=traumatic brain injury. HICs=high-income countries. LMICs=low-income and middle-income countries.

Figure 5:. Consensus-derived matrix for de-escalation of therapy in suspected intracranial hypertension

This decision-support heatmap matrix represents tendencies to wean ongoing treatment for intracranial pressure on the basis of the most recent Marshall CT scan classification and clinical status exam (GCS motor score and pupillary exam) in patients who have been stable for 24, 48, 72, or more than 72 h. Green cells in the table indicate a decision to initiate weaning; red cells indicate a decision to continue treatment; and yellow cells indicate an indeterminate situation, where further consideration is needed (modified with permission from Chesnut et al). GCS=Glasgow Coma Scale. NP=normal pupils. AP=abnormal pupils, without worsening since injury. DI=diffuse injury (graded by the Marshall CT classification—see appendix p 12). EML=evacuated mass lesion.

Figure 6:. Between-centre differences in surgery in acute traumatic brain injury

(A) Acute surgery in acute subdural haematoma, (B) primary decompressive craniectomy in acute subdural haematoma, and (C) early surgery in traumatic intracerebral haematoma. A logistic random-effects model, adjusted for predefined confounders, was used to estimate the acute surgery preference per centre, with corresponding 95% CIs. The MOR reflects the between-centre variation. An MOR equal to 1 represents no variation; the larger the MOR, the larger the variation. The proportion of patients with an acute subdural haematoma undergoing acute surgery ranged from 7% to 52% (IQR 13–35) between centres, with an MOR of 1·84, suggesting an almost two-fold difference in the likelihood of an identical patient receiving surgery in different centres. Furthermore, the type of surgery for acute subdural haematoma varied between centres: the proportion of primary decompressive craniectomies (as opposed to craniotomies) ranged from 6% to 67% (IQR 12–26), with an adjusted MOR for primary decompressive craniectomies of 2·68 (p<0·0001). Of 367 patients with a large traumatic intracerebral haematoma, the proportion who received acute surgery ranged from 13% to 48%, with an MOR of 1·39 (p=0·27). ASDH=acute subdural haematoma. MOR=median odds ratio. TICH=traumatic intracerebral haematoma.

Figure 7:. UpSet plot of pathoanatomic common data elements reported on early CT, by traumatic brain injury severity

(A) Data are from the CENTER-TBI study. (B) Data are from theTRACK-TBI study. Of a potential of 17 imaging CDEs, 14 were included in the analysis. Ventricular compression, mixed density subdural haematoma, and penetrating injuries were excluded as these were either not reported or not included in TRACK-TBI. The vertical bar graphs depict the absolute frequencies of lesion combinations. Combinations with fewer than ten occurrences and CDEs that appeared exclusively in such infrequent combinations are not shown. The horizontal bar graphs depict the absolute frequency of each CDE in the cohort. Traumatic subarachnoid haemorrhage, skull fracture, intraparenchymal haemorrhage (haematoma or contusion), and acute subdural haematoma were the most frequently occurring abnormalities in both studies. Although there are some differences in co-occurrence of abnormalities, five of the top six combinations in each study are consistent. Differences in co-occurrence were probably affected by differences in casemix. However, cisternal compression was less frequently scored in TRACK-TBI and oedema or ischaemia were more frequently scored than in CENTER-TBI, which might reflect differences in reporting. In both studies, co-occurrence of abnormalities was dependent on the severity of the initial injury. CDE=common data elements. TBI=traumatic brain injury. NA=not applicable. SAH=subarachnoid haemorrhage. IPH=intraparenchymal haemorrhage. ASDH=acute subdural haematoma. IVH=intraventricular haemorrhage. EDH=epidural haematoma. DAI=diffuse axonal injury. TAI=traumatic axonal injury.

Figure 8:. Outcomes after a traumatic brain injury: the bio-psycho-socio-ecological model

The pyramid represents how BPSE factors capture individual differences that can substantially affect the outcome trajectory after a traumatic brain injury, in some cases leading to a better outcome and in others leading to a worse than expected outcome. B=biological (eg, brain injury severity, host response, and genetics); P=psychological (eg, coping skills and mental health); S=social (eg, social support and employment); and E=ecological (eg, health-care systems). BPSE=bio-psycho-socio-ecological.

Figure 9:. UpSet plots of impaired scores on outcomes from (A) the CENTER-TBI study and (B) the TRACK-TBI study

Horizontal bars depict the frequencies of impairment on individual assessments; vertical bar scores depict the frequencies of profiles of impairment across all assessments (group sizes fewer than ten are not shown). Both samples include all severities of traumatic brain injury and cases with complete data on all six outcome measures at the 6-month follow-up. Impairment was defined as a Glasgow Outcome Scale-Extended score of less than 8, a Rivermead Post Concussion Symptoms Questionnaire score of at least 16, a Quality of Life After Brain Injury-Overall Scale score of less than 52, a Patient Health Questionnaire-9 Depression Scale score of more than 9, a Generalized Anxiety Disorder-7 score of more than 7, an 18-item Brief Symptom Inventory Anxiety Scale T score of at least 63, and a Post-traumatic Stress Disorder Checklist for DSM-5 score of at least 33. In both datasets, the GOSE is the outcome on which impaired scores are most frequent, followed by the Rivermead Post Concussion Symptoms Questionnaire, the Quality of Life After Brain Injury-Overall Scale, and mental health scales. Heterogenous combinations of impairment are apparent, with a similar order of clinical outcome profiles across studies. The top panel showing data for CENTER-TBI is modified with permission from Wilson et al. PCL-5=Post-traumatic Stress Disorder Checklist for DSM-5. GAD-7=Generalized Anxiety Disorder-7. PHQ-9=Patient Health Questionnaire-9. QOLIBRI-OS=Quality of Life After Brain Injury-Overall Scale. RPQ=Rivermead Post Concussion Symptoms Questionnaire. GOSE=Glasgow Outcome Scale-Extended. BSI-18=18-item Brief Symptom Inventory.

Figure 10:. Calibration plots for external validation of the IMPACT lab models for mortality and unfavorable outcome on data from the CENTER-TBI and TRACK-TBI studies

The correspondence between observed outcomes and predicted risks is shown as LOESS smoothed curves with 95% CI. The red line is the reference with perfect agreement (calibration intercept 0, slope 1). The distribution of predicted risks is shown at the bottom of each graph, stratified by outcome (1 vs 0). LOESS=Locally Estimated Scatterplot Smoothing.

Figure 11:. Absolute incremental value (delta R²) of biomarkers when added to the (left) IMPACT Core and (right) CRASH basic models for predicting mortality and unfavourable outcome

For IMPACT, we selected patients with moderate to severe TBI (Glasgow Coma sum score ≤12; n=737) and for CRASH, patients with a Glasgow Coma sum score of less than 15, thus also including patients with mild TBI (n=1083). Six biomarkers are considered separately, in combination (Comb: GFAP plus UCH-L1), and altogether (All). The vertical lines depict the 95% CIs around the estimates. The explained variance (R²) for the models without biomarkers was as follows: IMPACT Core: 30·7% [95% CI 23·5–37·7] for mortality and 22·6% [15·6–29·1] for unfavourable outcome; CRASH basic: 35·2% [95% CI 28·8–41·8] for mortality and 33·8% [28·4–39·7] for unfavourable outcome. UCH-L1, S100B, and total tau have the greatest incremental value. Combinations of biomarkers appear to have little added value. S100B=S100 calcium-binding protein B. UCH-L1=ubiquitin C-terminal hydrolase L1. GFAP=glial fibrillary acidic protein. NSE=neuron-specific enolase. NfL=neuro-filament light chain. Comb=combination.

Figure 12:. Caterpillar plots of between-centre differences in interventions and outcomes in the CENTER-TBI study

(A) Secondary versus primary referral to a specialised neuro-trauma centre in patients with moderate-to-severe traumatic brain injury. (B) Epidural haematoma surgery during hospitalisation in patients with an epidural haematoma on the admission CT. (C) Ventilator-associated pneumonia in intubated patients admitted to the ICU. (D) Glasgow Outcome Scale–Extended score at 6 months (higher scores on the ordinal scale). To estimate centre-specific effects, a random-effect regression model was created for each intervention and outcome. Each model was adjusted for casemix severity using variables from the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) Lab model: age, Glasgow Coma Scale–motor score, pupillary response, hypoxia, hypotension, Marshall CT classification, presence of traumatic subarachnoid haemorrhage, presence of epidural haematoma (omitted in the model for epidural haematoma surgery), and first glucose and first haemoglobin measurements from blood samples obtained on presentation. Multiple imputation was used for missing values of adjustment variables. For each intervention and outcome, only centres that enrolled at least ten patients from the target subgroup (eg, patients with an epidural haematoma in [B], intubated ICU patients in [C]) were included. As such, the number of centres on the y-axis differs between plots. Centres are ordered by their estimated random effect. For (A), (B), (C), (D), the origin of the x-axis represents the overall log-odds of experiencing the intervention and outcome for all patients from all centres for each respective plot. Random effects of more than 0 mean an increased likelihood and less than 0 mean a decreased likelihood of experiencing the intervention and outcome for a given centre. The MOR is a summary measure of the overall between-centre variation and is interpreted as the odds ratio of experiencing the intervention and outcome for the same patient, when comparing two randomly selected centres. An MOR of 1 indicates no between-centre differences, and larger MORs indicate higher variation. The MORs 95% CIs were derived from the profile likelihood CIs of the random effect SDs. ICU=intensive care unit. TBI=traumatic brain injury. MOR=median odds ratio.