Browsing by Author "Clark, David"

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    Association between BrainAGE and Alzheimer's disease biomarkers
    (Wiley, 2025-02-27) Abughofah, Yousaf; Deardorff, Rachael; Vosmeier, Aaron; Hottle, Savannah; Dage, Jeffrey L.; Dempsey, Desarae; Apostolova, Liana G.; Brosch, Jared; Clark, David; Farlow, Martin; Foroud, Tatiana; Gao, Sujuan; Wang, Sophia; Zetterberg, Henrik; Blennow, Kaj; Saykin, Andrew J.; Risacher, Shannon L.; Radiology and Imaging Sciences, School of Medicine
    Introduction: The brain age gap estimation (BrainAGE) method uses a machine learning model to generate an age estimate from structural magnetic resonance imaging (MRI) scans. The goal was to study the association of brain age with Alzheimer's disease (AD) imaging and plasma biomarkers. Methods: One hundred twenty-three individuals from the Indiana Memory and Aging Study underwent structural MRI, amyloid and tau positron emission tomography (PET), and plasma sampling. The MRI scans were processed using the software program BrainAgeR to receive a "brain age" estimate. Plasma biomarker concentrations were measured, and partial Pearson correlation models were used to evaluate their relationship with brain age gap (BAG) estimation (BrainAGE = chronological age - MRI estimated brain age). Results: Significant associations between BAG and amyloid and tau levels on PET and in plasma were observed depending on diagnostic categories. Discussion: These findings suggest that BAG is potentially a biomarker of pathology in AD which can be applied to routine brain imaging. Highlights: Novel research that uses an artificial intelligence learning tool to estimate brain age. Findings suggest that brain age gap is associated with plasma and positron emission tomography Alzheimer's disease (AD) biomarkers. Differential relationships are seen in different stages of disease (preclinical vs. clinical). Results could play a role in early AD diagnosis and treatment.
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    Casemix, management, and mortality of patients rreseceiving emergency neurosurgery for traumatic brain injury in the Global Neurotrauma Outcomes Study: a prospective observational cohort study
    (Elsevier, 2022) Clark, David; Joannides, Alexis; Adeleye, Amos Olufemi; Bajamal, Abdul Hafid; Bashford, Tom; Biluts, Hagos; Budohoski, Karol; Ercole, Ari; Fernández-Méndez, Rocío; Figaji, Anthony; Gupta, Deepak Kumar; Härtl, Roger; Iaccarino, Corrado; Khan, Tariq; Laeke, Tsegazeab; Rubiano, Andrés; Shabani, Hamisi K.; Sichizya, Kachinga; Tewari, Manoj; Tirsit, Abenezer; Thu, Myat; Tripathi, Manjul; Trivedi, Rikin; Devi, Bhagavatula Indira; Servadei, Franco; Menon, David; Kolias, Angelos; Hutchinson, Peter; Global Neurotrauma Outcomes Study collaborative; Neurology, School of Medicine
    Background: Traumatic brain injury (TBI) is increasingly recognised as being responsible for a substantial proportion of the global burden of disease. Neurosurgical interventions are an important aspect of care for patients with TBI, but there is little epidemiological data available on this patient population. We aimed to characterise differences in casemix, management, and mortality of patients receiving emergency neurosurgery for TBI across different levels of human development. Methods: We did a prospective observational cohort study of consecutive patients with TBI undergoing emergency neurosurgery, in a convenience sample of hospitals identified by open invitation, through international and regional scientific societies and meetings, individual contacts, and social media. Patients receiving emergency neurosurgery for TBI in each hospital's 30-day study period were all eligible for inclusion, with the exception of patients undergoing insertion of an intracranial pressure monitor only, ventriculostomy placement only, or a procedure for drainage of a chronic subdural haematoma. The primary outcome was mortality at 14 days postoperatively (or last point of observation if the patient was discharged before this time point). Countries were stratified according to their Human Development Index (HDI)-a composite of life expectancy, education, and income measures-into very high HDI, high HDI, medium HDI, and low HDI tiers. Mixed effects logistic regression was used to examine the effect of HDI on mortality while accounting for and quantifying between-hospital and between-country variation. Findings: Our study included 1635 records from 159 hospitals in 57 countries, collected between Nov 1, 2018, and Jan 31, 2020. 328 (20%) records were from countries in the very high HDI tier, 539 (33%) from countries in the high HDI tier, 614 (38%) from countries in the medium HDI tier, and 154 (9%) from countries in the low HDI tier. The median age was 35 years (IQR 24-51), with the oldest patients in the very high HDI tier (median 54 years, IQR 34-69) and the youngest in the low HDI tier (median 28 years, IQR 20-38). The most common procedures were elevation of a depressed skull fracture in the low HDI tier (69 [45%]), evacuation of a supratentorial extradural haematoma in the medium HDI tier (189 [31%]) and high HDI tier (173 [32%]), and evacuation of a supratentorial acute subdural haematoma in the very high HDI tier (155 [47%]). Median time from injury to surgery was 13 h (IQR 6-32). Overall mortality was 18% (299 of 1635). After adjustment for casemix, the odds of mortality were greater in the medium HDI tier (odds ratio [OR] 2·84, 95% CI 1·55-5·2) and high HDI tier (2·26, 1·23-4·15), but not the low HDI tier (1·66, 0·61-4·46), relative to the very high HDI tier. There was significant between-hospital variation in mortality (median OR 2·04, 95% CI 1·17-2·49). Interpretation: Patients receiving emergency neurosurgery for TBI differed considerably in their admission characteristics and management across human development settings. Level of human development was associated with mortality. Substantial opportunities to improve care globally were identified, including reducing delays to surgery. Between-hospital variation in mortality suggests changes at an institutional level could influence outcome and comparative effectiveness research could identify best practices.
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    Characterizing and validating 12-month reliable cognitive change in Early-Onset Alzheimer's Disease for use in clinical trials
    (Springer, 2025) Hammers, Dustin B.; Musema, Jane; Eloyan, Ani; Thangarajah, Maryanne; Taurone, Alexander; La Joie, Renaud; Touroutoglou, Alexandra; Vemuri, Prashanthi; Kramer, Joel; Aisen, Paul; Dage, Jeffrey L.; Nudelman, Kelly N.; Kirby, Kala; Atri, Alireza; Clark, David; Day, Gregory S.; Duara, Ranjan; Graff-Radford, Neill R.; Grant, Ian; Honig, Lawrence S.; Johnson, Erik C. B.; Jones, David T.; Masdeu, Joseph C.; Mendez, Mario F.; Womack, Kyle; Musiek, Erik; Onyike, Chiadi U.; Riddle, Meghan; Rogalski, Emily; Salloway, Steven; Sha, Sharon J.; Scott Turner, Raymond; Wingo, Thomas S.; Wolk, David A.; Carrillo, Maria C.; Rabinovici, Gil D.; Dickerson, Bradford C.; Apostolova, Liana G.; LEADS Consortium; Neurology, School of Medicine
    Background: As literature suggests that Early-Onset Alzheimer's Disease (EOAD) and late-onset AD may differ in important ways, need exists for randomized clinical trials for treatments tailored to EOAD. Accurately measuring reliable cognitive change in individual patients with EOAD will have great value for these trials. Objectives: The current study sought to characterize and validate 12-month reliable change from the Longitudinal Early-Onset Alzheimer's Disease Study (LEADS) neuropsychological battery. Design: Standardized regression-based (SRB) prediction equations were developed from age-matched cognitively intact participants within LEADS, and applied to clinically impaired participants from LEADS. Setting: Participants were recruited from outpatient academic medical centers. Participants: Participants were enrolled in LEADS and diagnosed with amyloid-positive EOAD (n = 189) and amyloid-negative early-onset cognitive impairment not related to AD (EOnonAD; n = 43). Measurement: 12-month reliable change (Z-scores) was compared between groups across cognitive domain composites, and distributions of individual participant trajectories were examined. Prediction of Z-scores by common AD biomarkers was also considered. Results: Both EOAD and EOnonAD displayed significantly lower 12-month follow-up scores than were predicted based on SRB equations, with declines more pronounced for EOAD across several domains. AD biomarkers of cerebral β-amyloid, tau, and EOAD-specific atrophy were predictive of 12-month change scores. Conclusions: The current results support including EOAD patients in longitudinal clinical trials, and generate evidence of validation for using 12-month reliable cognitive change as a clinical outcome metric in clinical trials in EOAD cohorts like LEADS. Doing so will enhance the success of EOAD trials and permit a better understanding of individual responses to treatment.
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    Differences in baseline cognitive performance between participants with early-onset and late-onset Alzheimer's disease: Comparison of LEADS and ADNI
    (Wiley, 2025) Hammers, Dustin B.; Eloyan, Ani; Thangarajah, Maryanne; Taurone, Alexander; Beckett, Laurel; Gao, Sujuan; Polsinelli, Angelina J.; Kirby, Kala; Dage, Jeffrey L.; Nudelman, Kelly; Aisen, Paul; Reman, Rema; La Joie, Renaud; Lagarde, Julien; Atri, Alireza; Clark, David; Day, Gregory S.; Duara, Ranjan; Graff-Radford, Neill R.; Honig, Lawrence S.; Jones, David T.; Masdeu, Joseph C.; Mendez, Mario F.; Womack, Kyle; Musiek, Erik; Onyike, Chiadi U.; Riddle, Meghan; Grant, Ian; Rogalski, Emily; Johnson, Erik C. B.; Salloway, Steven; Sha, Sharon J.; Turner, Raymond Scott; Wingo, Thomas S.; Wolk, David A.; Carrillo, Maria C.; Dickerson, Bradford C.; Rabinovici, Gil D.; Apostolova, Liana G.; LEADS Consortium 1 for the Alzheimer's Disease Neuroimaging Initiative; Neurology, School of Medicine
    Introduction: Early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD) share similar amyloid etiology, but evidence from smaller-scale studies suggests that they manifest differently clinically. Current analyses sought to contrast the cognitive profiles of EOAD and LOAD. Methods: Z-score cognitive-domain composites for 311 amyloid-positive sporadic EOAD and 314 amyloid-positive LOAD participants were calculated from baseline data from age-appropriate control cohorts. Z-score composites were compared between AD groups for each domain. Results: After controlling for cognitive status, EOAD displayed worse visuospatial, executive functioning, and processing speed/attention skills relative to LOAD, and LOAD displayed worse language, episodic immediate memory, and episodic delayed memory. Discussion: Sporadic EOAD possesses distinct cognitive profiles relative to LOAD. Clinicians should be alert for non-amnestic impairments in younger patients to ensure proper identification and intervention using disease-modifying treatments. Highlights: Both early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD) participants displayed widespread cognitive impairments relative to their same-aged peers. Cognitive impairments were more severe for EOAD than for LOAD participants in visuospatial and executive domains. Memory and language impairments were more severe for LOAD than for EOAD participants Results were comparable after removing clinical phenotypes of posterior cortical atrophy (PCA), primary progressive aphasia (lv-PPA), and frontal-variant AD.
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    Longitudinal cognitive performance of participants with sporadic early onset Alzheimer's disease from LEADS
    (Wiley, 2025) Hammers, Dustin B.; Eloyan, Ani; Taurone, Alexander; Thangarajah, Maryanne; Gao, Sujuan; Beckett, Laurel; Polsinelli, Angelina J.; Kirby, Kala; Dage, Jeffrey L.; Nudelman, Kelly; Aisen, Paul; Reman, Rema; La Joie, Renaud; Lagarde, Julien; Atri, Alireza; Clark, David; Day, Gregory S.; Duara, Ranjan; Graff-Radford, Neill R.; Grant, Ian; Honig, Lawrence S.; Johnson, Erik C. B.; Jones, David T.; Masdeu, Joseph C.; Mendez, Mario F.; Womack, Kyle; Musiek, Erik; Onyike, Chiadi U.; Riddle, Meghan; Rogalski, Emily; Salloway, Steven; Sha, Sharon J.; Turner, Raymond Scott; Wingo, Thomas S.; Wolk, David A.; Carrillo, Maria C.; Rabinovici, Gil D.; Dickerson, Bradford C.; Apostolova, Liana G.; LEADS Consortium; Neurology, School of Medicine
    Introduction: Early-onset Alzheimer's disease (EOAD) manifests prior to the age of 65, and affects 4%-8% of patients with Alzheimer's disease (AD). The current analyses sought to examine longitudinal cognitive trajectories of participants with early-onset dementia. Methods: Data from 307 cognitively normal (CN) volunteer participants and those with amyloid-positive EOAD or amyloid-negative cognitive impairment (EOnonAD) were compared. Cognitive trajectories across a comprehensive cognitive battery spanning 42 months were examined using mixed-effects modeling. Results: The EOAD group displayed worse cognition at baseline relative to EOnonAD and CN groups, and more aggressive declines in cognition over time. The largest effects were observed on measures of executive functioning domains, while memory declines were blunted in EOAD. Discussion: EOAD declined 2-4× faster than EOnonAD, and EOAD pathology is not restricted to memory networks. Early identification of deficits is critical to ensure that individuals with sporadic EOAD can be considered for treatment using disease-modifying medications. Highlights: Represents the most comprehensive longitudinal characterization of sporadic EOAD to date. The trajectory of cognitive declines was steep for EOAD participants and worse than for other groups. Executive functioning measures exhibited the greatest declines over time in EOAD.
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    Psychotropic medication usage in sporadic versus genetic behavioral-variant frontotemporal dementia
    (Wiley, 2025) Vargas-Gonzalez, Juan-Camilo; Dimal, Nico; Cortez, Kasey; Heuer, Hilary; Forsberg, Leah K.; Appleby, Brian S.; Barmada, Sami; Bozoki, Andrea; Clark, David; Cobigo, Yann; Darby, R. Ryan; Dickerson, Bradford C.; Domoto-Reilly, Kimiko; Galasko, Douglas R.; Geschwind, Daniel H.; Ghoshal, Nupur; Graff-Radford, Neill R.; Grant, Ian M.; Irwin, David; Hsiung, Ging-Yuek Robin; Honig, Lawrence S.; Kantarci, Kejal; Léger, Gabriel C.; Litvan, Irene; Mackenzie, Ian R.; Masdeu, Joseph C.; Mendez, Mario F.; Onyike, Chiadi U.; Pascual, Belen; Pressman, Peter; Ramos, Eliana Marisa; Roberson, Erik D.; Rogalski, Emily; Boeve, Brad F.; Boxer, Adam L.; Rosen, Howie J.; Tartaglia, Maria Carmela; ALLFTD Consortium Investigators; Neurology, School of Medicine
    Introduction: Psychotropic medication (PM) use in behavioral-variant frontotemporal dementia (bvFTD) is higher than in other dementias. However, no information exists on whether PM use differs between sporadic and genetic bvFTD. Methods: We analyzed data from sporadic and genetic bvFTD participants with PM prescriptions in the Advancing Research and Treatment in Frontotemporal Lobar Degeneration/Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects study. We estimated ordinal odds ratio (OOR) of having more PM comparing sporadic and genetic bvFTD. Finally, we explored the neuropsychiatric symptom (NPS) combinations using classification and regression trees (CART). Results: We included 263 with sporadic and 193 with genetic bvFTD. The OOR for sporadic bvFTD to be on PM was 1.75 (95% confidence interval: 1.21 to 2.53) for the fully adjusted model. CART revealed the most common NPS combination was apathy + personality changes in 18% of participants. Discussion: Participants with sporadic bvFTD were twice as likely to be on PM compared to genetic bvFTD. The reason for increased PM usage in sporadic bvFTD participants should be further investigated. Highlights: We report on patients with behavioral variant frontotemporal dementia (bvFTD). We evaluated the psychotropic medication (PM) prescription at baseline in the cohort. Patients with sporadic bvFTD had more prescriptions for PM than genetic patients. The frequency of symptoms combination was different in sporadic and genetic bvFTD.
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    Sex differences in clinical phenotypes of behavioral variant frontotemporal dementia
    (Wiley, 2025) Liu, Xulin; de Boer, Sterre C. M.; Cortez, Kasey; Poos, Jackie M.; Illán-Gala, Ignacio; Heuer, Hilary; Forsberg, Leah K.; Casaletto, Kaitlin; Memel, Molly; Appleby, Brian S.; Barmada, Sami; Bozoki, Andrea; Clark, David; Cobigo, Yann; Darby, Ryan; Dickerson, Bradford C.; Domoto-Reilly, Kimiko; Galasko, Douglas R.; Geschwind, Daniel H.; Ghoshal, Nupur; Graff-Radford, Neill R.; Grant, Ian M.; Hsiung, Ging-Yuek Robin; Honig, Lawrence S.; Huey, Edward D.; Irwin, David; Kantarci, Kejal; Léger, Gabriel C.; Litvan, Irene; Mackenzie, Ian R.; Masdeu, Joseph C.; Mendez, Mario F.; Onyike, Chiadi U.; Pascual, Belen; Pressman, Peter; Bayram, Ece; Ramos, Eliana Marisa; Roberson, Erik D.; Rogalski, Emily; Bouzigues, Arabella; Russell, Lucy L.; Foster, Phoebe H.; Ferry-Bolder, Eve; Masellis, Mario; van Swieten, John; Jiskoot, Lize; Seelaar, Harro; Sanchez-Valle, Raquel; Laforce, Robert; Graff, Caroline; Galimberti, Daniela; Vandenberghe, Rik; de Mendonça, Alexandre; Tiraboschi, Pietro; Santana, Isabel; Gerhard, Alexander; Levin, Johannes; Sorbi, Sandro; Otto, Markus; Pasquier, Florence; Ducharme, Simon; Butler, Chris R.; Le Ber, Isabelle; Finger, Elizabeth; Rowe, James B.; Synofzik, Matthis; Moreno, Fermin; Borroni, Barbara; Boeve, Brad F.; Boxer, Adam L.; Rosen, Howie J.; Pijnenburg, Yolande A. L.; Rohrer, Jonathan D.; Tartaglia, Maria Carmela; ALLFTD Consortium; GENFI Consortium; Medicine, School of Medicine
    Introduction: Higher male prevalence in sporadic behavioral variant frontotemporal dementia (bvFTD) has been reported. We hypothesized differences in phenotypes between genetic and sporadic bvFTD females resulting in underdiagnosis of sporadic bvFTD females. Methods: We included genetic and sporadic bvFTD patients from two multicenter cohorts. We compared behavioral and cognitive symptoms, and gray matter volumes, between genetic and sporadic cases in each sex. Results: Females with sporadic bvFTD showed worse compulsive behavior (p = 0.026) and language impairments (p = 0.024) compared to females with genetic bvFTD (n = 152). Genetic bvFTD females had smaller gray matter volumes than sporadic bvFTD females, particularly in the parietal lobe. Discussion: Females with sporadic bvFTD exhibit a distinct clinical phenotype compared to females with genetic bvFTD. This difference may explain the discrepancy in prevalence between genetic and sporadic cases, as some females without genetic mutations may be misdiagnosed due to atypical bvFTD symptom presentation. Highlights: Sex ratio is equal in genetic behavioral variant of frontotemporal dementia (bvFTD), whereas more males are present in sporadic bvFTD. Distinct neuropsychiatric phenotypes exist between sporadic and genetic bvFTD in females. Phenotype might explain the sex ratio difference between sporadic and genetic cases.
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    Traumatic brain injury: progress and challenges in prevention, clinical care, and research
    (Elsevier, 2022) Maas, Andrew I. R.; Menon, David K.; Manley, Geoffrey T.; Abrams, Mathew; Åkerlund, Cecilia; Andelic, Nada; Aries, Marcel; Bashford, Tom; Bell, Michael J.; Bodien, Yelena G.; Brett, Benjamin L.; Büki, András; Chesnut, Randall M.; Citerio, Giuseppe; Clark, David; Clasby, Betony; Cooper, D. Jamie; Czeiter, Endre; Czosnyka, Marek; Dams-O'Connor, Kristen; De Keyser, Véronique; Diaz-Arrastia, Ramon; Ercole, Ari; van Essen, Thomas A.; Falvey, Éanna; Ferguson, Adam R.; Figaji, Anthony; Fitzgerald, Melinda; Foreman, Brandon; Gantner, Dashiell; Gao, Guoyi; Giacino, Joseph; Gravesteijn, Benjamin; Guiza, Fabian; Gupta, Deepak; Gurnell, Mark; Haagsma, Juanita A.; Hammond, Flora M.; Hawryluk, Gregory; Hutchinson, Peter; van der Jagt, Mathieu; Jain, Sonia; Jain, Swati; Jiang, Ji-Yao; Kent, Hope; Kolias, Angelos; Kompanje, Erwin J. O.; Lecky, Fiona; Lingsma, Hester F.; Maegele, Marc; Majdan, Marek; Markowitz, Amy; McCrea, Michael; Meyfroidt, Geert; Mikolić, Ana; Mondello, Stefania; Mukherjee, Pratik; Nelson, David; Nelson, Lindsay D.; Newcombe, Virginia; Okonkwo, David; Orešič, Matej; Peul, Wilco; Pisică, Dana; Polinder, Suzanne; Ponsford, Jennie; Puybasset, Louis; Raj, Rahul; Robba, Chiara; Røe, Cecilie; Rosand, Jonathan; Schueler, Peter; Sharp, David J.; Smielewski, Peter; Stein, Murray B.; von Steinbüchel, Nicole; Stewart, William; Steyerberg, Ewout W.; Stocchetti, Nino; Temkin, Nancy; Tenovuo, Olli; Theadom, Alice; Thomas, Ilias; Torres Espin, Abel; Turgeon, Alexis F.; Unterberg, Andreas; Van Praag, Dominique; van Veen, Ernest; Verheyden, Jan; Vande Vyvere, Thijs; Wang, Kevin K. W.; Wiegers, Eveline J. A.; Williams, W. Huw; Wilson, Lindsay; Wisniewski, Stephen R.; Younsi, Alexander; Yue, John K.; Yuh, Esther L.; Zeiler, Frederick A.; Zeldovich, Marina; Zemek, Roger; InTBIR Participants and Investigators; Physical Medicine and Rehabilitation, School of Medicine
    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.