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Traumatic brain injury: progress and challenges in prevention, clinical care, and research
Andrew I.R. Maas, David Menon, Geoffrey T. Manley, Mathew Abrams, Cecilia Åkerlund, Nada Anđelić, Marcel Aries, Tom Bashford, Michael J. Bell, Yelena G. Bodien, Benjamin L. Brett, András Büki, Randall M. Chesnut, Giuseppe Citerio, David Clark, Betony Clasby, D. James Cooper, Endre Czeiter, Marek Czosnyka, Kristen Dams-O’Connor, Véronique De Keyser, Ramon Diaz‐Arrastia, Ari Ercole, Thomas A. van Essen, Éanna Falvey, Adam R. Ferguson, Anthony Figaji, Melinda Fitzgerald, Brandon Foreman, Dashiell Gantner, Guoyi Gao, Joseph T. Giacino, Benjamin Gravesteijn, Fabián Güiza, Deepak Gupta, Mark Gurnell, Juanita A. Haagsma, Flora M. Hammond, Gregory W. J. Hawryluk, Peter J. Hutchinson, Mathieu van der Jagt, Sonia Jain, Swati Jain, Jiyao Jiang, Hope Kent, Angelos G. Kolias, Erwin J. O. Kompanje, Fiona Lecky, Hester F. Lingsma, Marc Maegele, Marek Majdán, Amy J. Markowitz, Michael McCrea, Geert Meyfroidt, Ana Mikolić, Stefania Mondello, Pratik Mukherjee, David Nelson, Lindsay D. Nelson, Virginia Newcombe, David O. Okonkwo, Matej Orešič, Wilco C. Peul, Dana Pisică, Suzanne Polinder, Jennie Ponsford, Louis Puybasset, Rahul Raj, Chiara Robba, Cecilie Røe, Jonathan Rosand, Peter Schueler, David Sharp, Peter Smielewski, Murray B. Stein, Nicole von Steinbüchel, William Stewart, Ewout W. Steyerberg, Nino Stocchetti, Nancy Temkin, Olli Tenovuo, Alice Theadom, Ilias Thomas, Abel Torres‐Espín, Alexis F. Turgeon, Andreas Unterberg, Dominique Van Praag, Ernest van Veen, Jan Verheyden, Thijs Vande Vyvere, Kevin Wang, Eveline Wiegers, W. Huw Williams, Lindsay Wilson, Stephen R. Wisniewski, Alexander Younsi, John K. Yue, Esther L. Yuh, Frederick A. Zeiler, Marina Zeldovich, Roger Zemek
Bibliographic record
VenueThe Lancet Neurology · 2022
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsnot available
FundersSchool of Medicine, University of California, San DiegoDepartment of Radiology and Biomedical Imaging, University of California, San FranciscoNational Institute of Neurological Disorders and StrokeFaculty of Medicine and Health, University of SydneyUCLH Biomedical Research CentreCanadian Institutes of Health ResearchNational Institutes of HealthDepartment of Anesthesiology and Critical Care Medicine, Johns Hopkins MedicineUniversiteit AntwerpenSorbonne UniversitéTurun Yliopistollinen KeskussairaalaMonash UniversityUniversità degli Studi di MessinaMassachusetts General HospitalUniversity of Cape TownLeids Universitair Medisch CentrumKarolinska InstitutetTurun YliopistoSchool of Medicine, Indiana UniversityUniversity of PittsburghKU LeuvenGraduate School of Public Health, University of PittsburghEisaiÖrebro UniversitetZNS - Hannelore Kohl StiftungUniversity of WashingtonCurtin University of TechnologyPerelman School of Medicine, University of PennsylvaniaUniversity of GlasgowUniversiteit LeidenUniversity of ExeterCurtin Health Innovation Research Institute, Curtin UniversityAcademy of Medical SciencesOne MindACADIA PharmaceuticalsJazz PharmaceuticalsBrain Injury Research CenterUniversity of California, San DiegoHelsingin YliopistoUniversité LavalUniversity of StirlingUniversity of PennsylvaniaU.S. Department of Veterans AffairsGlaxoSmithKlineImperial College LondonNIHR Cambridge Biomedical Research CentreIntegra LifeSciencesUniversity of OttawaAuckland University of Technology, New ZealandRenji HospitalUniversity of CincinnatiUniversitätsklinikum HeidelbergCentre Hospitalier Universitaire de QuébecUniversity College CorkUniversità degli Studi di GenovaEuropean CommissionNational Institute for Health and Care ResearchAssistance publique-Hôpitaux de ParisU.S. Department of Defense
KeywordsTraumatic brain injuryMedicinePublic healthSocietal impact of nanotechnologyHealth careGlobal healthPsychiatryMedical emergencyPolitical scienceNursing
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.018
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
Opus teacher head0.504
GPT teacher head0.510
Teacher spread0.006 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".
Quick stats
Citations1,353
Published2022
Admission routes1
Has abstractno