MétaCan
Menu
Back to cohort
Record W4403454644 · doi:10.1016/j.lana.2024.100915

Clinical profile of patients with acute traumatic brain injury undergoing cranial surgery in the United States: report from the 18-centre TRACK-TBI cohort study

2024· article· en· W4403454644 on OpenAlexaff
John K. Yue, John H. Kanter, Jason Barber, Michael C. Huang, Thomas A. van Essen, Mahmoud Elguindy, Brandon Foreman, Frederick K. Korley, Patrick Belton, Dana Pisică, Young Moo Lee, Ryan S. Kitagawa, Mary J. Vassar, Xiaoying Sun, Gabriela Satris, Justin C. Wong, Adam R. Ferguson, J. Russell Huie, Kevin Wang, Hansen Deng, Vincent Y. Wang, Yelena G. Bodien, Sabrina R. Taylor, Debbie Y. Madhok, Michael McCrea, Laura B. Ngwenya, Anthony M. DiGiorgio, Phiroz E. Tarapore, Murray B. Stein, Ava M. Puccio, Joseph T. Giacino, Ramon Diaz‐Arrastia, Hester F. Lingsma, Pratik Mukherjee, Esther L. Yuh, Claudia S. Robertson, David Menon, Andrew I.R. Maas, Amy J. Markowitz, Sonia Jain, David O. Okonkwo, Nancy Temkin, Geoffrey T. Manley

Bibliographic record

VenueThe Lancet Regional Health - Americas · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsQueen Elizabeth II Health Sciences CentreDalhousie University
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesU.S. Department of DefenseU.S. ArmyUniversity of California, San FranciscoOne MindNeurosurgery Research and Education FoundationNational Institute of Neurological Disorders and StrokeAbbott Laboratories
KeywordsTraumatic brain injuryMedicineCohortSurgeryInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Background: Contemporary surgical practices for traumatic brain injury (TBI) remain unclear. We describe the clinical profile of an 18-centre US TBI cohort with cranial surgery. Methods: The prospective, observational Transforming Research and Clinical Knowledge in Traumatic Brain Injury Study (2014-2018; ClinicalTrials.gov #NCT02119182) enrolled subjects who presented to trauma centre and received head computed tomography within 24-h (h) post-TBI. We performed a secondary data analysis in subjects aged ≥17-years with hospitalisation. Clinical characteristics, surgery type/timing, hospital and six-month outcomes were reported. Findings: Of 2032 subjects (age: mean = 41.4-years, range = 17-89-years; male = 71% female = 29%), 260 underwent cranial surgery, comprising 65% decompressive craniectomy, 23% craniotomy, 12% other surgery. Subjects with surgery (vs. without surgery) presented with worse neurological injury (median Glasgow Coma Scale = 6 vs. 15; midline shift ≥5 mm: 48% vs. 2%; cisternal effacement: 61% vs. 4%; p < 0.0001). Median time-to-craniectomy/craniotomy was 1.8 h (interquartile range = 1.1-5.0 h), and 67% underwent intracranial pressure monitoring. Seventy-three percent of subjects with decompressive craniectomy and 58% of subjects with craniotomy had ≥3 intracranial lesion types. Decompressive craniectomy (vs. craniotomy) was associated with intracranial injury severity (median Rotterdam Score = 4 vs. 3, p < 0.0001), intensive care length of stay (median = 13 vs. 4-days, p = 0.0002), and six-month unfavourable outcome (62% vs. 30%; p = 0.0001). Earlier time-to-craniectomy was associated with intracranial injury severity. Interpretation: In a large representative cohort of patients hospitalised with TBI, surgical decision-making and time-to-surgery aligned with intracranial injury severity. Multifocal TBIs predominated in patients with cranial surgery. These findings summarise current TBI surgical practice across US trauma centres and provide the foundation for analyses in targeted subpopulations. Funding: National Institute of Neurological Disorders and Stroke; US Department of Defense; Neurosurgery Research and Education Foundation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.108
GPT teacher head0.397
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueThe Lancet Regional Health - AmericasSame topicTraumatic Brain Injury and Neurovascular DisturbancesFrench-language works237,207