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Record W4210381697 · doi:10.3171/2021.10.jns211794

External validation of the updated Brain Injury Guidelines for complicated mild traumatic brain injuries: a retrospective cohort study

2022· article· en· W4210381697 on OpenAlexafffundabout

Bibliographic record

VenueJournal of neurosurgery · 2022
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsMcGill UniversityUniversité de MontréalCentre hospitalier de l'Université LavalUniversité Laval
FundersUniversité Laval
KeywordsRetrospective cohort studyTraumatic brain injuryCohort studyTrauma centerMEDLINECenter (category theory)Poison control

Abstract

fetched live from OpenAlex

OBJECTIVE: Approximately 10% of patients with mild traumatic brain injury (mTBI) have intracranial bleeding (complicated mTBI) and 3.5% eventually require neurosurgical intervention, which is mostly available at centers with a higher level of trauma care designation and often requires interhospital transfer. In 2018, the Brain Injury Guidelines (BIG) were updated in the United States to guide emergency department care and patient disposition for complicated mild to moderate TBI. The aim of this study was to validate the sensitivity and specificity of the updated BIG (uBIG) for predicting the need for interhospital transfer in Canadian patients with complicated mTBI. METHODS: This study took place at three level I trauma centers. Consecutive medical records of patients with complicated mTBI (Glasgow Coma Scale score 13-15) who were aged ≥ 16 years and presented between September 2016 and December 2017 were retrospectively reviewed. Patients with a penetrating trauma and those who had a documented cerebral tumor or aneurysm were excluded. The primary outcome was a combination of neurosurgical intervention and/or mTBI-related death. Sensitivity and specificity analyses were performed. RESULTS: A total of 477 patients were included, of whom 8.4% received neurosurgical intervention and 3% died as a result of their mTBI. Forty patients (8%) were classified as uBIG-1, 168 (35%) as uBIG-2, and 269 (56%) as uBIG-3. No patients in uBIG-1 underwent neurosurgical intervention or died as a result of their injury. This translates into a sensitivity for predicting the need for a transfer of 100% (95% CI 93.2%-100%) and a specificity of 9.4% (95% CI 6.8%-12.6%). Using the uBIG could potentially reduce the number of transfers by 6% to 25%. CONCLUSIONS: The patients in uBIG-1 could be safely managed at their initial center without the need for transfer to a center with a higher level of neurotrauma care. Although the uBIG could decrease the number of transfers, further refinement of the criteria could improve its specificity.

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 machine prediction

Teacher imitation

Not 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)0.006
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.191
Threshold uncertainty score0.380

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.088
GPT teacher head0.356
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2022
Admission routes3
Has abstractyes

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