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Record W2021735693 · doi:10.1097/ta.0b013e31811ec178

Traumatic Brain Injury in Intoxicated Patients

2007· article· en· W2021735693 on OpenAlexaffabout
Jeff D. Golan, Judith Marcoux, Eyal Golan, Robert H. Schapiro, Karen M. Johnston, M. Maleki, Suneel Khetarpal, Line Jacques

Bibliographic record

VenueThe Journal of Trauma: Injury, Infection, and Critical Care · 2007
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsMcGill UniversityMontreal General Hospital
Fundersnot available
KeywordsGlasgow Coma ScaleMedicineTraumatic brain injuryIntracranial pressureIntracranial pressure monitoringAnesthesiaAlcohol intoxicationComa (optics)ConfoundingInjury Severity ScoreInternal medicinePoison controlEmergency medicineInjury preventionPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: We sought to evaluate the effect alcohol intoxication may have had in nonsurgically treated patients with severe traumatic brain injury. METHODS: The Montreal General Hospital Traumatic Brain Injury Registry was used to identify all adult patients with a Glasgow Coma Scale score < or =8 at admission, within a 15-month period. All charts were retrospectively reviewed. RESULTS: Twenty-three patients had toxic blood alcohol levels (BAL > or =21.7 mmol/L), 24 were alcohol negative (BAL <3 mmol/L), and 10 were alcohol-influenced or had unknown BAL. Patients were more likely to have intracranial pressure monitoring if they had multiple intracranial hemorrhages, sustained multiple injuries, or had a post-resuscitative Glasgow Coma Scale score < or =8. Intoxicated patients had a mean delay of 151 minutes more in the insertion time of an intracranial pressure monitoring device, compared with alcohol-negative patients. CONCLUSIONS: Alcohol was a confounding factor in the treatment of some of our patients.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.324
Teacher spread0.302 · 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

Citations21
Published2007
Admission routes2
Has abstractyes

Explore more

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