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Record W2059426961 · doi:10.1097/mej.0b013e32834f9d51

Urgent computed tomography brain scan for elderly patients

2011· article· en· W2059426961 on OpenAlexaff
Julien Segard, Emmanuel Montassier, David Trewick, Philippe Le Conte, Benoit Guillon, Gilles Berrut

Bibliographic record

VenueEuropean Journal of Emergency Medicine · 2011
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsHotel Dieu Hospital
Fundersnot available
KeywordsMedicineGlasgow Coma ScaleVomitingComputed tomographyEmergency departmentLogistic regressionLevel of consciousnessComa (optics)Retrospective cohort studyDeliriumPopulationRadiologyPediatricsSurgeryInternal medicineAnesthesiaIntensive care medicinePsychiatry

Abstract

fetched live from OpenAlex

We conducted a retrospective study of 291 patients aged 75 years or older who were admitted to the emergency department and who underwent a computed tomography (CT) brain scan. Our aims were to assess the reasons for requesting an urgent CT brain scan, to record the diagnostic yield of cerebral imaging, and to seek out predictive factors of an intracranial pathology. The three main reasons for requesting an urgent CT brain scan were the presence of localizing signs (60%), delirium (21%), and disorders of consciousness with a Glasgow Coma Score of less than 14 (14.5%). In our elderly population, we found no typical patient profile when concerned with the risk of having an intracranial pathology. The multivariate logistic regression found that predictive factors for intracranial bleeding were localizing signs, disorders of consciousness with a Glasgow Coma Score of less than 14, head trauma, sudden-onset headache, or headache associated with at least two episodes of vomiting.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.715
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.076
GPT teacher head0.294
Teacher spread0.218 · 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.

Study designNot applicable
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
Published2011
Admission routes1
Has abstractyes

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