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Record W2766010924 · doi:10.1097/tme.0000000000000169

Reducing Unnecessary Head Computed Tomography in Mild Traumatic Brain Injury

2017· review· en· W2766010924 on OpenAlexaboutno aff
Nathaniel John Webster, N. Anthony Moore, Felicia Stewart

Bibliographic record

VenueAdvanced Emergency Nursing Journal · 2017
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHead injuryComputed tomographyComputed tomographicHead traumaRadiologyHead (geology)Traumatic brain injurySurgery

Abstract

fetched live from OpenAlex

There is growing concern about the frequency of computed tomographic (CT) scans performed for evaluation of adults with suspected mild traumatic brain injury. The Canadian CT Head Rule and the New Orleans Criteria are the most studied head CT decision tools that aid providers in determining which patients do not require a CT scan. This article examines recent research to determine which of these tools has proven to be the most effective at safely reducing the use of head CT scans. The reviewed studies concluded that both the Canadian CT Head Rule and the New Orleans Criteria had similar sensitivities, but the Canadian CT Head Rule showed superior specificity in predicting the presence of a clinically significant brain injury. The authors of this article recommend that the Canadian CT Head Rule be used in the evaluation of minor head injury to reduce unnecessary CT scans.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.131
GPT teacher head0.432
Teacher spread0.301 · 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 designOther design
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

Citations13
Published2017
Admission routes1
Has abstractyes

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