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Record W1978341442 · doi:10.1016/j.carj.2012.04.005

The Use of Dynamic Computed Tomographic Angiography Ancillary to the Diagnosis of Brain Death

2012· article· en· W1978341442 on OpenAlexaff
Santanu Chakraborty, Stephanie Kenny, Reem Adas

Bibliographic record

VenueCanadian Association of Radiologists Journal · 2012
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineComputed tomographic angiographyCerebral blood flowCerebral circulationRadiologyComputed tomographicAngiographyBlood flowCerebral angiographyIntensive care medicineComputed tomographyCardiology

Abstract

fetched live from OpenAlex

OBJECTIVE: Global absence of cerebral circulation is an important ancillary test for brain death when the diagnosis cannot be confirmed clinically. A number of imaging methods are available to assess cerebral circulation; however, new techniques are sought to improve on limitations of the current tests. Dynamic computed tomographic angiography (dCTA) is a novel technique that enables dynamic noninvasive imaging of cerebral blood flow. MATERIALS AND METHODS: We present the use of dCTA in 3 cases as a corroboratory tool to diagnose brain death. Analysis of our findings suggest that it is a reliable technique for demonstrating the lack of intracranial blood flow, with many advantages over other current methods. CONCLUSION: A dCTA may be used to reliably demonstrate the lack of cerebral blood flow in patients with suspected brain death.

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)0.001
metaresearch head score (Gemma)0.008
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.028
GPT teacher head0.262
Teacher spread0.234 · 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

Citations6
Published2012
Admission routes1
Has abstractyes

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