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A SURVEY TO DETERMINE THE UNDERSTANDING OF THE CONCEPTUAL BASIS AND DIAGNOSTIC TESTS USED FOR BRAIN DEATH BY NEUROSURGEONS IN CANADA

2007· article· en· W2054347587 on OpenAlexaffabout
Ari R. Joffe, Natalie Anton, Vivek Mehta

Bibliographic record

VenueNeurosurgery · 2007
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsStollery Children's HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicineChoseCause of deathNeurosurgeryPsychiatryPathologyDisease

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the understanding of the conceptual basis and diagnostic tests used for brain death (BD) by neurosurgeons in Canada. METHODS: Between February and June 2006, a previously developed survey was mailed to every neurosurgeon in Canada. RESULTS: Of 223 surveys mailed, 147 (66%) were returned; of these, 128 (87%) were completed and analyzed. When asked to choose a conceptual reason to explain why BD is equivalent to death, 50 (39%) chose a higher brain concept, 50 (39%) chose a prognosis concept, and 33 (26%) chose a loss of integration of the organism concept. More than half of respondents answered that BD is not compatible with electroencephalographic activity or brainstem evoked potential activity. More than one-third of respondents answered that some cerebral blood flow or a brainstem with minimal microscopic damage was not compatible with BD. Of the 90 respondents who answered that they were comfortable diagnosing BD because the conceptual basis of BD makes it equivalent to death of the patient, in their own words, 14 (16%) used a loss of integration concept, 20 (22%) used a prognosis concept, 25 (28%) used a higher brain concept, and 39 (43%) did not articulate a concept. When asked, "Are brain death and cardiac death the same state (i.e., are both death of the patient)?," 57 (45%) answered "No." CONCLUSION: Within the neurosurgical community, a stand-alone concept of BD does not exist. There is also significant variability in the understanding of the tests that are compatible with the criterion of BD.

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)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.613
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.062
GPT teacher head0.274
Teacher spread0.212 · 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.

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

Citations25
Published2007
Admission routes2
Has abstractyes

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