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Record W2013207646 · doi:10.15273/dmj.vol30no1.4308

Awareness Under General Anesthesia

2003· article· en· W2013207646 on OpenAlexaffvenue
Luke Y. C. Chen, Romesh Shukla

Bibliographic record

VenueDalhousie Medical Journal · 2003
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsIzaak Walton Killam Health CentreDalhousie University
Fundersnot available
KeywordsBispectral indexHypnosisIntraoperative AwarenessLimitingMedicineIncidence (geometry)MEDLINESubject (documents)AnesthesiaIntensive care medicineComputer scienceAlternative medicinePropofol

Abstract

fetched live from OpenAlex

Summary : The incidence and causes of awareness under general anesthesia are reviewed, as well as principles of prevention and management. Although intra-operative awareness is rare, occurring in 0.2-0.4% of all operations done under general anesthesia, it causes severe peri-operative and post-operative complications. Moreover, the incidence of awareness is higher in certain patients (e.g. those who are drug-tolerant), and certain procedures (e.g. cardiac surgery). Preventing awareness has been difficult because depth of hypnosis is difficult to measure. However, the bispectral index (BIS) system offers a new way to objectively measure depth of hypnosis. In most cases, BIS is not necessary, but in patients and procedures where the risk of awareness is high, BIS is a useful clinical tool. Methods : A Medline search was performed, crossing the medical subject headings "Awareness" and "General Anesthesia", and limiting the results to reviews or meta-analyses in English. This search yielded five relevant papers. The reference sections of these papers were searched to obtain other relevant papers.

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)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.019
GPT teacher head0.296
Teacher spread0.276 · 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 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

Citations16
Published2003
Admission routes2
Has abstractyes

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Same venueDalhousie Medical JournalSame topicCardiac, Anesthesia and Surgical OutcomesFrench-language works237,207