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Nitrous oxide in neuroanaesthesia

2004· letter· en· W2049481061 on OpenAlexaboutno aff
J. Barker

Bibliographic record

VenueAnaesthesia · 2004
Typeletter
Languageen
FieldNeuroscience
TopicAnesthesia and Neurotoxicity Research
Canadian institutionsnot available
Fundersnot available
KeywordsNitrous oxideAnesthesiaMedicineHalothaneCerebral blood flowKetamineSevoflurane

Abstract

fetched live from OpenAlex

In a recent ‘State of the Art’ article on advances in anaesthesia (Hirsch. Anaesthesia 2003; 58: 1162–5), it is claimed that the use of nitrous oxide in neuro-anaesthetic practice is waning. In an even more recent article (Rowney et al. Anaesthesia 2004; 59: 10–4), three anaesthetists now based in Hospitals for Sick Children in Edinburgh, Glasgow and Toronto studied the effects of nitrous oxide on cerebral blood flow velocity (CBFV) in children anaesthetised with sevoflurane. The results showed that CBFV decreased when nitrous oxide was replaced by air and resumed its initial value when nitrous oxide was reintroduced. They suggested that these potentially deleterious effects of nitrous oxide could have significant bearing on the continued use of nitrous oxide with sevoflurane in paediatric anaesthesia especially in patients with intracranial space-occupying lesions. Forty years ago, McDowall, Harper and Jacobson [1] showed that halothane vapourised in air decreased cerebral blood flow (CBF) in canine brain, but subsequently it was demonstrated by McDowall and Harper [2] that halothane vapourised in nitrous oxide increased CBF above control; when air was administered in place of nitrous oxide CBF decreased below the control level. In an Editorial [3], I referred to the excitatory actions of ketamine and nitrous oxide on brain tissue and Winters [4] classified this as cataleptoid central nervous system stimulation. In the 1970s I abandoned the use of nitrous oxide to vapourise volatile agents in neuroanaesthesia in favour of oxygen enriched air and continued with this regime until I retired in the 1990s.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.285
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0000.002

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 head0.044
GPT teacher head0.276
Teacher spread0.232 · 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
GenreCommentary

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

Citations1
Published2004
Admission routes1
Has abstractyes

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