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Cerebrovascular carbon dioxide reactivity in children anaesthetized with propofol

2003· article· en· W2056898453 on OpenAlexaff
Cengiz Karsli, Igor Luginbuehl, Marc Farrar, Bruno Bissonnette

Bibliographic record

VenuePediatric Anesthesia · 2003
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Sedative Agents
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPropofolMedicineAnesthesiaMiddle cerebral arteryHeart rateCerebral blood flowBlood flowHemodynamicsTranscranial DopplerBlood pressurePharmacokineticsCardiologyIschemiaInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Propofol, by virtue of its favourable pharmacokinetic profile, is suitable for maintenance of anaesthesia by continuous infusion during neurosurgical procedures in adults. It is gaining popularity for use in paediatric patients. To determine the effects of propofol on carbon dioxide cerebrovascular reactivity in children, middle cerebral artery blood flow velocity was measured at different levels of endtidal (PECO2) by transcranial Doppler sonography. METHODS: Ten ASA I or II children, aged 1-6 years undergoing elective urological surgery were enrolled. Anaesthesia comprized propofol aimed at producing an estimated steady-state serum concentration of 3 microg x ml-1 and a caudal epidural block. PECO2 was adjusted randomly in an increasing or decreasing fashion between 3.3, 5.2 and 7.2 kPa (25, 40 and 55 mmHg) with an exogenous source of CO2 while maintaining ventilation parameters constant. RESULTS: Cerebral blood flow velocity increased as PECO2 increased from 3.3 to 5.2 kPa (25-40 mmHg) (P < 0.001) and from 5.2 to 7.2 kPa (40-55 mmHg) (P < 0.001). Mean heart rate and blood pressure did not change significantly. CONCLUSIONS: This study demonstrates that cerebrovascular CO2 reactivity is maintained over PECO2 values of 3.3, 5.2 and 7.2 kPa (25, 40 and 55 mmHg) in healthy children anaesthetized with propofol.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.215
Teacher spread0.208 · 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

Citations39
Published2003
Admission routes1
Has abstractyes

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