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Record W4237241955 · doi:10.1139/y99-122

Plasma and cerebrospinal fluid concentrations of neuropeptide Y, serotonin, and catecholamines in patients under propofol or isoflurane anesthesia

2000· article· en· W4237241955 on OpenAlexvenueno aff
Eric Grouzmann, Alain Borgeat, Marc Fathi, Rolf C. Gaillard, P Ravussin

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2000
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Sedative Agents
Canadian institutionsnot available
Fundersnot available
KeywordsIsofluraneCerebrospinal fluidPropofolNeuropeptide Y receptorAnestheticAnesthesiaMedicineSerotoninEndocrinologyNeuropeptideInternal medicine

Abstract

fetched live from OpenAlex

Propofol is a widely used anesthetic for both induction and maintenance of anesthesia during surgery. A strong feeling of hunger has been reported during the early recovery period after propofol anesthesia. We have investigated the effect of propofol on appetite in 10 patients undergoing a craniotomy and in parallel measured neuropeptide Y (NPY), catecholamines, and serotonin levels in the cerebrospinal fluid and plasma during anesthesia. Ten patients anesthetized with a volatile agent (isoflurane) served as a control group. Plasma NPY and catecholamines levels were not affected by surgery at any time. We observed a strong increase in NPY concentrations in the cerebrospinal fluid independently of the anesthetic technique agent used, whereas catecholamines were unchanged. We found that serotonin concentrations decreased significantly in the plasma (but not in the cerebrospinal fluid) of patients treated by propofol when compared with the control group; this decrease was associated with an increase of hunger early postoperatively. We concluded that the proappetite effect of propofol is mediated through a decrease of serotonin at the peripheral level.Key words: catecholamines, serotonin, neuropeptide Y (NPY), cerebrospinal fluid, serum, appetite.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.015
GPT teacher head0.264
Teacher spread0.249 · 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 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

Citations16
Published2000
Admission routes1
Has abstractyes

Explore more

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