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Record W2061361821 · doi:10.1213/ane.0b013e3181602dd4

Accelerated Recovery from Sevoflurane Anesthesia with Isocapnic Hyperpnoea

2008· article· en· W2061361821 on OpenAlexaff
Rita Katznelson, Leonid Minkovich, Zeev Friedman, Ludvik Fedorko, W. Scott Beattie, Joseph A. Fisher

Bibliographic record

VenueAnesthesia & Analgesia · 2008
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Sedative Agents
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsMedicineSevofluraneAnesthesia

Abstract

fetched live from OpenAlex

BACKGROUND: Isocapnic hyperpnoea (IH) reduces recovery time from isoflurane anesthesia in animals and humans. We studied the effect of IH on the emergence profile of sevoflurane-anesthetized patients by comparing postoperative recovery variables in patients administered IH (IH group) to those recovered in the customary fashion (control group). METHODS: We enrolled 30 ASA I-III patients undergoing elective gynecological surgery. Induction and maintenance of anesthesia were standardized with a protocol consisting of fentanyl, propofol, rocuronium, and sevoflurane in air/O2. Patients were randomly assigned to control (C) or IH groups at the end of the surgery. We recorded time intervals from discontinuing sevoflurane to recovery milestones. RESULTS: Time to tracheal extubation was much shorter in the IH group compared with group C (6.2 +/- 2.1 vs 12.3 +/- 3.8 min, respectively, P < 0.01). The IH group also had shorter times to initiation of spontaneous ventilation (4.2 +/- 1.7 vs 6.5 +/- 3.8 min, P = 0.047), eye opening (5.5 +/- 1.4 vs 13.3 +/- 4.4 min, P < 0.01), bispectral index value >75 (3.9 +/- 1.1 vs 8.8 +/- 3.7 min, P < 0.01), leaving operating room (7.7 +/- 2.0 vs 15.3 +/- 3.4 min, P < 0.01), and eligibility for postanesthetic care unit discharge (67.2 +/- 19.3 vs 90.6 +/- 20.0 min, P < 0.01). CONCLUSION: IH accelerates recovery from sevoflurane anesthesia and shortens operating room and postanesthetic care unit stay.

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), Insufficient 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 score0.060
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
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)0.0010.001

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 head0.033
GPT teacher head0.247
Teacher spread0.214 · 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

Citations30
Published2008
Admission routes1
Has abstractyes

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