Accelerated Recovery from Sevoflurane Anesthesia with Isocapnic Hyperpnoea
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".