Extent and Localization of Changes in Upper Airway Caliber with Varying Concentrations of Sevoflurane in Children
Bibliographic record
Abstract
BACKGROUND: Previous studies in humans suggest that inhibition of upper airway muscle activity is independent of the dose of inhalational anesthesia. Whether a dose-independent relation applies to changes in airway caliber is unknown. The authors sought to evaluate the configurational changes that lead to upper airway narrowing during inhalational anesthesia with sevoflurane and to determine whether these changes are dose dependent within a clinically relevant dose range. METHODS: Fifteen children undergoing elective magnetic resonance imaging of the brain were studied. Magnetic resonance images of the upper airway were acquired at sevoflurane concentrations of 0.5, 1.0, and 1.5 minimum alveolar concentration (MAC), administered in random sequence. At least 15 min was allowed for equilibration of inspired and alveolar partial pressures of sevoflurane. Images were acquired in early expiration at the level of the soft palate, base of the tongue, and tip of the epiglottis. Airway cross-sectional area (CSA), anteroposterior, and transverse dimension were determined using image-analysis software. RESULTS: At each anatomical level, pharyngeal CSA decreased progressively with increasing depth of sevoflurane anesthesia (P < 0.001). Increasing the sevoflurane concentration from 0.5 to 1.0 MAC reduced airway CSA by 13-18%, and a further increase to 1.5 MAC resulted in an overall 28-34% reduction in CSA. The reduction in CSA was predominantly due to a decrease in anteroposterior dimension. CONCLUSIONS: Increasing the depth of sevoflurane anesthesia resulted in a relatively uniform reduction in pharyngeal caliber at each anatomical level studied. The effect of sevoflurane on upper airway caliber is dose dependent.
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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 | 0.001 |
| 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 | 0.001 |
| 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".