Variable Ventilation Improves Perioperative Lung Function in Patients Undergoing Abdominal Aortic Aneurysmectomy
Bibliographic record
Abstract
BACKGROUND: Optimizing perioperative mechanical ventilation remains a significant clinical challenge. Experimental models indicate that "noisy" or variable ventilation (VV)--return of physiologic variability to respiratory rate and tidal volume--improves lung function compared with monotonous control mode ventilation (CV). VV was compared with CV in patients undergoing abdominal aortic aneurysmectomy, a patient group known to be at risk of deteriorating lung function perioperatively. METHODS: After baseline measurements under general anesthesia (CV with a tidal volume of 10 ml/kg and a respiratory rate of 10 breaths/min), patients were randomized to continue CV or switch to VV (computer control of the ventilator at the same minute ventilation but with 376 combinations of respiratory rate and tidal volume). Lung function was measured hourly for the next 6 h during surgery and recovery. RESULTS: Forty-one patients for aneurysmectomy were studied. The characteristics of the patients in the two groups were similar. Repeated-measures analysis of variance (group x time interaction) revealed greater arterial oxygen partial pressure (P = 0.011), lower arterial carbon dioxide partial pressure (P = 0.012), lower dead space ventilation (P = 0.011), increased compliance (P = 0.049), and lower mean peak inspiratory pressure (P = 0.013) with VV. CONCLUSIONS: The VV mode of ventilation significantly improved lung function over CV in patients undergoing abdominal aortic aneurysmectomy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".