The Use of Air in the Inspired Gas Mixture During Two-Lung Ventilation Delays Lung Collapse During One-Lung Ventilation
Bibliographic record
Abstract
BACKGROUND: Collapse of the ipsilateral lung facilitates surgical exposure during thoracic procedures. The use of different gas mixtures during two-lung ventilation (2LV) may improve or impede surgical conditions during subsequent one-lung ventilation (OLV) by increasing or delaying lung collapse. We investigated the effects of three different gas mixtures during 2LV on lung collapse and oxygenation during subsequent OLV: Air/Oxygen (fraction of inspired oxygen [FIO(2)] = 0.4), Nitrous Oxide/Oxygen ("N(2)O," FIO(2) = 0.4) and Oxygen ("O(2)," FIO(2) = 1.0). METHODS: Subjects were randomized into three groups: Air/Oxygen (n = 33), N(2)O (n = 34) or O(2) (n = 33) and received the designated gas mixture during induction and until the start of OLV. Subjects' lungs in all groups were then ventilated with FIO(2) = 1.0 during OLV. The surgeons, who were blinded to the randomization, evaluated the lung deflation using a verbal rating scale at 10 and 20 min after the start of OLV. Serial arterial blood gases were performed before anesthesia induction, during 2LV, and every 5 min, for 30 min, after initiation of OLV. RESULTS: The use of air in the inspired gas mixture during 2LV led to delayed lung deflation during OLV, whereas N(2)O improved lung collapse. Arterial oxygenation was significantly improved in the O(2) group only for the first 10 min of OLV, after which there were no differences in mean Pao(2) values among groups. CONCLUSIONS: De-nitrogenation of the lung during 2LV is a useful strategy to improve surgical conditions during OLV. The use of FIO(2) 1.0 or N(2)O/O(2) (FIO(2) 0.4) during 2LV did not have an adverse effect on subsequent oxygenation during OLV.
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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) | 0.001 | 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 | 0.001 |
| 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".