Arterial pCO2 changes during thoracoscopic surgery with CO2 insufflation and one lung ventilation.
Bibliographic record
Abstract
INTRODUCTION: The respiratory effects (changes in pH and PaCO(2)) of carbon dioxide insufflation in thoracoscopic surgery in adult patients with pulmonary disease were not documented previously. METHODS: In this observational study 21 patients scheduled for elective thoracoscopic surgery with one lung ventilation using a double lumen tube and intraoperative carbon dioxide insufflation were studied. Arterial blood gas findings were correlated with demographic and intraoperative variables. RESULTS: When compared to baseline (10-15 minutes of one lung ventilation before carbon dioxide insufflation), carbon dioxide insufflation lowered the pH, 7.31±0.08 vs 7.40±0.05 (p<0.001) caused increased PaCO(2), 53±12 vs 42±6.0 (p<0.001) at 40-60 minutes after carbon dioxide insufflation. These derangements in arterial blood gases persisted in the post-anesthetic care unit with pH 7.33±0.04 vs 7.40±0.05 (p<0.001) and PaCO(2) 51±6.7 vs 42±6.0 (p<0.001). Moderate hypercarbia defined as PaCO(2) >50 mmHg, developed in 12 of 21 patients (57%) and was associated to lower FEV1/FVC ratios 60±21 vs 81±3%, older age 69±9 vs 56±17 years, and history of smoking, 43 ± 30 vs 16±21 pack years, p<0.05. CONCLUSIONS: Intrathoracic carbon dioxide insufflation causes significant derangements in pH and PaCO(2) which is worse in patients with lower FEV1/FVC, increased age and smoking history.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".