Impact of the modality of mechanical ventilation on bleeding during pituitary surgery
Bibliographic record
Abstract
BACKGROUND: Bleeding modifies the surgeon's view of the field during transsphenoidal endoscopic pituitary surgery. Since ventilation can alter venous return, we compared the effect of volume-controlled ventilation (VCV) and pressure-controlled ventilation (PCV) on intraoperative bleeding. METHODS: Eighty-six patients were randomized to VCV or PCV in this single blinded study; comparisons concerned 42 in the PCV group and 43 in the VCV group. RESULTS: Intraoperative bleeding, the primary endpoint, did not differ between groups whether analysis focused on 7 levels of the score, from minimal bleeding to bleeding with significant change in the conduct of surgical procedure (P = .89) or on a stratification into 3 categories, mild, moderate, and major (P = .47). Median [interquartile range] peak airway pressure was lower in the PCV group (13.5 [12.5-15] vs 16.3 [14.4-19.1] cm H2O, P < .001) while mean airway pressures were similar (P = .08). Means ± SD of tidal volumes were lower in the VCV group when expressed as absolute values (470.6 ± 84 vs 434.7 ± 71.7 ml, P = .05) or as tidal volume/theoretical ideal weight ratio (6.7 [6.5-7] vs 7.2 [6.9-7.9], P < .001). The 2 groups were similar for postoperative complications and number of patients cured. CONCLUSION: In conclusion, ventilation mode does not influence intraoperative bleeding during transsphenoidal pituitary surgery. TRIAL REGISTRATION: Clinicaltrials.gov identifier: NCT01891838; July 3, 2013.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 | 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".