Protective Ventilation Influences Systemic Inflammation after Esophagectomy
Bibliographic record
Abstract
BACKGROUND: Esophagectomy induces a systemic inflammatory response whose extent has been recognized as a predictive factor of postoperative respiratory morbidity. The aim of this study was to determine the effectiveness of a protective ventilatory strategy to reduce systemic inflammation in patients undergoing esophagectomy. METHODS: The authors prospectively investigated 52 patients undergoing planned esophagectomy for cancer. Patients were randomly assigned to a conventional ventilation strategy (n = 26; tidal volume of 9 ml/kg during two-lung and one-lung ventilation; no positive end-expiratory pressure) or a protective ventilation strategy (n = 26; tidal volume of 9 ml/kg during two-lung ventilation, reduced to 5 ml/kg during one-lung ventilation; positive end-expiratory pressure 5 cm H2O throughout the operative time). RESULTS: Plasmatic levels of interleukin (IL)-1beta, IL-6, IL-8, and tumor necrosis factor alpha were measured perioperatively and postoperatively. Pulmonary function and postoperative evolution were also evaluated. Patients who received protective strategy had lower blood levels of IL-1beta, IL-6, and IL-8 at the end of one-lung ventilation (0.24 [0.15-0.40] vs. 0.56 [0.38-0.89] pg/ml, P < 0.001; 91 [61-117] vs. 189 [127-294] pg/ml, P < 0.001; and 30 [22-45] vs. 49 [29-69] pg/ml, P < 0.05, respectively) and 18 h postoperatively (0.18 [0.13-0.30] vs. 0.43 [0.34-0.54] pg/ml, P < 0.001; 54 [36-89] vs. 116 [78-208] pg/ml, P < 0.001; 16 [11-24] vs. 35 [28-53] pg/ml, P < 0.001, respectively). Protective strategy resulted in higher oxygen partial pressure to inspired oxygen fraction ratio during one-lung ventilation and 1 h postoperatively and in a reduction of postoperative mechanical ventilation duration (115 +/- 38 vs. 171 +/- 57 min, P < 0.001). CONCLUSION: A protective ventilatory strategy decreases the proinflammatory systemic response after esophagectomy, improves lung function, and results in earlier extubation.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".