Cardiopulmonary bypass induced inflammation: pathophysiology and treatment. An update
Bibliographic record
Abstract
Cardiac surgery with cardiopulmonary bypass (CPB) induces an acute phase reaction that has been implicated in the pathogenesis of several postoperative complications. Recent data indicate that a complex sequence of events leads to the final activation of leukocytes and endothelial cells (EC), which is responsible for cell dysfunction in different organs. Activation of the contact system, endotoxemia, ischemia and reperfusion injury and surgical trauma are all potential triggers of inflammation following CPB. Different pro- and anti-inflammatory mediators (cytokines, adhesion molecules) are involved and their release is mediated by intracellular transcription factors (nuclear factor-kappa B, NF-kappa B). In this review, we examine recent advances in the understanding of the pathophysiology of the CPB-induced acute phase reaction and evaluate the different pharmacological, technical and surgical strategies used to reduce its effects. Emphasis is given to the central role of transcription factor NF-kappa B in the complex mechanism of the inflammatory reaction and to the effects of compounds such as heparin and glycosaminoglycans, phosphodiesterase inhibitors and protease inhibitors whose role as anti-inflammatory agent has only recently been recognized.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".