Inflammation and Oxidative Stress in the Context of Extracorporeal Cardiac and Pulmonary Support
Bibliographic record
Abstract
Extracorporeal circulation (ECC) systems, including cardiopulmonary bypass, and extracorporeal membrane oxygenation have been an irreplaceable part of the cardiothoracic surgeries, and treatment of critically ill patients with respiratory and/or cardiac failure for more than half a century. During the recent decades, the concept of extracorporeal circulation has been extended to isolated machine perfusion of the donor organ including thoracic organs ( ex-situ organ perfusion, ESOP) as a method for dynamic, semi-physiologic preservation, and potential improvement of the donor organs. The extracorporeal life support systems (ECLS) have been lifesaving and facilitating complex cardiothoracic surgeries, and the ESOP technology has the potential to increase the number of the transplantable donor organs, and to improve the outcomes of transplantation. However, these artificial circulation systems in general have been associated with activation of the inflammatory and oxidative stress responses in patients and/or in the exposed tissues and organs. The activation of these responses can negatively affect patient outcomes in ECLS, and may as well jeopardize the reliability of the organ viability assessment, and the outcomes of thoracic organ preservation and transplantation in ESOP. Both ECLS and ESOP consist of artificial circuit materials and components, which play a key role in the induction of these responses. However, while ECLS can lead to systemic inflammatory and oxidative stress responses negatively affecting various organs/systems of the body, in ESOP, the absence of the organs that play an important role in oxidant scavenging/antioxidative replenishment of the body, such as liver, may make the perfused organ more susceptible to inflammation and oxidative stress during extracorporeal circulation. In the present manuscript, we will review the activation of the inflammatory and oxidative stress responses during ECLP and ESOP, mechanisms involved, clinical implications, and the interventions for attenuating these responses in ECC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".