Assessment of immunological status in the critically ill.
Bibliographic record
Abstract
The systemic inflammatory response (SIRS) results from various types of injuries such as severe infection, trauma, ischemia-reperfusion and major surgery including cardiac surgery with cardio-pulmonary bypass. This response involves immune cell activation and a complex network of proinflammatory cytokines, which may induce multiple organ failure when uncontrolled. The monocyte plays a central role in the response to infection with the release of TNF, IL-1, and IL-12. In addition, monocytes present antigens to T lymphocytes. An optimal antigen presentation requires the expression of MHC class II HLA-DR on monocytes surface and of co-stimulatory molecules such as CD54 on monocytes and LFA-1 on lymphocytes. It has become increasingly apparent that the pro-inflammatory response is balanced by concomitant anti-inflammatory mechanisms that results in monocyte deactivation, characterized by a decrease in HLA-DR expression and the release of anti-inflammatory cytokines such as IL-10. This counterregulatory response, if prolonged or predominant, may predispose the patient to a higher risk of infection. Further studies need to be conducted to precise: 1) the intensity of depression of the surface molecule expression assessing monocyte function, such as HLA DR and CD54; 2) the level of IL-10 and IL-12 release in patients with severe sepsis; 3) the immunomodulating effects of frequently used treatments in these patients with severe sepsis and in surgical patients; 4) the time course of recovery; 5) if the monitoring of HLA-DR, CD54, IL-10 and IL-12 will better predict the clinical outcome than clinical parameters.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".