Inflammation, coagulopathy, and the pathogenesis of multiple organ dysfunction syndrome
Bibliographic record
Abstract
OBJECTIVE: An improved understanding of the mechanisms through which infecting pathogens harm the host is leading to new formulations of the concept of sepsis. We review the roles of inflammation and coagulation in the pathogenesis of the multiple organ dysfunction syndrome, and explore the potential of new therapies to restore the fine biological balance between procoagulant and anticoagulant mechanisms that are disrupted during the life-threatening processes that lead to organ dysfunction. DATA SOURCES: Narrative review of published primary sources in the basic and clinical literature. DATA SUMMARY: Traditional models of host-pathogen interactions ascribe the morbidity of infection to the direct cytotoxic effects of micro-organisms on host tissues. However, abundant experimental and clinical evidence has revealed that it is the response of the host, rather than the trigger that elicited it, that is the more potent determinant of outcome. The elucidation of a complex network of host-derived inflammatory mediators raised the possibility that targeting these individually could improve patient outcomes, and some modest successes with this approach have been achieved. More recently, it is becoming evident that the inflammatory response, in turn, mediates its deleterious effects by inducing tissue hypoxia, and cellular injury, either through tissue necrosis or through the induction of programmed cell death or apoptosis. Thus, treatment strategies that target the downstream consequences of the activation of inflammation, for example, microvascular coagulation or acute adrenal insufficiency, represent the latest, and some of the most promising approaches to attenuation of the septic response to improve survival, and minimize organ dysfunction. The maladaptive sequelae of systemic inflammation, embodied in the concept of the multiple organ dysfunction syndrome, comprise the leading obstacle to survival for patients admitted to a contemporary intensive care unit. Further insights into this intimidatingly complex process will not only provide potent new therapeutic options, but promise to transform critical illness from a biological standoff, during which the clinician merely supports failing organs, to a disease that can be successfully treated.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".