Specific Etiologies Associated With the Multiple Organ Dysfunction Syndrome in Children: Part 1
Bibliographic record
Abstract
OBJECTIVE: To describe a number of the conditions associated with multiple organ dysfunction syndrome presented as part of the Eunice Kennedy Shriver National Institute of Child Health and Human Development multiple organ dysfunction syndrome workshop (March 26-27, 2015). DATA SOURCES: Literature review, research data, and expert opinion. STUDY SELECTION: Not applicable. DATA EXTRACTION: Moderated by an expert from the field, issues relevant to the association of multiple organ dysfunction syndrome with a variety of conditions were presented, discussed, and debated with a focus on identifying knowledge gaps and research priorities. DATA SYNTHESIS: Summary of presentations and discussion supported and supplemented by the relevant literature. CONCLUSIONS: There is a wide range of medical conditions associated with multiple organ dysfunction syndrome in children. Traditionally, sepsis and trauma are the two conditions most commonly associated with multiple organ dysfunction syndrome both in children and adults. However, there are a number of other pathophysiologic processes that may result in multiple organ dysfunction syndrome. In this article, we discuss conditions such as cancer, congenital heart disease, and acute respiratory distress syndrome. In addition, the relationship between multiple organ dysfunction syndrome and clinical therapies such as hematopoietic stem cell transplantation and cardiopulmonary bypass is also considered. The purpose of this article is to describe the association of multiple organ dysfunction syndrome with a variety of conditions in an attempt to identify similarities, differences, and opportunities for therapeutic intervention.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".