Coagulation Dysfunction Criteria in Critically Ill Children: The PODIUM Consensus Conference
Bibliographic record
Abstract
CONTEXT: Previous criteria for coagulation dysfunction in critically ill children were based mainly on expert opinion. OBJECTIVE: To evaluate current evidence regarding coagulation tests associated with adverse outcomes in children to inform criteria for coagulation dysfunction during critical illness. DATA SOURCES: Electronic searches of PubMed and Embase were conducted from January 1992 to January 2020 by using a combination of medical subject heading terms and text words to define concepts of coagulation dysfunction, pediatric critical illness, and outcomes of interest. STUDY SELECTION: Studies were included if critically ill children with coagulation dysfunction were evaluated, if performance characteristics of assessment and/or scoring tools to screen for coagulation dysfunction were evaluated, and if outcomes related to mortality or functional status, organ-specific outcomes, or other patient-centered outcomes were assessed. DATA EXTRACTION: Data were abstracted from each eligible study into a standard data extraction form, along with risk of bias assessment, by a task force member. RESULTS: The systematic review supports the presence of at least 2 of the following criteria reflecting coagulation dysfunction in the absence of liver dysfunction: platelet count <100 000 cells per μL, international normalized ratio >1.5, fibrinogen level <150 mg/dL, and D-dimer value above 10 times the upper limit of normal, or above the assay's upper limit of detection if this limit is below 10 times the upper limit of normal. LIMITATIONS: The proposed criteria for coagulation dysfunction are limited by the available evidence and will require future validation. CONCLUSIONS: Validation of the proposed criteria and identified scientific priorities will enhance our understanding of coagulation dysfunction in critically ill children.
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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 | 0.063 | 0.102 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.008 | 0.007 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".