Executive Summary: The Pediatric Extracorporeal Membrane Oxygenation Anticoagulation CollaborativE (PEACE) Consensus Conference*
Bibliographic record
Abstract
OBJECTIVES: To present recommendations and consensus statements with supporting literature for the clinical management of neonates and children supported with extracorporeal membrane oxygenation (ECMO) from the Pediatric ECMO Anticoagulation CollaborativE (PEACE) consensus conference. DATA SOURCES: Systematic review was performed using PubMed, Embase, and Cochrane Library (CENTRAL) databases from January 1988 to May 2021, followed by serial meetings of international, interprofessional experts in the management ECMO for critically ill children. STUDY SELECTION: The management of ECMO anticoagulation for critically ill children. DATA EXTRACTION: Within each of eight subgroup, two authors reviewed all citations independently, with a third independent reviewer resolving any conflicts. DATA SYNTHESIS: A systematic review was conducted using MEDLINE, Embase, and Cochrane Library databases, from January 1988 to May 2021. Each panel developed evidence-based and, when evidence was insufficient, expert-based statements for the clinical management of anticoagulation for children supported with ECMO. These statements were reviewed and ratified by 48 PEACE experts. Consensus was obtained using the Research and Development/UCLA Appropriateness Method. Results were summarized using the Grading of Recommendations Assessment, Development, and Evaluation method. We developed 23 recommendations, 52 expert consensus statements, and 16 good practice statements covering the management of ECMO anticoagulation in three broad categories: general care and monitoring; perioperative care; and nonprocedural bleeding or thrombosis. Gaps in knowledge and research priorities were identified, along with three research focused good practice statements. CONCLUSIONS: The 91 statements focused on clinical care will form the basis for standardization and future clinical trials.
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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 | 0.092 | 0.274 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.019 | 0.015 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.008 | 0.005 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.031 | 0.013 |
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".