Pharmacological Research Agenda on Adult Extracorporeal Membrane Oxygenation Using the Delphi Method: A Position Paper of the Extracorporeal Membrane Oxygenation Pharmacology Network
Bibliographic record
Abstract
OBJECTIVES: Extracorporeal membrane oxygenation (ECMO) is a critical intervention for patients with severe cardiac or respiratory failure. However, pharmacological management for ECMO-supported patients presents unique challenges due to alterations in drug pharmacokinetics and pharmacodynamics induced by the ECMO circuit and underlying critical illness. This position paper identifies key research priorities in ECMO pharmacology using a structured Delphi consensus process and provides a focused review of current evidence and knowledge gaps to inform future research and clinical practice. DATA SOURCES: An international panel of 25 ECMO pharmacology experts from 13 countries representing the ECMO Pharmacology Network contributed to this position paper. Literature was reviewed to summarize current evidence and identify knowledge gaps in ECMO pharmacology. STUDY SELECTION: The Delphi process involved iterative, anonymous voting by the expert panel to propose key research priorities. Items selected were based on their perceived importance to improving clinical outcomes and advancing pharmacological management in ECMO-supported patients. DATA EXTRACTION: Key research priorities were identified, and a detailed literature review was conducted for each, focusing on pharmacokinetics/pharmacodynamics, related therapeutic challenges, and knowledge gaps. Future research directions were outlined. DATA SYNTHESIS: Six critical ECMO pharmacotherapy research priorities were identified: 1) pharmacokinetics/pharmacodynamics reporting, 2) interactions between ECMO and renal replacement therapy, 3) antimicrobial dosing, 4) analgesia and sedation for pain and agitation, 5) sedation and neuromuscular blocking agents for increased work of breathing, and 6) anticoagulation. The review for the key research priorities highlighted substantial gaps in the existing literature, emphasizing the need for comprehensive studies addressing these issues to enhance pharmacotherapy in ECMO patients, improve clinical outcomes, and contribute to the development of evidence-based guidelines for this complex population. CONCLUSIONS: ECMO presents unique challenges to drug pharmacokinetics and pharmacodynamics, complicating pharmacotherapy in critically ill patients. Further research addressing identified gaps is essential to develop evidence-based treatment strategies and enhance patient outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".