Joint Society of Critical Care Medicine-Extracorporeal Life Support Organization Task Force Position Paper on the Role of the Intensivist in the Initiation and Management of Extracorporeal Membrane Oxygenation
Bibliographic record
Abstract
OBJECTIVES: To define the role of the intensivist in the initiation and management of patients on extracorporeal membrane oxygenation. DESIGN: Retrospective review of the literature and expert consensus. SETTING: Series of in-person meetings, conference calls, and emails from January 2018 to March 2019. SUBJECTS: A multidisciplinary, expert Task Force was appointed and assembled by the Society of Critical Care Medicine and the Extracorporeal Life Support Organization. Experts were identified by their respective societies based on reputation, experience, and contribution to the field. INTERVENTIONS: A MEDLINE search was performed and all members of the Task Force reviewed relevant references, summarizing high-quality evidence when available. Consensus was obtained using a modified Delphi process, with agreement determined by voting using the RAND/UCLA scale, with score ranging from 1 to 9. MEASUREMENTS AND MAIN RESULTS: The Task Force developed 18 strong and five weak recommendations in five topic areas of extracorporeal membrane oxygenation initiation and management. These recommendations were organized into five areas related to the care of patients on extracorporeal membrane oxygenation: patient selection, management, mitigation of complications, coordination of multidisciplinary care, and communication with surrogate decision-makers. A common theme of the recommendations is extracorporeal membrane oxygenation is best performed by a multidisciplinary team, which intensivists are positioned to engage and lead. CONCLUSIONS: The role of the intensivist in the care of patients on extracorporeal membrane oxygenation continues to evolve and grow, especially when knowledge and familiarity of the issues surrounding extracorporeal membrane oxygenation selection, cannulation, and management are applied.
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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 | 0.091 | 0.127 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".