The Roles of Venopulmonary Arterial Extracorporeal Membrane Oxygenation
Bibliographic record
Abstract
OBJECTIVES: Concise definitive review of the use of venopulmonary arterial extracorporeal membrane oxygenation (V-PA ECMO) support in patients with cardiopulmonary failure. DATA SOURCES: Original investigations identified through a PubMed search with search terms "percutaneous right ventricular assist device," "oxy-RVAD," "V-PA ECMO," and "veno-pulmonary arterial ECMO" were reviewed and evaluated for relevance. STUDY SELECTION: Studies that included more than three patients supported with V-PA ECMO were included. DATA EXTRACTION: Clinically relevant data from included studies, including patient-important outcomes, were summarized and discussed. DATA SYNTHESIS: We identified four groups of patients where V-PA ECMO has been studied: acute respiratory distress syndrome, right ventricular dysfunction after left ventricular assist device placement, bridge to lung transplantation, and pulmonary embolism. Most identified works are small, single center, and retrospective in nature, precluding definitive conclusions regarding the efficacy of V-PA ECMO. There have been no clinical trials evaluating the efficacy of V-PA ECMO for any indication. CONCLUSIONS: V-PA ECMO is a promising form of extracorporeal support for patients with right ventricular dysfunction. Future work should focus on identifying the optimal timing and populations for the use of V-PA ECMO.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".