Extracorporeal membrane oxygenation during pregnancy and peripartal. An international retrospective multicenter study
Bibliographic record
Abstract
Introduction Extracorporeal Membrane Oxygenation (ECMO) may be used in the setting of pregnancy or the peripartal period, however its utility has not been well-characterized. This study aims to give an overview on the prevalence of peripartel ECMO cases and further assess the indications and outcomes of ECMO in this setting across multiple centers and countries. Methods A retrospective, multicenter, international cohort study of pregnant and peripartum ECMO cases was performed. Data were collected from six ECMO centers across three continents over a 10-year period. Results A total of 60 pregnany/peripartal ECMO cases have been identified. Most frequent indications are acute respiratory distress syndrome ( n = 30) and pulmonary embolism ( n = 5). Veno-venous ECMO mode was applied more often (77%). ECMO treatment during pregnancy was performed in 17 cases. Maternal and fetal survival was high with 87% ( n = 52), respectively 73% ( n = 44). Conclusions Various emergency scenarios during pregnancy and at time of delivery may require ECMO treatment. Peripartal mortality in a well-resourced setting is rare, however emergencies in the labor room occur and knowledge of available rescue therapy is essential to improve outcome. Obstetricians and obstetric anesthesiologists should be aware of the availability of ECMO resource at their hospital or region to ensure immediate contact when needed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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 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".