Characteristics of Pediatric Extracorporeal Membrane Oxygenation Programs in the United States and Canada
Bibliographic record
Abstract
The aim of this study was to evaluate the current infrastructure and practice characteristics of pediatric extracorporeal membrane oxygenation (ECMO) programs. A 40-question survey of center-specific demographics, practice structure, program experience, and support network utilized to cannulate and maintain a pediatric patient on ECMO was designed via a web-based survey tool. The survey was distributed to pediatric ECMO programs in the United States and Canada. Of the 101 centers that were identified to participate, 41 completed the survey. The majority of responding centers are university affiliated (73%) and have an intensive care unit (ICU) with 15-25 beds (58%). Extracorporeal membrane oxygenation has been offered for >10 years in 85% of the centers. The median number of total cannulations per center in 2017 was 15 (interquartile range [IQR] = 5-30), with the majority occurring in the cardiovascular intensive care unit (median = 13, IQR = 5-25). Fifty-seven percent of responding centers offer ECPR, with a median number of four cases per year (IQR = 2-7). Most centers cannulate in an operating room or ICU; 11 centers can cannulate in the pediatric ED. Sixty-three percent of centers have standardized protocols for postcannulation management. The majority of protocols guide anticoagulation, sedation, or ventilator management; left ventricle decompression and reperfusion catheter placement are the least standardized procedures. The majority of pediatric ECMO centers have adopted the infrastructure recommendations from the Extracorporeal Life Support Organization. However, there remains broad variability of practice characteristics and organizational infrastructure for pediatric ECMO centers across the United States and Canada.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".