Setting up a Rescue Extracorporeal Life Support Program
Bibliographic record
Abstract
Extracorporeal life support (ECLS) is a high-risk, lifesaving medical treatment that is typically limited to centers that can support a comprehensive ECLS program. Rescue programs can bridge the gap in care between ECLS centers and other tertiary pediatric centers without cardiac surgical and comprehensive ECLS support. We describe how our pediatric center without cardiac surgery successfully partnered with an established ECLS center to develop a Rescue ECLS Cannulation Program. This formalized program provides cannulation and stabilization by a specialized team at the presenting hospital before being transported to a partner hospital. This article outlines how we established our unique Rescue ECLS Cannulation program. We outline the planning, development, and implementation of the program and describe the unique aspects contributing to successful implementation including longitudinal training, staged program evolution, and a bundled approach to care. We also describe the patients who we have cannulated since its inception. Rescue ECLS Cannulation Programs provide access to consistent, high-quality, and lifesaving care to critically ill patients at sites without the resources to support a full ECLS program.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".