Pediatric Extracorporeal Life Support Transport in Western Canada: Experience over 14 years
Bibliographic record
Abstract
This retrospective cohort study describes all children transported on extracorporeal life support (ECLS) by the Stollery Children's Hospital Pediatric Transport team (SCH-PTT) between 2004 and 2018. We compared outcomes and complications between primary (SCH-PTT performed ECLS cannulation) vs. secondary (cannulation performed by referring facility) transports, as well as secondary transports from referring centers with and without an established ECLS cannulation program. SCH-PTT performed 68 ECLS transports during the study period. Median (IQR) transport distance was 298 (298-1,068) kilometers. Mean (SD) times from referral call to ECLS-initiation were: primary transports 7.8 (2.9) vs. 2.5(3.5) hours for secondary transports, p value < 0.001. Complications were common (n = 65, 95%) but solved without leading to adverse outcomes. There were no significant differences in the number of complications between primary and secondary transports. There was no significant difference in survival to ECLS decannulation between primary 9 (90%) and secondary transports 43 (74%), p value = 0.275. ECLS survival was higher for children cannulated by the SCH-PTT or a center with an ECLS cannulation program: 42 (82%) vs. 10 (59%), p value = 0.048. Critically ill children on ECLS can be safely transported by a specialized pediatric ECLS transport team. Secondary transports from a center with an ECLS cannulation program are also safe and have similar results as primary transports.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".