C.4 Neurologic injury in pediatric patients cannulated for rescue extracorporeal life support
Bibliographic record
Abstract
Background: Historical literature suggests the risk of neurologic injury in children supported by extracorporeal life support (ECLS) is between 10-20%, however recent studies suggest the incidence may be much higher. Methods: The Alberta Children’s Hospital (ACH) Rescue ECLS program cannulates patients who are then transferred to the partner program at Stollery Children’s Hospital. Data was systematically collected from all patients cannulated for Rescue ECLS at ACH October 2011 and May 2023. Neuroimaging (CT, MR) performed after cannulation was reviewed for evidence of ischemic and hemorrhagic strokes and hypoxic-ischemic brain injury. Results: Seventy-one patients were included in the Rescue ECLS cohort. Median age at cannulation was 1.74 years (range 0-17.6 years, 51% female). Survival to hospital discharge was 65%. Primary indication for ECLS included cardiac (42%), respiratory (33.3%), extracorporeal cardiopulmonary resuscitation (ECPR; 23.2%) and trauma (1.4%). Seventy four percent of the cohort underwent neuroimaging, of whom 67% had evidence of neurologic injury including stroke (ischemic 67%; hemorrhagic 50%) or hypoxic-ischemic injury (33%). Risk of neurologic injury did not differ by indication for ECLS. Conclusions: Neuroimaging abnormalities are present in most pediatric patients imaged post-cannulation for Rescue ECLS. Further research into modifiable risk factors for specific ECLS-related brain injuries may help to improve outcomes for survivors.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".