Survival and Neurocognitive Outcomes After Cardiac Extracorporeal Life Support in Children Less Than 5 Years of Age
Bibliographic record
Abstract
BACKGROUND: Survival after pediatric cardiac extracorporeal life support (ECLS) is guarded, and neurological morbidity varies widely. Our objective is to report our 10-year experience with cardiac ECLS, including survival and kindergarten entry neurocognitive outcomes; to identify predictors of mortality or adverse neurocognitive outcomes; and to compare 2 eras, before and after 2005. METHODS AND RESULTS: From 2000 to 2009, 98 children had venoarterial cardiac ECLS. Sixty-four patients (65%) survived to hospital discharge, and 50 (51%) survived ≤5 years of age. Neurocognitive follow-up of survivors was completed at mean (SD) age of 52.9 (8) months using Wechsler Preschool and Primary Scale of Intelligence. Logistic regression analysis found the longer time (hours) for lactate to fall below 2 mmol/L on ECLS (hazard ratio, 1.39; 95% confidence interval, 1.05, 1.84; P=0.022), and the amount of platelets (mL/kg) given in the first 48 hours (hazard ratio, 1.18; 95% confidence interval, 1.06, 1.32; P=0.002) was independently associated with higher in-hospital mortality. Receiving ECLS after the year 2005 was independently associated with lower risk of in-hospital mortality (hazard ratio, 0.36; 95% confidence interval, 0.13, 0.99; P=0.048). Extracorporeal cardiopulmonary resuscitation was not independently associated with mortality or neurocognitive outcomes. Era was not independently associated with neurocognitive outcomes. The full-scale intelligence quotient of survivors without chromosomal abnormalities was 79.7 (16.6) with 25% below 2 SD of the population mean. CONCLUSIONS: Mortality has improved over time; time for lactate to fall on ECLS and volume of platelets transfused are independent predictors of mortality. Extracorporeal cardiopulmonary resuscitation and era were not independently associated with neurocognitive outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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".