Predictors of mortality and neurological morbidity in children undergoing extracorporeal life support for cardiac disease
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was to determine the incidence and risk factors for death and adverse neurological outcomes in children receiving extracorporeal life support (ECLS) for cardiac indications. METHODS: A retrospective single centre consecutive cohort study was conducted in children who received ECLS for cardiac indications between January 1990 and June 2000. Health records and neuroimaging films were assessed, and long-term outcomes were obtained by standardized telephone follow-up or by assessments performed in outpatient clinic. Clinical, neuroimaging and surgical predictors of outcome were tested. RESULTS: Of 90 children studied, short-term clinical neurological events (during hospitalization) occurred in 20 children (22%) during or following ECLS. Long-term neurological sequelae were present in 11 of 31 children discharged alive, after a mean follow-up interval of 4.5 years (range 4 months to 9 years). Death occurred in 59 children (66%) during hospitalisation, and in 3 following discharge. Of the 28 long-term survivors, only 15 children (17%) survived without neurological sequelae. Abnormal neuroimaging was associated with short-term neurological events (P = 0.03, OR 10.5), and the use of CPR prior to ECLS (P = 0.02, OR 2.9) was the only significant predictor of death. There were no significant predictors of long-term neurological sequelae. CONCLUSIONS: More than two-thirds of the children receiving ECLS died, and 39% (11/28) of long-term survivors had neurological deficits. Although mortality is close to 100% without this type of support, there is still a significantly high morbidity and mortality with this type of support.
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 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".