Leveraging pediatric veno-arterial extra corporeal membrane oxygenation parameters to identify early risk factors for mortality
Bibliographic record
Abstract
ObjectivePediatric Veno-Arterial Extra Corporeal Membrane Oxygenation (VA ECMO) can be a lifesaving technology; however, it is associated with high mortality. A successful VA ECMO course requires attention to multiple aspects of patient care; yet often overlooked are ECMO flow parameters. Early, potentially modifiable, risk factors associated with patient mortality should be scrutinized in patients requiring VA ECMO.MethodRetrospective single center experience of pediatric patients requiring VA ECMO from January 2021 to October 2023. Laboratory and ECMO flow parameters were extracted from the patients record and analyzed. Risk factors were analyzed using a Cox proportion hazard regression, and a multivariate regression.Main ResultsThere were 45 patients studied. Overall survival was 51%. Upon uncorrected analysis there were no significant differences between the patients who survived and those who died during their hospital admission. Utilizing a Cox proportion hazard regression, platelet count, fibrinogen level, and creatinine level normalized to age within the first 24 hours of a patients ECMO course were significant risk factors for hospital mortality. We did not find that ECMO flow parameters were significantly associated with mortality within the first 24 hours.SignificanceAlthough we did not find a significant difference among ECMO flow parameters in this study, this work highlights that granular ECMO flow data can be incorporated to risk analysis profiles and potential modeling in pediatric VA ECMO. This study demonstrated that when controlling for ECMO flow parameters, kidney dysfunction and clotting regulation are associated with pediatric VA ECMO mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".