Racial and Ethnic Variation in ECMO Utilization and Outcomes in Pediatric Cardiac ICU Patients
Bibliographic record
Abstract
Previous studies have reported racial disparities in extracorporeal membrane oxygenation (ECMO) utilization in pediatric cardiac patients. The objective of this study was to determine if there was racial/ethnic variation in ECMO utilization and, if so, whether mortality was mediated by differences in ECMO utilization. This is a multicenter, retrospective cohort study of the Pediatric Cardiac Critical Care Consortium clinical registry. Analyses were stratified by hospitalization type (medical vs surgical). Logistic regression models were adjusted for confounders and evaluated the association between race/ethnicity with ECMO utilization and mortality. Secondary analyses explored interactions between race/ethnicity, insurance, and socioeconomic status with ECMO utilization and mortality. A total of 50,552 hospitalizations from 34 hospitals were studied. Across all hospitalizations, 2.9% (N = 1,467) included ECMO. In medical and surgical hospitalizations, Black race and Hispanic ethnicity were associated with severity of illness proxies. In medical hospitalizations, race/ethnicity was not associated with the odds of ECMO utilization. Hospitalizations of other race had higher odds of mortality (adjusted odds ratio [aOR]: 1.61; 95% CI: 1.22-2.12; P = 0.001). For surgical hospitalizations, Black (aOR: 1.24; 95% CI: 1.02-1.50; P = 0.03) and other race (aOR: 1.50; 95% CI: 1.17-1.93; P = 0.001) were associated with higher odds of ECMO utilization. Hospitalizations of Hispanic patients had higher odds of mortality (aOR: 1.31; 95% CI: 1.03-1.68; P = 0.03). No significant interactions were demonstrated between race/ethnicity and socioeconomic status indicators with ECMO utilization or mortality. Black and other races were associated with increased ECMO utilization during surgical hospitalizations. There were racial/ethnic disparities in outcomes not explained by differences in ECMO utilization. Efforts to mitigate these important disparities should include other aspects of care.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".