Abstract 4361336: Exploring Disparities in Pediatric Wolff-Parkinson-White Patients by Race and Ethnicity: Results of a Multicenter Ambispective Registry
Bibliographic record
Abstract
Background: Social determinants of health —including socioeconomic status, race and ethnicity, and access to care—affect health outcomes and contribute to disparities in disease burden and treatment. We sought to describe racial and ethnic differences in pediatric WPW patients (pts), focusing on healthcare utilization, management, and life-threatening events (LTEs) using a multicenter registry. Methods: Data were extracted from the international ambispective WPW registry, which enrolled pts age < 21 years (2017- 2024). Demographics, clinical presentation, ED visits, hospital/ICU admissions, antiarrhythmic use, and EP study (EPS) (transesophageal and/or invasive) were compared by race (White vs. non-White) and ethnicity (Hispanic vs. non-Hispanic). LTEs were defined as sudden death (SD), aborted SD, or pre-excited AF with rapid conduction or hemodynamic instability. Logistic regression model adjusting for age at enrollment was performed to evaluate associations between race and total and invasive EPS rates. Results: 1118 pts from 23 centers were included. Racial distribution was White (87%), Black (6%), Asian (3%), others (1%), and > 1 race (3%). Most pts with reported ethnicity were non-Hispanic (NH) (93%). Compared to White pts, non-White pts were more likely to have congenital heart disease and persistent pre-excitation but less likely to require ICU admission or undergo EPS, including invasive EPS (Table 1). There were no significant racial differences in age at presentation at EPS, symptoms at presentation, hospitalization, antiarrhythmic drug use, or LTEs at presentation or f/u. In logistic regression models adjusting for age at enrollment, race was not significantly associated with invasive EPS (p=0.067). However, White pts were significantly more likely to undergo any EPS than non-White pts (OR 1.82, 95% CI 1.05–3.14). With respect to ethnicity, Hispanic pts underwent EPS at a younger age than NH pts (12.13 vs. 13.28 yrs, p=0.033). There were no other significant management or outcome differences between ethnic groups. Conclusion: Racial disparities in healthcare utilization and management strategies exist among pediatric WPW pts, with non-White pts less likely to undergo any EPS despite higher rates of persistent pre-excitation. Rates of LTE, however, were similar between racial and ethnic groups. Future studies should focus on exploring causes of racial disparities that would inform targeted interventions to promote equitable 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".