Abstract 4361336: Exploring Disparities in Pediatric Wolff-Parkinson-White Patients by Race and Ethnicity: Results of a Multicenter Ambispective Registry
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».