Impact of COVID-19 Pandemic on Sex and Racial Disparities in Chest Pain Presentation and Management Through the Emergency Department
Notice bibliographique
Résumé
Background: Sex and racial disparities in the presentation and management of chest pain persist, however, the impact of coronavirus disease 2019 (COVID-19) on these disparities have not been studied. We sought to determine whether the COVID-19 pandemic contributed to pre-existing sex and racial disparities in the presentation, management, and outcomes of patients presenting to the emergency department (ED) with chest pain. Methods: We conducted an observational cohort study with retrospective data collection of patients between January 1, 2016, and May 1, 2022. This was a single study conducted at a quaternary academic medical center of all patients who presented to the ED with a complaint of chest pain or chest pain equivalent symptoms. Patient were further segregated into different groups based on sex (male, female), race, ethnicity (Asian, Black, Hispanic, White, and other), and age (18 - 40, 41 - 65, > 65). We compared diagnostic evaluations, treatment decisions, and outcomes during prespecified time points before, during, and after the COVID-19 pandemic. Results: This study included 95,764 chest pain encounters. Total chest pain presentations to the ED fell about 38% during the early pandemic months. Females presented significantly less than males during initial COVID-19 (48% vs. 52%, P < 0.001) and Asian females were least likely to present. There was an increase in the total number of troponins and echocardiograms ordered during peak COVID-19 across both sexes, but females were still less likely to have these tests ordered across all timepoints. The number of coronary angiograms did not increase during peak COVID-19, and females were less likely to undergo coronary angiogram during all timepoints. Finally, females with chest pain were less likely to be diagnosed with acute myocardial infarction (AMI) during all timepoints, while in-hospital deaths were similar between males and females during all timepoints. Conclusions: During COVID-19, females, especially Asian females, were less likely to present to the ED for chest pain. Non-White patients were less likely to present to the ED compared to White patients prior to and during the pandemic. Disparities in management and outcomes of chest pain encounters remained similar to pre-COVID-19, with females receiving less cardiac workup and AMI diagnoses than males, but in-hospital mortality remaining similar between groups and timepoints.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».