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Clinical Characteristics and Outcomes of COVID-19 Positive Acute Coronary Syndrome Patients; a multisource Electronic Healthcare Records Study from England
Preprint
en En
| PREPRINT-MEDRXIV
| ID: ppmedrxiv-20175091
ABSTRACT
BackgroundPatients with underlying cardiovascular disease and Coronavirus disease 2019 (COVID-19) infection are at increased risk of morbidity and mortality. However, there is limited information on management and outcomes of patients presenting with acute coronary syndrome (ACS) and concomitant COVID19 infection. ObjectivesThis multisource national analysis of live data from England was designed to characterise the presenting profile and outcomes of patients hospitalized with ACS and COVID-19 infection. MethodsMultisource data from all acute NHS hospital in England was linked to study the characteristics and outcomes of patients hospitalized with COVID-19 ACS compared to non COVID-19 ACS patients. Hierarchical multilevel models were constructed to study the association between COVID19 ACS and in-hospital and 30-day mortality. ResultsBetween 1st March 2020 and 31st May 2020, 517 (4.0%) were admitted with COVID-19 ACS from a total of 12,958 ACS patients. COVID-19 ACS patients were generally older, BAME ethnicity, more comorbid and had unfavourable presenting characteristics compared to non-COVID-19 ACS patients. They were less likely to receive invasive coronary strategy in the form of coronary angiography (67.7% vs 81.0%), PCI (30.2% vs 53.9%), dual antiplatelet medication 76.3% vs 88.0%), and other important secondary medication. Patients with COVID-19 ACS had higher in-hospital (aOR 3.27 95%CI 2.41-4.42) and 30-day mortality (aOR 6.53 95%CI 5.1-8.36) compared to non COVID-19 ACS group. ConclusionCOVID-19 infection is prevalent but less frequent in the patients hospitalized with ACS in England. Presence of COVID-19 infection in patients with ACS is associated with significant mortality hazard.
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Texto completo:
1
Colección:
09-preprints
Base de datos:
PREPRINT-MEDRXIV
Tipo de estudio:
Prognostic_studies
Idioma:
En
Año:
2020
Tipo del documento:
Preprint