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The relationship between the severity of coronary artery disease in angiography and the incidence of short-term major cardiovascular events of patients with Covid-19 and myocardial infarction: a cross-sectional study in Iran (preprint)
researchsquare; 2023.
Preprint
in English
| PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-2579378.v1
ABSTRACT
Background Coronary artery disease (CAD) has been frequently recognized as a risk factor for poor prognosis in COVID-19 patients. Syntax score is an invasive coronary angiographic-based tool used to determine the severity of CAD. In this study, we aim to investigate the prognostic significance of syntax score for mortality and morbidity among COVID-19 patients.Methods In this cross-sectional study, we have included patients with confirmed COVID-19 diagnosis who underwent percutaneous coronary intervention (PCI). Based on angiographic records, the CAD complexity was measured by Syntax score, and echocardiographic variables were documented. The laboratory data were obtained from the HISS database of the hospital. All patients were followed up one month after discharge for new cardiovascular events, rehospitalization, heart failure (HF), stent thrombosis, cerebrovascular accidents, and death.Results In one month, 108 patients were included in the study. The mean age was 64.8 ± 11.6, and 74% were male. The Cox regression model found no association between the Syntax score and the composite outcomes. In the univariate cox proportional HR model, MPV, LDH, and ESR were found to have predictive significance for in-hospital death. AKI was resulted to be significantly associated with rehospitalization in multivariate analysis.Conclusion The present study did not find a significant association between adverse outcomes and syntax score in COVID-19 patients referred for PCI. Acute kidney injury and duration of ICU stay was found to be the main factor predicting rehospitalization and HF. Future studies are needed to confirm these findings.
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Collection:
Preprints
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PREPRINT-RESEARCHSQUARE
Language:
English
Year:
2023
Document Type:
Preprint
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