Trends in Coronary Artery Anomalies Detection by Coronary Computed Tomography Angiography (CCTA): A Real-Life Comparative Study before and during the COVID-19 Pandemic.
Healthcare (Basel)
; 12(11)2024 May 26.
Article
en En
| MEDLINE
| ID: mdl-38891166
ABSTRACT
BACKGROUND:
In the wake of the coronavirus disease 19 (COVID-19) pandemic, affecting healthcare systems globally, urgent research is needed to understand its potential repercussions on the diagnosis and management of cardiovascular disorders. This emphasises the importance of detecting coronary artery anomalies (CAAs), rare conditions that can range from benign to potentially life-threatening manifestations. We aimed to retrospectively assess the impact of the COVID-19 pandemic on the detection of various coronary anomalies using Coronary Computed Tomography Angiography (CCTA) within a regional tertiary cardiology unit in north-eastern Romania, focusing on perceived occurrence in the population under study, types, and related demographic and clinical factors.METHODS:
We analysed CCTA scans and investigated the trends in CAA detection among cardiology patients over a decade. We compared pre-COVID-19 and pandemic-era data to assess the impact of healthcare utilisation, patient behaviour, and diagnostic approaches on anomaly detection.RESULTS:
Our analysis revealed a higher detection rate of CAAs during the pandemic (3.9% versus 2.2%), possibly highlighting differences in patient clinical profile and addressability changes presentation compared to the previous period. Origination and course anomalies, often linked to severe symptoms, were significantly higher pre-COVID-19 (64.1% versus 51.3%). Conversely, intrinsic CAAs, typically asymptomatic or manifesting later in life, notably increased during the pandemic (49.0% versus 61.4%; p = 0.020).CONCLUSIONS:
Our study underscores a significant rise in CAA detection during the COVID-19 era, potentially linked to changes in cardiovascular and respiratory clinical patterns, with advanced imaging modalities like CCTA offering accuracy in identification.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
Healthcare (Basel)
Año:
2024
Tipo del documento:
Article
País de afiliación:
Rumanía