Contemporary Trends, Outcomes, and Novel Risk Score for Spontaneous Coronary Artery Dissection: A Nationwide Analysis

Area of Science:

• Cardiology
• Vascular Medicine
• Health Informatics

Background:

• Spontaneous coronary artery dissection (SCAD) is an under-recognized cause of acute coronary syndrome (ACS).
• Understanding SCAD's distinct characteristics, predictors, and outcomes is crucial for patient management.
• The National Inpatient Sample (NIS) database provides a large-scale dataset for studying SCAD prevalence and associated factors.

Purpose of the Study:

• To investigate the characteristics, predictors, and outcomes of SCAD within a large inpatient population.
• To identify key risk factors associated with SCAD and in-hospital mortality.
• To develop and validate a predictive risk score model for SCAD.

Main Methods:

• Utilized the NIS database from 2016-2020 to identify hospitalizations for ACS and SCAD.
• Employed multivariable logistic regression to determine risk factors for SCAD and mortality.
• Developed a risk score model using 2016-2019 data and validated it with 2020 data.

Main Results:

• SCAD accounted for 0.43% of ACS hospitalizations (30,770 cases), with a mean age of 59.6 years and 58.5% female patients.
• SCAD patients exhibited higher in-hospital mortality (8.0% vs. 6.0%) and acute stroke rates (3.2% vs. 1.7%) compared to non-SCAD ACS patients.
• Strongest SCAD predictors included percutaneous coronary intervention history, coronary artery aneurysm, and fibromuscular dysplasia. Key mortality predictors were cardiogenic shock, ECMO, balloon pump, cardiac arrest, and acute kidney injury.

Conclusions:

• SCAD is a rare yet significant cause of ACS with unique risk factors and poorer outcomes.
• The developed risk score model demonstrated strong performance (AUC 0.867 development, 0.860 validation) for early SCAD identification.
• The risk model has the potential to improve early detection and management strategies for SCAD patients.