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Association Between ECG Findings and Atherosclerotic Cardiovascular Disease (ASCVD) Risk Score: A Cross-Sectional
Pouria Azami1,2,3, Alireza Mirhosseini3,4, Mohammadjavad Nobakhti1,2
1School of Medicine Shiraz University of Medical Sciences Shiraz Iran.
Insights
Electrocardiogram (ECG) findings like ST depression and left bundle branch block (LBBB) are associated with Atherosclerotic Cardiovascular Disease (ASCVD) risk scores in asymptomatic individuals. These ECG markers can help identify those at higher cardiovascular risk.
Area of Science:
- Cardiology
- Preventive Medicine
- Medical Diagnostics
Background:
- Cardiovascular disease is a leading global cause of death, necessitating early risk detection.
- The Atherosclerotic Cardiovascular Disease (ASCVD) risk score is a key tool for predicting cardiovascular events.
- Identifying novel markers for risk stratification in asymptomatic individuals is crucial.
Purpose of the Study:
- To investigate the association between various Electrocardiogram (ECG) findings and 10-year ASCVD risk scores.
- To evaluate the predictive value of specific ECG parameters in asymptomatic individuals without a history of cardiovascular events.
- To explore the utility of ECG in enhancing cardiovascular risk assessment.
Main Methods:
- A cross-sectional study utilizing data from the Shiraz Heart Study (SHS) on 1471 participants aged 40-70.
- Analysis of continuous and categorical ECG findings by trained cardiologists.
- Calculation of 10-year ASCVD risk scores and multivariate regression to assess associations, adjusting for confounders.
Main Results:
- Significant associations were observed between several ECG variables (P-wave duration, PR interval, QRS duration, QRS axis) and ASCVD risk.
- Categorical ECG findings, including ST depression, ST elevation, and left bundle branch block (LBBB), were significantly linked to ASCVD scores.
- ST depression and LBBB emerged as independent predictors of ASCVD risk after adjusting for clinical factors.
Conclusions:
- ST depression and LBBB demonstrate a modest but significant association with the 10-year ASCVD risk score.
- Incorporating these ECG findings into clinical practice may improve the identification of high-risk individuals.
- These ECG markers can potentially refine cardiovascular risk prediction models and guide personalized interventions.
Background And Aims:
Cardiovascular disease remains a leading cause of morbidity and mortality worldwide, making early detection and risk assessment critical. Various clinical tools, including the Atherosclerotic Cardiovascular Disease (ASCVD) risk score, have been developed to predict cardiovascular risk. This study aimed to evaluate the association of various Electrocardiogram (ECG) findings with 10-year ASCVD risk scores in asymptomatic individuals without prior cardiovascular events, using data from the Shiraz Heart Study (SHS).
Materials And Methods:
This cross-sectional study included participants aged 40-70 years from the Shiraz Heart Study (SHS). Inclusion criteria required complete ECG data and recorded ASCVD risk factors. ECG findings, encompassing both continuous and categorical variables, were reviewed by trained cardiologists. ASCVD risk scores were calculated using demographic and clinical variables. Statistical analyses, including multivariate regression, assessed associations between ECG parameters and 10-year ASCVD risk scores, adjusting for key confounders.
Result:
A total of 1471 participants were included in the study, with 44.5% male (N = 654) and a mean age of 51.65 years (SD = 7.84). The mean ASCVD score was 5.49 (SD = 6.41). Significant associations were found between continuous ECG variables, such as P-wave duration, PR interval, QRS duration, and QRS axis, with ASCVD risk. Categorical ECG findings, including ST depression, ST elevation, left bundle branch block (LBBB), prolonged P-wave duration, and left atrial enlargement, were also significantly associated with ASCVD scores. Multivariate linear regression identified ST depression (B = 0.060, p < 0.001) and LBBB (B = 0.031, p = 0.039) as independent predictors of ASCVD risk, after adjusting for confounders such as age, gender, hypertension, diabetes, and cholesterol levels.
Conclusion:
ST depression and LBBB show a modest association with cardiovascular risk stratification using the 10-year ASCVD risk score. Incorporating these ECG markers into clinical assessments may aid in identifying high-risk individuals, enabling more personalized interventions and refining cardiovascular risk prediction models.
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