Key result
Non-traditional atherosclerotic image markers, including carotid intima-media thickness and plaque risk score, significantly correlated with modified cardiovascular risk categories (p<0.05).
Why the study?
Whether non-traditional image markers can improve traditional cardiovascular risk estimation had remained untested in Kerala-based participants.
Does the addition of non-traditional image-based markers (cIMT, plaque complexity) to traditional risk factors improve cardiovascular risk classification in a Kerala-based population?
Cross-Sectional (n=594)
Yes
Does the addition of non-traditional image-based markers (cIMT, plaque complexity) to traditional risk factors improve cardiovascular risk classification in a Kerala-based population?
The inclusion of ultrasound-derived atherosclerotic markers like cIMT and plaque complexity significantly improves cardiovascular risk classification accuracy.
Answers are grounded in this paper and cite their sources.
Supports addition of cIMT and plaque scores to traditional factors; leaves open outcome impact in prospective cohorts.
BACKGROUND: Non-traditional image markers can improve the traditional cardiovascular risk estimation, is untested in Kerala based participants. OBJECTIVE: To identify the relationship between the 'Modified CV risk' categories with traditional and non-traditional image-based risk markers. The correlation and improvement in reclassification, achieved by pooling atherosclerotic non-traditional markers with Intermediate (≥7.5% and <20%) and High (≥20%) 10-year participants is evaluated. METHODS: The cross-sectional study with 594 participants has the ultrasound measurements recorded from the medical archives of clinical locations at Ernakulum district, Kerala. With carotid Intima-Media Thickness (cIMT) measurement, the Plaque (cP) complexity was computed using selected plaque characteristics to compute the carotid Total Plaque Risk Score (cTPRS) for superior risk tagging. Statistical analysis was done using RStudio, the classification accuracy was verified using the decision tree algorithm. RESULTS: The mean age of the participants was (58.14±10.05) years. The mean cIMT was (0.956±0.302) mm, with 65.6% plaque incidence. With 94.90% variability around its mean, the Multinomial Logistic Regression model identifies cIMT and cTPRS, age, diabetics, Familial Hypercholesterolemia (FH), Hypertension treatment, the presence of Rheumatoid Arthritis (RA), Chronic Kidney Disease (CKD) as significant (p<0.05). cIMT and cP were found significant for 'Intermediate High', 'High' and 'Very High' 'Modified CV risk' categories. However, age, diabetes, gender and use of hypertension treatment are significant for the 'Intermediate' 'Modified CV risk' category. The overall performance of the MLR model was 80.5%. The classification accuracy verified using the decision tree algorithm has 78.7% accuracy. CONCLUSION: The use of atherosclerotic markers shows a significant correlation suitable for a nextlevel reclassification of the traditional CV risk.
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Paul et al. (2020) conducted a cross-sectional in Cardiovascular risk (n=594). Non-traditional image-based markers (cIMT and cTPRS) vs. Traditional cardiovascular risk markers was evaluated on Relationship between 'Modified CV risk' categories and traditional/non-traditional image-based risk markers (p=<0.05). Non-traditional atherosclerotic image markers, including carotid intima-media thickness and plaque risk score, significantly correlated with modified cardiovascular risk categories (p<0.05).
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