From Risk Scales to Subclinical Atherosclerosis Quantification Through Non-invasive Imaging: Toward a New Paradigm in Cardiovascular Risk Prediction

Primary prevention of CVD (cardiovascular disease) is mainly based on the assessment of individual cardiovascular risk factors. However, often, only the most important (conventional) cardiovascular risk factors are determined, and every level of risk factor exposure is associated with a substantial variation in the amount of atherosclerosis. Measuring the effect of risk factor exposure over time directly in the vessel might (partially) overcome these shortcomings. Several non-invasive imaging techniques have the potential to accomplish this, each of these techniques focusing on a different stage of the atherosclerotic process. In this review, we aim to define the current role of various of these non-invasive measurements of atherosclerosis in individual cardiovascular risk prediction, taking into account the most recent insights about validity and reproducibility of these techniques and the results of recent prospective outcome trials. We conclude that, although the clinical application of FMD (flow-mediated dilation) and PWA (pulse wave analysis) in individual cardiovascular risk prediction seems far away, there may be a role for PWV (pulse wave velocity) and IMT (intima-media thickness) measurements in the near future.

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Cardiovascular Risk Prediction in Type 2 Diabetes Patients

Medical Connections ◽

10.33311/medcon.2016.40.4.3 ◽

2016 ◽

Vol 40 (4/2016) ◽

Keyword(s):

Type 2 Diabetes ◽

Cardiovascular Risk ◽

Risk Prediction ◽

Cardiovascular Risk Prediction ◽

Diabetes Patients

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Faculty Opinions recommendation of Common carotid intima-media thickness measurements do not improve cardiovascular risk prediction in individuals with elevated blood pressure: the USE-IMT collaboration.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.718306203.793493346 ◽

2014 ◽

Author(s):

Stefano Taddei ◽

Rosa Maria Bruno

Keyword(s):

Blood Pressure ◽

Cardiovascular Risk ◽

Risk Prediction ◽

Intima Media Thickness ◽

Carotid Intima Media Thickness ◽

Elevated Blood Pressure ◽

Elevated Blood ◽

Media Thickness ◽

Cardiovascular Risk Prediction ◽

Thickness Measurements

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Cardiovascular Risk Prediction using JBS3 Tool: A Kerala based Study

Current Medical Imaging Formerly Current Medical Imaging Reviews ◽

10.2174/1573405616666200103144559 ◽

2020 ◽

Vol 16 ◽

Author(s):

Paulin Paul ◽

Noel George ◽

B. Priestly Shan

Keyword(s):

Logistic Regression ◽

Cardiovascular Risk ◽

Risk Prediction ◽

Goodness Of Fit ◽

Significant Risk ◽

Lifetime Risk ◽

British Society ◽

Cvd Risk ◽

South Indian ◽

Cardiovascular Risk Prediction

Background: The accuracy of Joint British Society calculator3 (JBS3) cardiovascular risk prediction may vary within Indian population, and is not yet studied using south Indian Kerala based population data. Objectives: To evaluate the cardiovascular disease (CV) risk estimation using the traditional CVD risk factors (TRF) in Kerala based population. Methods: This cross sectional study has 977 subjects aged between 30 and 80 years. The traditional CVD risk markers are recorded from the medical archives of clinical locations at Ernakulum district, in Kerala The 10 year risk categories used are low (<7.5%), intermediate (≥7.5% and <20%), and high (≥20%). The lifetime classifications low lifetime (≤39%) and high lifetime (≥40%) are used. The study was evaluated using statistical analysis. Chi-square test was done for dependent and categorical CVD risk variable comparison. Multivariate ordinal logistic regression for 10-year risk model and odds logistic regression analysis for lifetime model was used to identify significant risk variables. Results: The mean age of the study population is 52.56±11.43 years. The risk predictions has 39.1% in low, 25.0% in intermediate, and 35.9% had high 10-year risk. The low lifetime risk had 41.1% and 58.9% is high lifetime risk. Reclassifications to high lifetime are higher from intermediate 10-year risk category. The Hosmer-Lemeshow goodness-of-fit statistics indicates a good model fit. Conclusion: The risk prediction and timely intervention with appropriate therapeutic and lifestyle modification is useful in primary prevention. Avoiding short-term incidences and reclassifications to high lifetime can reduce the CVD mortality rates.

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