Precision Medicine in Cardiovascular Disease Prevention

Preface
Acknowledgments
Contents
1 Social Determinants
Social Determinants of Health and Cardiovascular Care: A Historical Perspective
Landmark Reports on Health Disparities: Relevance to CVD
Role of SDOH in Cardiovascular Care: Ignored for Far Too Long
Current State of CVD Disparities in the US
SDOH, ‘Traditional’ Risk Factors and Current Models of CVD Care
SDOH and CVD: A Review of Current Literature
SDOH: A Domain-Based Analysis
Economic Stability
Current Evidence and Pathways
Summary
Education
Current Evidence and Pathways
Summary
Neighborhood and Physical Environment
Current Evidence and Pathways
Summary
Food
Current Evidence and Pathways
Summary
Community and Social Context
Current Evidence and Pathways
Summary
Healthcare
Current Evidence and Pathways
Summary
Conclusions
References
2 Biomarkers
Introduction
Lipid Biomarkers and Cardiovascular Risk
Low-Density Lipoprotein Cholesterol
Estimation of LDL-C in Precision Medicine
There is More Than LDL-C: LDL Particles and Apolipoprotein B
Non-High-Density Lipoprotein Cholesterol (non-HDL-C): The “Poor Man” apoB?
Maximizing the Use of the Standard Lipid Panel: The Total Cholesterol to HDL-C Ratio
Residual Risk and Lipoprotein-Related Risk Beyond LDL: Triglyceride-Rich Lipoproteins
Lipoprotein (a)—ready for Prime-Time Use?
Non-Lipid Cardiac Biomarkers in Risk Stratification of Asymptomatic Patients
Cardiac Biomarkers of Wall Stress and Myocardial Injury
Factors Affecting Biomarker Interpretation
Cardiac Troponin and Cardiovascular Risk
Cardiac Biomarkers in Hypertension
Cardiac Biomarkers in Aortic Stenosis
Cardiac Biomarkers in Heart Failure
HsCRP
GlycA
Galectin-3
Lp-PLA2
Hepatocyte Growth Factor
Fibrinogen
Adipokines
Sex Hormones
Conclusions
References
3 Genetics
Introduction
Rare Variation Highlights Novel Disease Pathways
Background
Relevance for Cardiovascular Prevention
Leveraging Common Variant Genomics to Understand Disease Pathophysiology
Background
Relevance for Cardiovascular Prevention
Mendelian Randomization Can Help Us Understand Causal Relationships
Background
Relevance for Cardiovascular Prevention
Polygenic Risk Scores Can Improve Risk Prediction
Background
Relevance for Cardiovascular Prevention
Conclusions and Future Perspectives
References
4 Atherosclerosis Imaging
Traditional Risk Scores and Individualized Risk Assessment
Proposed Tools for Personalizing Risk Estimation
Serum Biomarkers and Genetics: Pros and Cons
Coronary Artery Calcium
CAC Imaging
CAC Scoring
Early Data
Major Population-Based Studies
MESA
Heinz Nixdorf
Rotterdam Study
Meta-Analysis
CAC in Guidelines
Shared Decision-Making
Risk Re-Classification Through CAC
CAC Future Directions
CAC Score = 0
CAC Predicting Non-CVD Outcomes
Risk Estimators Incorporating CAC Scores
Coronary Computed Tomography Angiography
Technology
Characterization of Atherosclerotic Plaque
Scoring/Measuring
Evidence for Clinical Outcome
CCTA Versus CAC
Extra-Coronary Atherosclerosis Imaging
Carotid Artery Ultrasound
Ultrasound Carotid Plaque Imaging
CT-Detected Extra-Coronary Atherosclerosis
Magnetic Resonance Imaging
Tests for Myocardial Ischemia
Structural Imaging
Echocardiography
Cardiac Magnetic Resonance
Diagnostic Accuracy of Cardiac Imaging
Conclusion
References
5 Digital Health
Introduction
Consumer Connected Health & Tracking
Heart Rate Monitoring and Arrhythmia Detection
Blood Pressure Tracking
Weight Tracking and Management
Medication Adherence Support and Tracking
Physical Activity and Exercise Tracking
Diet and Nutrition Tracking
Digital Biomarker Tracking
Digital Health Coaching
Overview of Digital Health Coaching
Exercise Health Coaching
Smoking Cessation Coaching
Blood Pressure Control Coaching
Blood Glucose Control Coaching
Transformation of Healthcare Delivery
Outpatient Clinic (Chronic Condition Management and Prevention)
Inpatient (Acute Care)
Center-Based Services (Post Acute Care)
Conclusions
References
6 Artificial Intelligence and Machine Learning
Preventive Cardiology, the Past and the Future
Artificial Intelligence, Machine Learning, and Deep Learning
Applications in the Cardiovascular Care
Coronary Artery Disease
Heart Failure
Atrial Fibrillation
Sudden Cardiac Death
Polygenic Risk Scores in the Era of Machine Learning
A Dynamic Approach to Prevention
Limitations and Future Directions
Disclosures
References
7 Novel Research Designs
Introduction
History of RCTs
Benefits of RCTs
Limitations of RCTs
Micro-randomized Trials
Summary of the Design
Pros and Cons
MRT Example
N-of-1
Summary of the Design
Pros and Cons
Example of N-of-1 Trials
Patient Centered Participatory Research/User Centered Design
Summary of Design
Pros and Cons
Example of PD
Site-Less/Digital Clinical Trials
Summary of Design
Pros and Cons
Example of a Site-Less Design
Stepped Wedge Trial
Summary of Design
Pros and Cons
Example of Stepped Wedged Trial Design
Summary/Conclusion
References
8 Shared Decision Making
Shared Decision Making: The Introduction
The Role of Shared Decision Making in Personalizing Care
Shared Decision Making Highlighted in the ACC/AHA Guidelines
Statin Use in Primary Prevention
Shared Decision Making: The Transition from the Population to Individual Level
Shared Decision Making in Clinical Practice
Shared Decision Making—Discussing Patient Risk
When Shared Decision Making Feels Like Shared Decision Guessing
Selective Use of Coronary Artery Calcium Measurements
When ‘Plan A’ Fails, Lean on Shared Decision Making
Statin Associated Side-Effects
Ezetimibe, PCSK9-Inhibitors, Icosapent Ethyl & Bempedoic Acid
Shared Decision Making Beyond Statins and LDL-C Lowering Therapies
Aspirin
Blood Pressure
Anticoagulation
Conclusion
References
Index