Cardiovascular Prevention: Migrating From a Binary to a Ternary Classification

Area of Science:

• Cardiovascular Medicine
• Medical Diagnostics
• Inflammation Research

Background:

• Traditional binary risk assessment models have limitations in managing complex diseases.
• Atherosclerosis and vascular disease progression require nuanced understanding beyond standard risk factors.
• Previous research demonstrated the positive impact of evidence-based management on subclinical atherosclerosis.

Purpose of the Study:

• To introduce and advocate for a ternary model of disease identification.
• To demonstrate how this model optimizes individualized disease management.
• To enhance the understanding of atherosclerosis and vascular disease progression.

Main Methods:

• Transitioning from a binary to a ternary approach for disease risk assessment.
• Implementing a redefined disease/inflammatory model for patient management.
• Utilizing comprehensive, evidence-based strategies for atherosclerosis treatment.

Main Results:

• The ternary model facilitates individualized and optimal disease management.
• The redefined approach successfully identifies, stabilizes, and regresses atherosclerosis.
• Enhanced understanding of vascular disease progression is achieved.

Conclusions:

• A ternary model augments, rather than replaces, standard risk factor identification.
• This comprehensive approach benefits individual patient care and disease outcomes.
• Optimized management of atherosclerosis and vascular disease is achievable.