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Published on: September 16, 2022
Risk Stratification in Patients with Coronary Artery Disease: A Practical Walkthrough in the Landscape of Prognostic
Sergio Buccheri1,2, Paolo D'Arrigo1, Gabriele Franchina1
1CAST, AOU. Policlinico-Vittorio Emanuele, University of Catania Catania, Italy.
Insights
Personalized medicine improves coronary artery disease (CAD) outcomes by considering individual factors. This review guides clinicians on using risk scoring systems for better prognostic stratification in CAD patients.
Area of Science:
- Cardiology
- Medical Informatics
- Public Health
Background:
- Coronary artery disease (CAD) remains a leading global cause of death despite advances in prevention and treatment.
- Individual patient factors significantly influence CAD outcomes, necessitating personalized approaches over generalized strategies.
- The proliferation of CAD risk scoring systems has created complexity in clinical decision-making.
Purpose of the Study:
- To review established risk models for patients with diagnosed coronary artery disease (CAD).
- To offer practical guidance on the application of prognostic risk stratification tools.
- To address the uncertainty surrounding the adoption of predictive models in clinical practice.
Main Methods:
- Literature review of accepted risk models for coronary artery disease (CAD).
- Analysis of the utility and application of various prognostic risk stratification tools.
- Synthesis of information to provide clinical decision-making guidance.
Main Results:
- Identified and summarized the most accepted risk models for CAD prognostic stratification.
- Highlighted the importance of personalized medicine in managing CAD.
- Provided a framework for understanding and applying risk models in clinical settings.
Conclusions:
- Risk stratification models are crucial for personalized CAD management.
- Clinicians need clear guidance to effectively utilize predictive tools for better patient outcomes.
- Adopting appropriate risk models can enhance the precision of CAD treatment strategies.
Abstract:
Although a combination of multiple strategies to prevent and treat coronary artery disease (CAD) has led to a relative reduction in cardiovascular mortality over recent decades, CAD remains the greatest cause of morbidity and mortality worldwide. A variety of individual factors and circumstances other than clinical presentation and treatment type contribute to determining the outcome of CAD. It is increasingly understood that personalised medicine, by taking these factors into account, achieves better results than "one-size-fitsall" approaches. In recent years, the multiplication of risk scoring systems for CAD has generated some degree of uncertainty regarding whether, when and how predictive models should be adopted when making clinical decisions. Against this background, this article reviews the most accepted risk models for patients with evidence of CAD to provide practical guidance within the current landscape of tools developed for prognostic risk stratification.
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