Current Trends in Cardiology

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Mini Review - Current Trends in Cardiology (2024) Volume 8, Issue 12

Cardiovascular risk stratification: A personalized approach to preventing heart disease

Bularga Anda *

Department of Cardiology, University of Chinese Medicine, China.

*Corresponding Author:
Bularga Anda
Department of Cardiology, br /> University of Chinese Medicine,
China
E-mail: bularganda@gmail.com

Received:02-Dec-2024,Manuscript No. AACC-24-154840; Editor assigned:03-Dec-2024,PreQC No. AACC-24-154840(PQ); Reviewed:16-Dec-2024,QC No. AACC-24-154840; Revised:20-Dec-2024, Manuscript No. AACC-24-154840(R); Published:26-Dec-2024,DOI:10.35841/aacc-8.12.348

Citation: Anda B. Cardiovascular risk stratification: A personalized approach to preventing heart disease. Curr Trend Cardiol. 2024;8(12):348

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Abstract

      

Introduction

Cardiovascular Disease (CVD) remains one of the leading causes of death worldwide. Despite advancements in medical treatments, heart disease continues to claim millions of lives each year. This highlights the urgent need for effective prevention strategies. One of the most powerful tools in combating heart disease is cardiovascular risk stratification, which helps healthcare professionals predict the likelihood of cardiovascular events in individuals and personalize preventive measures. Cardiovascular risk stratification refers to the process of evaluating a person's risk of developing cardiovascular disease or experiencing a cardiovascular event, such as a heart attack or stroke, over a specific period. By assessing various risk factors, healthcare providers can categorize individuals into different risk groups (low, moderate, or high) and recommend appropriate interventions based on their individual risk profiles. Several factors contribute to the development of cardiovascular diseases. These include both modifiable and non-modifiable factors. The risk of cardiovascular events increases with age, especially in individuals over 45 for men and 55 for women. Men are generally at higher risk at a younger age, but the risk for women increases post-menopause. A genetic predisposition to heart disease can significantly increase risk, particularly when close relatives are affected early in life. [1,2].

High blood pressure damages the arteries, making the heart work harder and increasing the risk of heart disease. Elevated levels of Low-Density Lipoprotein (LDL) cholesterol contribute to plaque build up in arteries, leading to atherosclerosis. Smoking accelerates the development of atherosclerosis, reducing the oxygen supply to the heart and increasing clot formation. Sedentary lifestyles contribute to obesity, high cholesterol, and high blood pressure, all of which increase cardiovascular risk. Excess weight, particularly abdominal fat, is linked to numerous risk factors such as high cholesterol, hypertension, and diabetes. Diabetes accelerates the process of atherosclerosis and increases the risk of heart attacks and strokes. Diets high in saturated fats, trans fats, and sodium increase the likelihood of hypertension, high cholesterol, and obesity. [3,4].

Several tools and scoring systems are available to assess cardiovascular risk. These models use the above risk factors to estimate the probability of cardiovascular events. Some commonly used risk scores include. Developed from the Framingham Heart Study, this score estimates the 10-year risk of coronary heart disease based on factors such as age, cholesterol levels, blood pressure, smoking, and diabetes. It is widely used in clinical practice to guide decision-making. The Atherosclerotic Cardiovascular Disease (ASCVD) Risk Calculator, developed by the American College of Cardiology (ACC) and the American Heart Association (AHA), provides a 10-year and lifetime risk of heart attack, stroke, or death from cardiovascular disease. It includes factors such as cholesterol levels, blood pressure, age, sex, smoking status, and diabetes. Commonly used in the UK, the QRISK score calculates the risk of cardiovascular disease over the next 10 years based on clinical factors and ethnicity, among others. This score includes traditional risk factors as well as High-Sensitivity C-Reactive Protein (hs-CRP), a marker of inflammation that may be elevated in people at higher risk for cardiovascular events. [5,6].

While traditional risk models are invaluable, they don't account for all individual variations. Emerging tools aim to refine cardiovascular risk stratification further. With advances in genomics, genetic risk scores are being explored as a way to assess an individual's genetic predisposition to heart disease. These scores incorporate multiple genetic variants that influence cardiovascular health. Inflammatory markers such as hs-CRP, as well as lipid biomarkers like lipoprotein(a), are being researched for their role in more accurately predicting cardiovascular events. High levels of these markers may indicate a higher risk even in individuals without traditional risk factors. Tools like Coronary Artery Calcium (CAC) scoring and Carotid Intima-Media Thickness (CIMT) measurements provide visual indicators of atherosclerosis and may help identify individuals at higher risk even before they experience symptoms.AI algorithms are now being used to analyze large datasets of patient information, including medical history, lab results, imaging, and genetic data, to provide more accurate and personalized risk assessments. [7,8].

Once a person's cardiovascular risk has been assessed, the next step is intervention. For those at high risk, preventive measures may include. Encouraging a heart-healthy diet (e.g., rich in fruits, vegetables, whole grains), regular physical activity, smoking cessation, and weight loss are critical steps in reducing cardiovascular risk. For patients with high cholesterol or hypertension, medications like statins or ACE inhibitors may be prescribed to manage these conditions and reduce the risk of cardiovascular events. For individuals with diabetes or those at high risk, regular check-ups are essential to monitor blood pressure, cholesterol levels, and other risk factors. [9,10].

Conclusion

Cardiovascular risk stratification is a vital component of heart disease prevention. By identifying individuals at higher risk and tailoring interventions to their unique profiles, healthcare providers can help prevent the onset of cardiovascular events and improve patient outcomes. With emerging technologies and refined assessment tools, we are moving toward a more personalized approach to cardiovascular health—one that could significantly reduce the burden of heart disease.

References

  1. Missinato MA. Dusp6 attenuates Ras/MAPK signaling to limit zebrafish heart regeneration. 2018; 145: dev157206.
  2. Indexed atGoogle ScholarCross Ref

  3. Li C. Dusp6 (Mkp3) is a negative feedback regulator of FGF?stimulated ERK signaling during mouse development. Development. 2007; 134: 167–76.
  4. Indexed atGoogle ScholarCross Ref

  5. Keyse SM. The regulation of oncogenic Ras/ERK signalling by dual?specificity mitogen activated protein kinase phosphatases (MKPs).Semin Cell Dev Biol. 2016; 50: 125–32.
  6. Indexed atGoogle ScholarCross Ref

  7. Haj FG. Protein?tyrosine phosphatase 1B substrates and metabolic regulation. Semin Cell Dev Biol. 2015; 37: 58–65.
  8. Indexed atGoogle ScholarCross Ref

  9. Smith AM. The protein tyrosine phosphatase 1B inhibitor MSI?1436 stimulates regeneration of heart and multiple other tissues. Npj Regen Medicine. 2017; 2: 57. 
  10. Indexed atGoogle Scholar,

  11. Maack C. Treatments targeting inotropy. Eur Heart J. 2019;40:3626–3640D.
  12. Indexed atGoogle scholarCross Ref

  13. Ahmad T. Why has positive inotropy failed in chronic heart failure? Lessons from prior inotrope trials. Eur J Heart Fail. 2019;21:1064–78.
  14. Indexed atGoogle scholarCross Ref

  15. Stevenson LW. INTERMACS profiles of advanced heart failure: the current picture. J Heart Lung Transplant2009;28:535–41.
  16. Indexed atGoogle scholarCross Ref

  17. Takeda A. Disease management interventions for heart failure. Cochrane Database Syst Rev.2019;1:CD002752.
  18. Indexed atGoogle scholar,

  19. Dorken Gallastegi A. Prospective evaluation of ventricular assist device risk scores’ capacity to predict cardiopulmonary exercise parameters. Interact Cardiovasc Thorac Surg2020;30:223–28.
  20. Indexed atGoogle scholarCross Ref

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