Fit is It for Cardiovascular Disease Prediction, Prevention and Treatment

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2021

Fit is It for Cardiovascular Disease

Prediction, Prevention and Treatment

Lavie, Carl

Elsevier BV

Tieteelliset aikakauslehtiartikkelit

© 2020 Canadian Cardiovascular Society

CC BY-NC-ND https://creativecommons.org/licenses/by-nc-nd/4.0/

http://dx.doi.org/10.1016/j.cjca.2020.05.007

https://erepo.uef.fi/handle/123456789/24906

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Fit is It for Cardiovascular Disease Prediction, Prevention and Treatment

Carl J. Lavie, MD, Fabian Sanchis-Gomar, MD, PhD, Jari A. Laukkanen, MD, PhD

PII: S0828-282X(20)30452-9

DOI: https://doi.org/10.1016/j.cjca.2020.05.007 Reference: CJCA 3759

To appear in: Canadian Journal of Cardiology Received Date: 24 April 2020

Revised Date: 6 May 2020 Accepted Date: 6 May 2020

Please cite this article as: Lavie CJ, Sanchis-Gomar F, Laukkanen JA, Fit is It for Cardiovascular Disease Prediction, Prevention and Treatment, Canadian Journal of Cardiology (2020), doi: https://

doi.org/10.1016/j.cjca.2020.05.007.

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

© 2020 Published by Elsevier Inc. on behalf of the Canadian Cardiovascular Society.

1 Invited Editorial Canadian Journal of Cardiology

Title:

Fit is It for Cardiovascular Disease Prediction, Prevention and Treatment

Authors:

Carl J. Lavie, MD,^a Fabian Sanchis-Gomar, MD, PhD,^b,c Jari A. Laukkanen, MD, PhD,^d,e Affiliations:

aJohn Ochsner Heart and Vascular Institute, Ochsner Clinical School - The University of Queensland School of Medicine, New Orleans, LA, USA

bDepartment of Physiology, Faculty of Medicine, University of Valencia and INCLIVA Biomedical Research Institute, Valencia, Spain

cDivision of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, USA

dInstitute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland

eFaculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland

Type of article: Editorial

Keywords: Cardiorespiratory Fitness; Cardiovascular Diseases; Prevention; Atherosclerosis;

Guidelines; Algorithm.

Corresponding Author:

Dr. Carl J. Lavie

Cardiology, John Ochsner Heart and Vascular Institute New Orleans, LA 70121, USA

E-mail: clavie@ochsner.org

Considerable evidence supports the benefits of physical activity, exercise training and fitness, including muscular fitness but, especially, cardiorespiratory fitness, for the primary and secondary prevention of cardiovascular diseases.^1-9 Substantial evidence has shown that patients with significant cardiovascular risk factors, such as hypertension, diabetes, obesity, and dyslipidemia, but with high cardiorespiratory fitness, have a better prognosis than do patients without these risk factors but with low cardiorespiratory fitness, showing that preserved fitness is one of the strongest risk factors for cardiovascular disease and survival.^1-3 Maintaining or improving fitness over time is associated with especially good survival.^10-12

Reductions in heart disease burden have been achieved through extensive population-based prevention programs. There have been many beneficial trends in cardiovascular illness, mainly due to focused prevention and treatment in middle-aged populations. Cardiovascular risk assessment is a crucial tool for cardiovascular disease prevention, which includes identifying individuals at high cardiovascular risk and targeting them for lifestyle and pharmacological interventions. Risk assessment tools by the American College of Cardiology/American Heart Association (ACC/AHA) Task Force and the European Society of Cardiology (ESC) are the main cardiovascular illness prevention guidelines that are impacting clinical practice.^{13, 14} These guideline bodies recommend the Pooled Cohort Equations and the Systematic Coronary Risk Evaluation algorithm, respectively, for 10-year cardiovascular disease risk estimation. The Pooled Cohort Equations employed by ACC/AHA guidelines are based on any atherosclerotic cardiovascular events, whereas the Systematic Coronary Risk Evaluation is based on fatal cardiovascular disorders outcomes. Other available cardiovascular risk algorithms include the Framingham Risk Score and the Reynolds Risk Score.

These risk scores may vary in their combination of risk factors and cardiovascular

3 using different cardiovascular risk-estimating algorithms may differ considerably, especially among older individuals.¹⁵Additionally, subclinical coronary artery disease is among the most common causes of sudden cardiac arrest and sudden cardiac death in apparently healthy individuals aged 35 years and older.¹⁶ Therefore, identifying individuals at higher cardiovascular disease risk is imperative for preventing sudden disease due to subclinical ischemic heart disease.¹⁷ Accurate cardiovascular disease risk score calculators’ algorithms represent essential tools for this purpose and would be extremely useful to reorient individuals at higher cardiovascular risk therapeutically. To enhance clinical decision making in prevention, initial outcome risk prediction tools need to be improved, and appropriate population-wide treatment thresholds should be set. Without accurate individual risk predictions, clinicians should not readily prescribe medications that could potentially be harmful to some patients. This relates especially to primary prevention as compared to drug use in secondary prevention in high-risk groups.

It is essential to have a readily available assessment for fitness assessment, which is the accurate indicator of the ability to transport oxygen from the lung to the muscles to allow for physical exercise. Cardiorespiratory fitness has relatively good reliability and validity, and it is one of the strongest predictors for death from heart disorders and other causes. However, it is not yet well known to which extent the incremental prognostic information offered by the assessment of cardiorespiratory fitness in risk stratification beyond that of conventional risk factors would prompt interventions and ultimately reduce cardiovascular disease-related events. Some evidence also suggests that physical fitness could provide additional prognostic value beyond established risk factors in predicting fatal vascular outcomes. In future clinical settings, if/when exercise testing with cardiorespiratory fitness assessment, or physical fitness estimation by validated non-exercise algorithms, will be as readily available as prevailing risk factor determination, the inclusion of physical fitness in classic risk algorithms might offer the

classification of an individuals' risk and optimize focused prevention. A recent UK Biobank study shows that cardiorespiratory fitness can provide incremental prognostic value in all- cause mortality risk prediction on top of age, sex, systolic blood pressure, cholesterol, and smoking, which are established components of many cardiovascular risk scores,¹⁸ as has recently been reviewed.¹⁹

Results and interpretation from prediction analyses are dependent on the outcomes and variables that are included in the models. In the paper by Fardman et al.²⁰ published in this issue of the Canadian Journal of Cardiology, the authors evaluated whether incorporating the cardiorespiratory fitness to the atherosclerotic cardiovascular disease risk model could improve its prediction accuracy in middle-aged asymptomatic healthy adults (median age of 49 years). To this end, they calculated the 10-year atherosclerotic cardiovascular risk score using a Pooled Cohort Equations risk model and also evaluated the exercise capacity of 15,445 individuals, and followed them up during a median of 8 years. Participants were dichotomized into two baseline risk groups: low risk (<7.5%) and intermediate/high risk (≥7.5). The primary outcome was a composite of all-cause mortality, non-fatal acute coronary syndrome and stroke, and 1,362 (9%) individuals reached this endpoint. To evaluate the role of fitness in predicting the cardiovascular risk, the authors recalculated this risk using the continuous net reclassification improvement approach in which cardiorespiratory fitness was added. Interestingly, they showed a statistically significant improvement of 11.4% (95%CI 8–

14.6%, p<0.001) when the continuous net reclassification improvement approach was used, i.e., when both fitness and atherosclerotic cardiovascular disease risk model were combined.

The authors implemented a category-free net reclassification improvement, as the definition of a specific threshold for performing category net reclassification improvement may hinder comparisons of the results with others who have used different categories in their risk

5 factors, representing a valuable marker with potential clinical utility. The disparity between the observations from studies using risk prediction metrics, such as net reclassification improvement, can be attributed to the baseline study population and risk factor assessments.

They also suggested that the inclusion of cardiorespiratory fitness to the pooled cohort atherosclerotic cardiovascular risk could increase the accuracy of the model. On the other hand, the original atherosclerotic cardiovascular disease score that contains cardiovascular mortality measured non-cancer related all-cause mortality.

The bottom line is that “Fit is It” for cardiovascular disease prediction, prevention and treatment; this means that increased fitness is known to be associated with prevention of cardiovascular disease and improving prognosis with known cardiovascular disease. In this report from Fardman et al.,²⁰ the authors extend this evidence for fitness adding considerably to cardiovascular disease prediction. Indeed, more considerable efforts are needed to increase the utilization of physical fitness as a vital sign, as we have recently suggested²¹ and using physical fitness will add to cardiovascular risk assessment;^18-21 the authors of the current study should be applauded for adding to these efforts. Potentially, later assessments could determine if adding muscular strength level to the equation adds further to cardiovascular events risk assessment. Additionally, more considerable efforts are needed to increase physical activity, exercise training and fitness, especially cardiorespiratory fitness but also muscular fitness with resistance exercise training,^22-26 as these efforts will help tremendously in the primary and secondary prevention of cardiovascular events.

Funding Sources

There are no funding sources to declare.

Disclosures

The authors declare that no conflict of interest exists.

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