Original Research
Impact of Patient Visualization of Cardiovascular Images on Modification of Cardiovascular Risk Factors: Systematic Review and Meta-Analysis

https://doi.org/10.1016/j.jcmg.2023.03.007Get rights and content

Abstract

Background

It is unclear whether detection and patient visualization of cardiovascular (CV) images using computed tomography to assess coronary artery calcium or carotid ultrasound (CU) to identify plaque and intima-medial thickness merely prompts prescription of lipid-lowering therapy or whether it motivates lifestyle change among patients.

Objectives

This systematic review and meta-analysis sought to investigate whether patient visualization of CV images (computed tomography or CU) has a beneficial impact on improving overall absolute CV risk as well as lipid and nonlipid CV risk factors in asymptomatic individuals.

Methods

The key words “CV imaging,” “CV risk,” “asymptomatic persons,” “no known or diagnosed CV disease,” and “atherosclerotic plaque” were searched in PubMed, Cochrane, and Embase in November 2021. Randomized trials that assessed the role of CV imaging in reducing CV risk in asymptomatic persons with no known CV disease were eligible for study inclusion. The primary outcome was a change in 10-year Framingham risk score from the trial commencement to the end of the follow-up following patient visualization of CV images.

Results

Six randomized controlled trials (7,083 participants) were included; 4 studies used coronary artery calcium and 2 used CU to detect subclinical atherosclerosis. All studies used image visualization in the intervention group to communicate CV risk. Imaging-guidance was associated with a 0.91% improvement in 10-year Framingham risk score (95% CI: 0.24%-1.58%; P = 0.01). Significant reductions in low-density-lipoprotein, total cholesterol, and systolic blood pressure were observed (all P < 0.05).

Conclusions

Patient visualization of CV imaging is associated with overall CV risk reduction and improvement of individual risk factors: cholesterol and systolic blood pressure.

Section snippets

Study design

This systematic review was undertaken in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement.12 The review was registered with PROSPERO (ID 288686) in November 2021.

Published Reports search

PubMed, Cochrane, and Embase electronic databases using Ovid were searched from inception to November 2021 for randomized controlled trials that assessed the role of cardiovascular (CV) imaging and patient visualization of atherosclerotic plaque on reducing CV risk in

Search results

We identified 4,714 records in the initial search. After removal of duplicates (n = 557), 4,157 were screened for suitability by comparing titles and abstracts with selection criteria. We retrieved the full text for 19 studies and excluded 10, due to study design (n = 8) or incomplete data (n = 2). Nine full-text papers were reviewed for data extraction and 4 authors were contacted to provide patient-level data because of incomplete CV risk information. One author14 provided patient-level data

Discussion

To the best of our knowledge, this study is the first meta-analysis to determine whether patient visualization of CV images improves the estimated 10-year FRS CV risk13 and individual CV risk factors. There was an almost 1% reduction in 10-year FRS observed in those individuals who were provided with pictorial images of their CAC scan or CU and a personalized risk discussion, compared with those who were not provided this information. This meta-analysis was only able to evaluate CV risk

Conclusions

This study has demonstrated that patient visualization of CV images within a CV risk discussion is an effective tool in educating and motivating individuals to engage in risk modification. CV imaging has a beneficial effect on improving both lipid and nonlipid CV risk factors, as well as overall CV risk score. Evidence supporting the use of CV imaging for improving patient understanding and adherence may help to justify the wider use of CAC scanning at a population-based level.

COMPETENCY IN

Funding Support and Author Disclosures

Supported in part by a grant from the Ernst Heine Foundation, Sydney, Australia. The authors have reported that they have no relationships relevant to the contents of this paper to disclose.

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    Harvey Hecht, MD, served as Guest Editor for this paper.

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