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In Vivo Quantitative Assessment of Myocardial Structure, Function, Perfusion and Viability Using Cardiac Micro-computed Tomography
Published on: February 16, 2016
Association between Cardiovascular Risk Factors and High-Risk Features in Myocardial Perfusion Imaging: A Multicenter
Hamid Khederlou1, Amirali Mohammadi2, Maryam Tajik1
1Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran.
Insights
Myocardial perfusion imaging (MPI) effectively diagnoses coronary artery disease (CAD) in patients with risk factors. Older age, diabetes, hypertension, and dyslipidemia significantly increase the likelihood of abnormal MPI results.
Area of Science:
- Cardiology
- Diagnostic Imaging
- Public Health
Background:
- Myocardial perfusion imaging (MPI) is a key noninvasive diagnostic tool for coronary artery disease (CAD).
- MPI demonstrates acceptable sensitivity and specificity in moderate-risk patients, including those with CAD risk factors.
- Evaluating MPI findings in relation to common CAD risk factors is crucial for patient management.
Purpose of the Study:
- To investigate the association between cardiovascular disease (CAD) risk factors and abnormal myocardial perfusion imaging (MPI) results.
- To determine the predictive value of accumulating CAD risk factors on MPI outcomes.
- To identify specific risk factors independently associated with abnormal MPI findings.
Main Methods:
- A cross-sectional, prospective study involving 4886 patients from April 2020 to March 2023.
- Data collection included anthropometric variables, demographics, CAD risk factors, and MPI findings via questionnaire.
- Statistical analysis assessed the independent association of risk factors with abnormal MPI.
Main Results:
- 44.6% of patients exhibited abnormal MPI results.
- Older age, diabetes mellitus (DM), hypertension, and dyslipidemia were independently associated with abnormal MPI.
- The likelihood of abnormal MPI increased significantly with the number of CAD risk factors, ranging from 3.7% (0-1 risk factor) to 76.2% (8 risk factors).
- Left ventricular dilation and right ventricular prominence were more frequent in patients with these risk factors.
Conclusions:
- CAD risk factors, particularly older age, DM, hypertension, and dyslipidemia, are strongly linked to abnormal MPI findings.
- Patients with multiple CAD risk factors warrant careful evaluation using MPI.
- Meticulous attention to individuals with CAD risk factors is essential during diagnostic assessments like MPI.
Background:
Myocardial perfusion imaging (MPI) is a noninvasive method with acceptable sensitivity and specificity in diagnosing coronary artery disease (CAD) in moderate-risk patients, including those with CAD risk factors.
Methods:
The present cross-sectional, prospective study was conducted on 4886 patients from April 2020 through March 2023 at Chamran and Tehran Heart Center hospitals. A questionnaire regarding anthropometric variables, demographic characteristics, CAD risk factors, and MPI findings was designed.
Results:
Totally, 2179 patients (44.6%) had abnormal MPI. Patients with abnormal MPI were significantly older than those with normal MPI. Older age (OR, 1.64; 95% CI, 1.2 to 1.72; P<0.001), diabetes mellitus (DM) (OR, 1.36; 95% CI, 1.1 to 1.48; P=0.012), hypertension (OR, 1.24; 95% CI, 1.04 to 1.37; P=0.032), and dyslipidemia (OR, 1.54; 95% CI, 1.25 to 1.8; P<0.001) were associated with abnormal MPI independently. Patients with more CAD risk factors were more likely to have abnormal MPI. Thus, in patients without or at most with 1 risk factor and those with 8 CAD risk factors, the likelihood of abnormal MPI was 3.7% and 76.2%, respectively. The frequency of left ventricular dilation and right ventricular prominence was significantly higher in patients with older age (P<0.001 and P=0.043, respectively), dyslipidemia (P<0.001 and P=0.007, respectively), DM (P<0.001 and P<0.001, respectively), and hypertension (P=0.048 and P=0.057, respectively).
Conclusion:
Individuals with CAD risk factors, especially those with older age, DM, hypertension, or dyslipidemia, require meticulous attention during CAD evaluation, particularly via MPI.
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