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Meta-Analysis
. 2012 Oct;17(4):291-8.
doi: 10.1111/j.1542-474X.2012.00538.x. Epub 2012 Aug 13.

Magnetocardiography for the diagnosis of coronary artery disease: a systematic review and meta-analysis

Rajender Agarwal  1 , Abhimanyu Saini, Tareq Alyousef, Craig A Umscheid
Affiliations
Meta-Analysis

Magnetocardiography for the diagnosis of coronary artery disease: a systematic review and meta-analysis

Rajender Agarwal et al. Ann Noninvasive Electrocardiol. 2012 Oct.

Abstract

Background: Coronary artery disease (CAD) has a significant disease burden making early diagnosis and management imperative. Magnetocardiography (MCG) is a relatively new noninvasive technique that allows diagnosis of CAD by recording the magnetic fields generated by the electrical activity of the heart.

Methods: We searched MEDLINE and the Cochrane Central Register of Controlled Trials for prospective studies that evaluated the test characteristics (e.g., sensitivity, specificity, likelihood ratios) of MCG for detection of CAD. Studies were included if they evaluated either patients with stable CAD documented by angiogram or patients presenting initially with acute coronary syndrome and subsequently diagnosed with CAD. The quality of included studies was assessed using an adaptation of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool. We performed meta-analyses of sensitivity, specificity and positive and negative likelihood ratios using Meta-DiSc software.

Results: Screening of titles and abstracts followed by full-text review yielded seven studies that met our inclusion criteria. Meta-analyses yielded a pooled sensitivity of 83% (95% confidence interval [CI] 80% to 86%) and a specificity of 77% (95% CI 73% to 81%). The pooled positive likelihood ratio was 3.92 (95% CI 2.30 to 6.66) and negative likelihood ratio was 0.20 (95% CI 0.12 to 0.35). Significant heterogeneity was present in all meta-analyses.

Conclusions: The pooled test characteristics for MCG are similar to those of existing noninvasive modalities for diagnosing CAD. Our results suggest that MCG is a potential complementary or alternative tool for noninvasive detection of CAD.

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Figures

Figure 1
Figure 1
Flow diagram for selection of included studies.
Figure 2
Figure 2
Study quality assessment.
Figure 3
Figure 3
Pooled sensitivity and specificity.
Figure 4
Figure 4
Pooled positive and negative likelihood ratios.
Figure 5
Figure 5
Summary receiver operating characteristics (SROC) curve.
See this image and copyright information in PMC

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