Magnetocardiography scoring system to predict the presence of obstructive coronary artery disease

Issue title: Selected papers from the Neubrandenburg Conference, 8-9 June, 2018

Article type: Research Article

Authors: Shin, Eun-Seok^{a; *} | Park, Seung Gu^b | Saleh, Ahmed^c | Lam, Yat-Yin^d | Bhak, Jong^{b; e} | Jung, Friedrich^f | Morita, Sumio^g | Brachmann, Johannes^c

Affiliations: [a] Division of Cardiology, Ulsan Medical Center, Ulsan Hospital, Ulsan, Korea | [b] Korean Genomics Industrialization and Commercialization Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan, Korea | [c] 2nd Medical Department, Coburg Hospital, Coburg, Germany | [d] Prince of Wales Hospital, Chinese University of Hong Kong, Hong Kong | [e] Department of Biomedical Engineering, School of Life Sciences, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Korea | [f] Institute of Biomaterial Science and Berlin-Brandenburg, Center for Regenerative Therapies (BCRT), Helmholtz Zentrum Geesthacht, Teltow, Germany | [g] Department of Cardiology, Charité Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Berlin, Germany

Correspondence: [*] Corresponding author: Eun-Seok Shin, MD, PhD, Department of Cardiology, Ulsan Medical Center, Ulsan Hospital, 13, Wolpyeong-ro 171beon-gil, Nam-gu, Ulsan, 44686, South Korea. Tel.: +82 52 250 5020; Fax: +82 52 259 5117; E-mail: sesim1989@gmail.com.

Abstract: BACKGROUND: Magnetocardiography (MCG) has been proposed as a non-invasive and functional technique with high accuracy for diagnosis of myocardial ischemia. OBJECTIVE: This study sought to develop a novel scoring system of MCG for predicting the presence of significant obstructive coronary artery disease (CAD). METHODS: In a training set of 108 subjects, predictors of ≥70% stenosis in at least one major coronary vessel were prospectively identified from MCG variables. The final model was then retrospectively validated in a separate set of 45 subjects. RESULTS: In the multivariable logistic regression, among those in the training set, elevated scores were predictive of ≥70% stenosis in all subjects (OR: 40.85; 95% CI: 6.28–265.90; p < 0.001). In the validation set, the score had an area under the receiver-operating characteristic curve of 0.91 (p < 0.001) for ≥70% stenosis. At an optimal cutoff, the score had 89% sensitivity, 77% specificity, 74% positive predictive value (PPV), 91% negative predictive value (NPV), and 82% accuracy for ≥70% stenosis. Partitioning the score into three levels of predicted risk, 91% of subjects could be identified or excluding CAD (81% PPV and 84% NPV). CONCLUSION: We described an MCG score with high accuracy for predicting the presence of anatomically significant CAD.

Keywords: Magnetocardiography, scoring, coronary artery disease, diagnosis

DOI: 10.3233/CH-189301

Journal: Clinical Hemorheology and Microcirculation, vol. 70, no. 4, pp. 365-373, 2018