OBJECTIVE To evalu ate the role of resting magnetocardiography in identifying seve re coronary artery stenosis in patients with suspected coronary artery disease.METHODS A total of 513 patients with angina symptoms we...OBJECTIVE To evalu ate the role of resting magnetocardiography in identifying seve re coronary artery stenosis in patients with suspected coronary artery disease.METHODS A total of 513 patients with angina symptoms were included and divided into two groups based on the extent of coronary artery disease determined by angiography:the non-severe coronary stenusis group(<70% stenosis) and the severe coronary stenosis group(≥70% stenosis).The diagnostic model was constructed using magnetic field map(MFM) parameters,either individually or in combination with clinical indicators.The performance of the models was evaluated using receiver operating characteristic curves,accuracy,sensitivity,specificity,positive predictive value(PPV) and ne gative predictive value(NPV).Calibration plots and decision curve analysis were performed to investigate the clinical utility and performance of the models,respectively.RESULTS In the severe coronary stenosis group,QR_MCTDd,S_MDp,and TT_(MA)C_(50) were significantly higher than those in the non-severe coronary stenosis group(10,46±10.66 vs,5.11±6.07,P <0.001;7.2±8.64 vs.4.68±6.95,P=0.003;0.32±57.29 vs.0.26±57.29,P <0.001).While,QR_MV_(amp),R_(MA),and T_(MA) in the severe coronary stenosis group were lower(0.23±0.16 vs.0.28±0.16,P<0.001;55.06±48.68 vs.59.24±53.01,P<0.001;51.67±39.32 vs. 60.45±51.33,P <0.001).Seven MFM parameters were integrated into the model,resulting in an area under the curve of 0.810(95% CI:0.765-0.855).The sensitivity,specificity,PPV,NPV,and accurecy were 71.7%,80.4%,93.3%,42.8 %,and 73.5%;respectevely.The combined model exhibited an area under the curve of 0.845(95% CI:0.798-0.892).The sensitivity,specificity,PPV,NPV,and accuracy were 84.3%,73.8%,92.6%,54.6%,and 82.1%;respectively.Calibration curves demonstrate d excellent agreement between the nomogram prediction and actual observation.The decision curve analysis showed that the c ombine d model provided greater net benefit compared to the magnetocardingraphy model.CONCLUSIONS The novel quantitative MFM parameters,whether used individually or in combination with clinical indicators,have been shown to effectively pre dict the risk of severe coronary stenosis in patients presenting with angina-like symptoms.Magnetocardiography,an emerging non-invasive diagnostic tool,warrants further exploration for its potential in diagnosing coronary heart disease.展开更多
基金supported by the National Key Research and Development Program (No.2022YFC2407001)。
文摘OBJECTIVE To evalu ate the role of resting magnetocardiography in identifying seve re coronary artery stenosis in patients with suspected coronary artery disease.METHODS A total of 513 patients with angina symptoms were included and divided into two groups based on the extent of coronary artery disease determined by angiography:the non-severe coronary stenusis group(<70% stenosis) and the severe coronary stenosis group(≥70% stenosis).The diagnostic model was constructed using magnetic field map(MFM) parameters,either individually or in combination with clinical indicators.The performance of the models was evaluated using receiver operating characteristic curves,accuracy,sensitivity,specificity,positive predictive value(PPV) and ne gative predictive value(NPV).Calibration plots and decision curve analysis were performed to investigate the clinical utility and performance of the models,respectively.RESULTS In the severe coronary stenosis group,QR_MCTDd,S_MDp,and TT_(MA)C_(50) were significantly higher than those in the non-severe coronary stenosis group(10,46±10.66 vs,5.11±6.07,P <0.001;7.2±8.64 vs.4.68±6.95,P=0.003;0.32±57.29 vs.0.26±57.29,P <0.001).While,QR_MV_(amp),R_(MA),and T_(MA) in the severe coronary stenosis group were lower(0.23±0.16 vs.0.28±0.16,P<0.001;55.06±48.68 vs.59.24±53.01,P<0.001;51.67±39.32 vs. 60.45±51.33,P <0.001).Seven MFM parameters were integrated into the model,resulting in an area under the curve of 0.810(95% CI:0.765-0.855).The sensitivity,specificity,PPV,NPV,and accurecy were 71.7%,80.4%,93.3%,42.8 %,and 73.5%;respectevely.The combined model exhibited an area under the curve of 0.845(95% CI:0.798-0.892).The sensitivity,specificity,PPV,NPV,and accuracy were 84.3%,73.8%,92.6%,54.6%,and 82.1%;respectively.Calibration curves demonstrate d excellent agreement between the nomogram prediction and actual observation.The decision curve analysis showed that the c ombine d model provided greater net benefit compared to the magnetocardingraphy model.CONCLUSIONS The novel quantitative MFM parameters,whether used individually or in combination with clinical indicators,have been shown to effectively pre dict the risk of severe coronary stenosis in patients presenting with angina-like symptoms.Magnetocardiography,an emerging non-invasive diagnostic tool,warrants further exploration for its potential in diagnosing coronary heart disease.