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Coronary atherosclerotic heart disease (CHD) and Coronary Microvascular Disease (CMVD), as the primary etiologies of myocardial ischemia, have garnered increasing clinical attention due to their high prevalence and severe prognostic implications.
Currently, the primary method for detecting myocardial ischemia is Emission Computed Tomography (ECT). However, it suffers from limitations such as low spatial resolution and radiation exposure risks.magnetocardiography(MCG) is a non-invasive, contactless medical imaging device that maps localized magnetic signals generated by cardiac electrical activity.The magnetocardiography (MCG) system constructs cardiac magnetic field images by recording biomagnetic signals via a multi-channel sensor array positioned above the thoracic region.MCGcan capture the spatial magnetic field changes of ischemic myocardial cells, and carry out early warning, early diagnosis and positioning detection of myocardial ischemia.
This study is a prospective, multicenter, controlled trial. The study will enroll adult patients presenting with myocardial ischemia symptoms suspected of having coronary heart disease (CHD) or coronary microvascular disease (CMVD), who are scheduled to undergo ECT examination.and a domestically manufactured "ultra-high sensitivity" cardiomagnetic detection device will be used to collect cardiac magnetic images. The ECT examination will be completed within one week. A consistency analysis will be conducted between the cardiac magnetic results and the ECT results to evaluate the early diagnostic efficacy of cardiac magnetic detection for myocardial ischemia. Subgroup analyses will also be performed based on resting and stress conditions.
Primary study endpoints:Diagnostic Performance of MCG in Detecting Myocardial Ischemia: Positive Predictive Value, Specificity, and Sensitivity.
Secondary study endpoint:Concordance and Discrepancies Between MCG and ECT in Diagnosing Myocardial Ischemia.
Full description
3.1.2 Preparation before magnetic examination Before undergoing magnetic electrocardiogram, the patient's basic information was asked and checked, the past history, alcohol and tobacco status, and the current medical history (the onset time, inducement, symptom characteristics, duration, etc. of chest pain) were recorded, and the subject's blood pressure, height, and weight were measured.
3.1.3 Magnetocardiography and ECT examination MCG images were collected using a domestic "ultra-high-sensitive" MCG detection device, and ECG examinations were performed 10 minutes before and after. ECT examination was completed within 1 week.
3.1.4 Data Entry The subject's diagnostic results, myocardial damage markers, heart failure indicators, electrocardiogram, echocardiography, coronary CTA/angiography, ECT and other laboratory test results were recorded and entered into EDC.
3.2 Data Analysis The consistency of Magnetocardiographic results and ECT results was analyzed to evaluate the effectiveness of magnetocardiographic testing in early diagnosis of myocardial ischemia.
3.3 Sample size Estimation In this project sample size calculation was performed to ensure the statistical reliability of the study. By considering factors such as the expected effect size and significance level, an appropriate sample size was determined. This ensures sufficient support for testing the study hypothesis, guarantees scientifically credible results, enhances study reproducibility, and boosts data analysis robustness, thereby making the study conclusions more convincing and reliable.
For testing the non - inferiority of cardiomagnetic evaluation of myocardial ischemia compared to ECT, the sample size estimation used the method for comparing paired two - sample rates in a non - inferiority design and was calculated as follows:
n=(Zα+Zβ)2×(p1(1-p1)+p2(1-p2))/(p1-p2-Δ)2 In the formula: Zα is the critical value of the standard normal distribution; Zβ is the critical value of the standard normal distribution corresponding to the power; P1 and P2 represent the positive rates of the control group and the intervention group, respectively; Δ:non-inferiority margin; α:significance level; β:power of the test. The preliminary experimental results indicated a 77% positive rate for cardiomagnetic detection and 71% for ECT, with α=0.05 (one - sided), β=0.2 (power 80%), and Δ=0.05. We calculated the minimum sample size to be 196 cases, with a total sample size of 196 cases. Considering a dropout rate of 10%, the final determined sample size was 218 cases.
3.4 Statistical Methods Unless otherwise stated, the following general principles will be used for statistical analysis of the study data.
For categorical variables, statistical descriptions will be provided as the number and percentage of participants in each category. For continuous variables, the mean, standard deviation, median, Q1,Q3 and extremes will be listed. Diagnostic efficiency will be evaluated using sensitivity, specificity, AUC, recall, and F1 score for discrimination. Calibration will be assessed via calibration curves and the Hosmer-Lemeshow (H-L) test. Subgroup analyses will be conducted for rest ECT and stress ECT groups to compare diagnostic efficiency and consistency. The Pearson correlation coefficient will assess the linear relationship between cardiomagnetic scores and ECT ischemic areas, with the correlation coefficient (r) and significance level (p value) reported. The Kappa coefficient will evaluate the consistency of cardiomagnetic detection with rest and stress ECT in diagnosing myocardial ischemia, with the consistency level reported.
All statistical tests will use a significance level of 0.05.
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Jun Xiao PhD
Data sourced from clinicaltrials.gov
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