Assessing the diagnostic accuracy of cardisiography in the diagnosis of coronary heart disease: CSG-DR study (A pilot study)

Background: Early and accurate detection of coronary artery disease (CAD) remains a challenge in primary care, particularly in low- and middle-income countries where access to advanced diagnostic imaging is limited. A resting electrocardiogram (ECG) is widely available but has low sensitivity for detecting ischemia. Cardisiography (CSG), an artificial intelligence-enhanced vectorcardiography technique, offers a promising non-invasive alternative. Methods: This single-center, prospective, double-blinded pilot study enrolled 104 patients aged 40 and above with suspected CAD referred for coronary computerized tomography angiography (CCTA). All participants underwent ECG, CSG, and CCTA as the reference standard. Diagnostic accuracy was assessed using the CAD-RADS classification. Results: CCTA identified coronary lesions classified as CAD-RADS 1-3 in 29 patients (12, 11, and 6, respectively). CSG achieved an overall sensitivity of 96.5% (28/29), compared with 6.9% (2/29) for ECG. Sensitivity was 100% for CAD-RADS 1 and 3, and 91% for CAD-RADS 2. Diagnostic accuracy metrics are reported with 95% confidence intervals. Conclusion: In this pilot referral cohort, CSG demonstrated higher sensitivity than resting ECG for detecting coronary plaque. These preliminary findings suggest CSG may serve as a triage tool before CCTA or cardiology referral. Larger, multicenter studies are needed to validate its role and determine clinical utility. Clinical Trial Registration: https://conabios.gob.do/reglamento, identifier 034-2023.