Utility of a Novel Point-of-Care Test in Detecting Coronary Artery Disease Following Negative Nuclear Testing: A Case Series

Abstract Background Coronary artery disease (CAD) often presents diagnostic challenges, especially in patients with atypical chest pain that persists despite negative non-invasive testing. For instance, nuclear stress testing, although widely used, may yield false-negative results, particularly in cases of balanced ischemia. Accurate diagnostics are essential to avoid delays in diagnosis and treatment, particularly in presence of negative nuclear testing. Case Summary We present five cases of intermediate to high-risk patients with ongoing symptoms (chest pressure/discomfort/pain, nausea, shortness of breath, exertional fatigue) and negative nuclear stress tests, who were ultimately diagnosed with significant CAD via invasive coronary angiography. In each case, CorVista CAD (POC-CAD), a novel point-of-care test (POC-CAD) that analyzes electrical and hemodynamic signals using machine learning, was contributory in raising the probability of disease, prompting invasive evaluation via coronary angiography and guiding appropriate management strategies. Discussion This case series demonstrates the utility of POC-CAD as a non-invasive tool in the diagnostic pathway for patients with ongoing symptoms despite negative nuclear stress testing. The findings highlight limitations of nuclear stress testing, particularly its reduced sensitivity in multivessel disease. POC-CAD may help identify high-risk patients who would otherwise be missed, facilitating timely intervention. Integration of novel diagnostics like POC-CAD into multimodal assessment strategies could improve accuracy and reduce diagnostic delays in CAD.