The goal of this observational study is to develop and evaluate the efficacy of a foundational model that integrates multimodal medical data to improve the diagnosis and prediction of cardiovascular diseases in patients aged 18 and older, including those with various heart conditions such as coronary artery disease, heart failure, and arrhythmias. The main questions it aims to answer are:
Can a multimodal data-based diagnostic model match or exceed the accuracy of traditional gold-standard methods like coronary angiography, MRI, and echocardiography? Does integrating different types of data (ECG, imaging, biochemical tests) improve diagnostic accuracy and prediction of cardiovascular disease outcomes? Researchers will compare the foundational model with traditional diagnostic methods to see if the model offers better sensitivity, specificity, and prediction accuracy across different heart disease types.
Participants will:
Provide data from past medical records, including ECG, echocardiography, cardiac MRI, and biochemical tests.
Undergo further data collection if necessary, in line with standard clinical procedures for cardiovascular disease management.
Eligibility
Sex
ALL
Min age
18 Years
Max age
—
Healthy volunteers
Accepted
Inclusion Criteria:
Age ≥ 18 years: Patients who are 18 years of age or older. Time period: Patients who were treated or diagnosed between January 1, 2009, and December 31, 2023.
Complete medical records: Patients with comprehensive medical records, including ECG, echocardiography, MRI, CTA, nuclear imaging (SPECT/PET), and biochemical test results.
Cardiovascular diseases: Patients with diagnosed cardiovascular conditions, such as coronary artery disease (CAD), heart failure, arrhythmias, and valvular heart disease (VHD), as well as healthy individuals for comparison.
Willingness to participate: Patients who are able to provide informed consent or their legal representatives.
Exclusion Criteria:
Participation in other clinical trials: Patients who are currently participating in other clinical trials that may affect the study outcomes.
Incomplete medical records: Patients whose medical records lack essential data, such as ECG, echocardiography, MRI, CTA, nuclear imaging (SPECT/PET), or biochemical test results.
Data quality issues: Patients with records that have significant errors, inconsistencies, or incomplete data that cannot be reasonably corrected.
Ethical or legal concerns: Patients whose data cannot be used due to a lack of necessary consent or legal/ethical restrictions.
Primary outcome measure(s)
Area under ROC — 1 month In this study, the area under the receiver operating characteristic curve (AUROC) will be used as a key performance metric to evaluate the diagnostic accuracy of the foundational model for cardiovascular diseases. The AUROC measures the model's ability to distinguish between patients with and without a specific condition, such as coronary artery disease, heart failure, or arrhythmias.
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
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