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| Name | Class |
|---|---|
| Second Affiliated Hospital, School of Medicine, Zhejiang University | OTHER |
This observational study aims to develop and validate a single-feature artificial intelligence algorithm based on data collected via a wearable ECG patch in patients with heart failure (HF).
The main question: Does the algorithm, using synchronized ECG and accelerometer signals from the patch, achieve accurate detection of heart sounds (S1, S2, and in some patients S3, S4) compared to the Eko CORE 500 digital stethoscope in patients with acute exacerbation of HF? It aims to answer: Participants with confirmed HF (NYHA class II-IV) will first undergo a 2-minute session of simultaneous ECG patch and digital stethoscope recordings, followed by standard 12-lead ECG, and then a repeated 2-minute heart sound recording session. Data will be used for algorithm training and validation. The primary endpoint is the sensitivity and specificity of heart sound detection using ECG patch against the Eko CORE 500 digital stethoscope.
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| Measure | Description | Time Frame |
|---|---|---|
| Heart sounds include S1 and S2 | In some patients, S3 and S4 are also present. | 10-15 minutes |
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Inclusion Criteria:
Exclusion Criteria:
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Adult patients diagnosed with heart failure (NYHA classification II~IV)
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Second Affiliated Hospital, School of Medicine, Zhejiang University | Hangzhou | Zhejiang | China |
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