Prognostic Value of Echocardiographic Parameters Based on Machine Learning Approach

Launched by PR. NICOLAS GIRERD · Mar 15, 2023

Keywords

ClinConnect Summary

This clinical trial is exploring how a machine learning approach can help predict the outcomes for patients with transthyretin cardiac amyloidosis, a condition that can lead to heart failure. Currently, this heart disease is diagnosed using non-invasive methods like blood tests and imaging techniques, but it is still incurable and often leads to repeated hospital stays and serious health issues. The researchers want to see if using advanced technology can improve our understanding of how the disease progresses and potentially help in managing it better.

If you or a loved one is at least 18 years old and has been suspected of having transthyretin cardiac amyloidosis, you may be eligible to participate in this study. Participants will undergo tests that include echocardiograms (ultrasound of the heart), which allow doctors to gather important information about heart function. However, some people may not qualify if there isn't enough information to confirm the diagnosis or if their echocardiogram data isn't clear. This trial is currently looking for participants, and being involved could contribute to finding better ways to understand and treat this challenging condition.

Gender

ALL

Eligibility criteria

• Inclusion Criteria:
• • Patients with suspicion of transthyretin cardiac amyloidosis
• • Age ≥18 years
• Exclusion Criteria:
• • Lack of data to confirm or overturn the transthyretin amyloidosis diagnostic
• • Echocardiographic data not allowing deep analysis (technical default, bad echogenicity of the patient)
• • Final diagnostic of AL or AA amyloidosis