Decentralised Community-Based Hub-Intermediary-Spoke Model for Rapid Cardiac Ultrasound Triage for Early Heart Failure Detection: Findings From the Heart2Miss Initiative
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Overview
Prospective trial evaluates AI-Powered Ultrasound for heart failure detection in diabetes care, suggesting feasibility and efficiency benefits.
Key Points
The study aims to assess the feasibility of an AI-powered triage model for early heart failure detection in patients with diabetes.
Prospective study evaluating 1,000 adults with diabetes across six primary care clinics over seven months.
Training for novice biomedical graduates in performing AI-powered point-of-care ultrasound.
Analysis of ultrasound images through a hub-intermediary-spoke model.
11.1% of participants had Stage B heart failure and 1.0% had Stage C heart failure.
Rapid triage ruled out abnormalities in 77.3%, with a further 12.6% confirmed by intermediary TTE, lowering tertiary referral to 1.0%.
Scan time decreased significantly from 11.0 to 8.3 minutes, and complete capture of scans improved from 88.0% to 92.2%.