VizTM HCM

Product catalog summary

Overview: The document is a brochure for Viz RECRUIT for PE-TRACT, focusing on the Viz HCM application designed to streamline the patient journey for those with Hypertrophic Cardiomyopathy (HCM). It highlights the importance of early detection and diagnosis of HCM, a potentially fatal condition that is often missed.

Key Features:

AI-Driven Detection: The Viz HCM app uses real-time AI analysis of 12-lead ECGs to flag and triage suspected HCM cases, facilitating quick referral to specialists.
High Prevalence and Low Diagnosis Rate: Approximately 1 million people in the U.S. are affected by HCM, with only a 20% diagnosis rate and an average of 5 years to diagnosis.
Robust AI Development: The AI was trained on over 830,000 ECG exams from a diverse global dataset, ensuring it accounts for racial and ethnic differences in ECG wave morphologies.
Validation and Performance: The AI's performance is validated against echocardiography and cardiac MRIs, with high sensitivity and specificity across different racial groups.

Data and Performance Metrics:

Asian: AUC 0.987, Sensitivity 73.3%, Specificity 98.9%
Black: AUC 0.981, Sensitivity 64.5%, Specificity 99.2%
Hispanic: AUC 1.000, Sensitivity 100%, Specificity 98.2%
White: AUC 0.972, Sensitivity 66.8%, Specificity 99.1%

Conclusion: The Viz HCM app is positioned as a critical tool for improving the diagnosis and management of HCM, with a focus on enhancing care coordination within health systems. For more information, contact [email protected].

Catalog excerpts

Streamline the HCM patient journey Hypertrophic cardiomyopathy: Potentially fatal, yet commonly missed 1 million people affected in the U.S1,2 End-to-end approach for detecting suspected HCM and directing patients Viz HCM delivers real-time AI analysis of 12-lead ECGs to flag and triage suspected cases to HCM specialists for diagnostic workup, all from the Viz HCM mobile app. Example views of Viz HCM mobile application Flag Suspected HCM Review patients identified by AI as having signals of HCM. Follow Up Direct patients to the HCM specialist for additional workup. Diagnose View echo images and reports to diagnose HCM. Given the high prevalence of patients with suspected HCM who remain undiagnosed, flagging and connecting them quickly to the right providers is critical to improve health outcomes. Matthew Martinez, MD Director of Sports Cardiology and HCM, Atlantic Health System PRM XXXX US Rev 01 1 Hypertrophic Cardiomyopathy Association. (2021, June). HCM Prevalence. 2 Butzner M et al 2021. VizJRECRUIT PE-TRACT Brochure Am Cardiol for 3 The Patient's Voice | HCM: Understanding the Patient Journey From Diagnosis to Treatment (2022) Learn More:

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Streamline the HCM patient journey Ensuring AI algorithm robustness Viz HCM AI was trained using ECGs from more than 300,000 individuals worldwide. Diverse Dataset Gold Standard Validation 830k+ ECG exams Covering non-obstructive and obstructive HCM Sourced from global locations Included racial & ethnic differences seen in PQRST wave morphologies Echocardiography Cardiac MRIs Asian Black Hispanic *AUC = Area under the curve for detecting suspected HCM Source: Algorithm Performance Data from Mass General Brigham Improving care coordination at health systems Learn more about how Viz HCM can advance...

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