Work

Artificial Intelligence-Based Electrocardiographic Analysis Facilitated Diagnosis of Hypertrophic Cardiomyopathy With Successful Treatment Using Mavacamten

Year: 2025

Type: article

Abstract: BACKGROUND: Despite a prevalence of 1 in 500, it is estimated that 85% patients with hypertrophic cardiomyopathy (HCM) may be underdiagnosed or misdiagnosed. There are emerging data on role of artificial intelligence enhanced 12-lead electrocardiogram (AI-ECG) in detection of HCM. CASE SUMMARY: In the current report, we describe the case of a 61-year-old man who was diagnosed with obstructive HCM using AI-ECG, performed as part of an executive physical with subsequent successful initiation and therapeutic response to mavacamten. DISCUSSION: An earlier and accurate diagnosis of HCM is a major unmet need and there are major efforts to enhance the ability a clinician to diagnose HCM as early as possible to be able to institute optimal therapies. TAKE-HOME MESSAGES: The case describes the use of AI-ECG to diagnose HCM appropriately in a 61-year-old symptomatic patient with no previous knowledge of the disease. Following an appropriate diagnosis of HCM, the patient was initiated on the novel cardiac myosin inhibitor mavacamten, with an excellent clinical response.

Source: JACC Case Reports

DOI: 10.1016/j.jaccas.2024.103228

Authors: Milind Y. Desai, Katy Rutkowski, Susan Ospina

Institution: Cleveland Clinic

Language: English

Topic: Cardiomyopathy and Myosin Studies

Subfield: Cardiology and Cardiovascular Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $850