Rapid screening for acute rheumatic fever using machine learning analysis of host tissue reactive antibodies.

ABSTRACT: Acute Rheumatic Fever and Rheumatic Heart Disease (ARF/RHD) affect over 45 million people globally. ARF/RHD are autoimmune complications following group A streptococcal infections. Current diagnosis of ARF requires thorough medical examination, echocardiography and laboratory tests that are unavailable in most primary care settings where patients with ARF typically first present. This pilot study was conducted to determine whether machine learning-based predictive models could be used to stratify host tissue protein reactive antibodies associated with ARF, that could be incorporated into a lateral flow point-of-care (POC) platform for ARF screening. We investigated serum antibody levels against four host tissue proteins (cardiac myosin, laminin, keratin, and tropomyosin) known to increase

SUBMITTER: Vo B 

PROVIDER: S-EPMC12639040 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature