Use of Steroid Profiling Combined With Machine Learning for Identification and Subtype Classification in Primary Aldosteronism

Key Points Question Does steroid profiling combined with machine learning offer a potential 1-step strategy to facilitate diagnosis and subtype classification for treatment stratification of patients with primary aldosteronism? Findings This diagnostic study involving patients tested for primary aldosteronism found that those with unilateral adenomas harboring pathogenic KCNJ5 sequence variants showed the most clinical benefit from surgical intervention and could be effectively identified at a single screening step using machine-learning combinatorial marker profiles of 7 steroids. Meaning The outlined strategy offers a potential approach to improve diagnosis of primary aldosteronism and facilitate more efficient and effective stratification of patients for surgical intervention.