Objective: The clinical practice guideline for primary aldosteronism (PA) places a high value on confirmatory tests to sparing patients with false-positive results in case detection from undergoing adrenal venous sampling (AVS). However, it is unclear whether multiple types of confirmatory tests are more useful than a single type. To evaluate whether the machine-learned combination of two confirmatory tests is more useful in predicting subtypes of PA than each test alone.
Design: A retrospective cross-sectional study in referral centres.
Patients: This study included 615 patients with PA randomly assigned to the training and test data sets. The participants underwent saline infusion test (SIT) and captopril challenge test (CCT) and were subtyped by AVS (unilateral, n = 99; bilateral, n = 516).
Measurements: The area under the curve (AUC) and clinical usefulness using decision curve analysis for the subtype prediction in the test data set.
Results: The AUCs for the combination of SIT and CCT, SIT alone and CCT alone were 0.850, 0.813 and 0.786, respectively, with no significant differences between them. The AUC for the baseline clinical characteristics alone was 0.872, whereas the AUCs for these combined with SIT, combined with CCT and combined with both SIT and CCT were 0.868, 0.854 and 0.855, respectively, with no significant improvement in AUC. The additional clinical usefulness of the second confirmatory test was unremarkable on decision curve analysis.
Conclusions: Our data suggest that patients with positive case detection undergo one confirmatory test to determine the indication for AVS.
Keywords: adrenal cortex function tests; adrenocortical adenoma; artificial intelligence; hyperaldosteronism; hypertension; machine learning; renin-angiotensin system.
© 2022 John Wiley & Sons Ltd.