Abstract

BackgroundsAdrenal venous sampling (AVS) represents the gold standard for classifying primary aldosteronism (PA). However, AVS is a technically demanding, expensive and invasive procedure. Computed tomography (CT) scans is recommended as the initial study of classification diagnosis by the current guidelines. In addition, postural stimulation test (PST) has been used to provide additional subtype diagnostic information.ObjectiveThis work aimed to evaluate the diagnostic utility of the adrenal CT combined with PST in the classification diagnosis of PA.MethodsWe analyzed PA patients who underwent AVS from November 2017 to February 2022 at a single center. Subtype classification of PA was determined by AVS. We analyzed the concordance rate between AVS outcomes, adrenal CT, and PST, and explored the value of adrenal CT combined with PST for predicting laterality of PA.ResultsTotal 531 PA patients were included in the present study. The concordance rate between AVS and the adrenal CT was 51.0%(271/531). Receiver operating characteristic (ROC) curve of PST showed that the area under curve (AUC) was 0.604 [95% confidence interval (CI): 0.556, 0.652], the optimal cut-off value was 30%. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (+LR), and negative likelihood ratio (−LR) of PST for diagnosis bilateral PA on AVS was 72.8, 46.2%, 0.48, 0.71, 1.35, and 0.59, respectively. The prevalence of unilateral PA on AVS in patients with unilateral lesion on CT and negative PST, unilateral lesion on CT and positive PST, bilateral normal or lesions on CT and negative PST, and bilateral normal or lesions on CT and positive PST was 82.4% (108/131), 59.9% (91/152), 50.7% (37/73), and 44.6% (78/175), respectively. The sensitivity, specificity, PPV, NPV, +LR, and -LR of adrenal CT combined with PST for the diagnosis of unilateral PA were 34.4, 89.4%, 0.82, 0.49, 3.25, and 0.73, respectively.ConclusionsThe combination of CT findings and PST can improve the accuracy of predicting laterality of PA.

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