Subtyping primary aldosteronism by inconclusive adrenal vein sampling: A derivation and validation study in a tertiary centre

Objective Indices based on aldosterone/cortisol (A/C) concentration in the successfully cannulated adrenal vein (AV) and in the inferior vena cava (IVC) (AV/IVC) appear to be possible markers to verify the subtype of primary aldosteronism (PA) in the case of inconclusive results of adrenal vein sampling (AVS). The variability of results in previous studies encouraged us to calculate AV/IVC and adrenal A/C cutoff values that could predict the aetiology of PA. Methods This retrospective study included 96 patients who underwent AVS due to PA between 2015 and 2020. The derivation cohort ultimately consisted of 60 patients with bilaterally successful AVS and a clear diagnosis of unilateral or bilateral disease. Receiver operating characteristic analysis was used to find the optimal A/C and AV/IVC cutoff values predicting the subtype of PA. The validation cohort consisted of 11 patients with either unsuccessful cannulation or a borderline lateralization index (LI), those patients underwent adrenalectomy because their indices were suggestive of unilateral disease based on the derivation cohort data. Results The cutoff values of A/C <= 0.63 or AV/IVC <= 0.37 identified unaffected glands with a sensitivity of 91.2% and 97.1%, respectively, and a specificity of 90.7% and 88.4%, respectively. Unilateral ipsilateral gland involvement was characterized by A/C >= 3.5 or AV/IVC >= 3.4 with a corresponding specificity of 100%. All patients in the validation cohort achieved biochemical remission postoperatively. Conclusions A/C and AV/IVC cutoff values could be a useful tool to determine the subtype of PA in patients with unilateral successful AVS as well as in patients with a borderline LI.

Automated summary

Objective indices based on aldosterone/cortisol concentration in the adrenal vein and inferior vena cava can be used to determine the subtype of primary aldosteronism. The study provides cutoff values that can predict the aetiology of the disease and determine the location and involvement of the lesions.