Contralateral Suppression in Adrenal Venous Sampling Predicts Clinical and Biochemical Outcome in Primary Aldosteronism.

Abstract

The role of hormone parameters at adrenal venous sampling (AVS) in predicting clinical and biochemical outcomes remains controversial. To investigate the impact of hormone parameters at AVS under cosyntropin stimulation on lateralization and on complete biochemical and clinical outcomes. We retrospectively evaluated 150 sequential AVS under cosyntropin infusion. The bilateral successful cannulation rate was 83.3% (n = 140), 47.9% bilateral and 52.1% unilateral. The lateralization index, aldosterone/cortisol ratio (A/C) in the dominant adrenal vein (AV), and relative aldosterone secretion index (RASI = A/C in AV divided by A/C in inferior vena cava) were assessed. The contralateral suppression (CS) percentage was defined by (1 - nondominant RASI) * 100. A nondominant RASI <0.5 (CS >50%) had 86.84% sensitivity and 92.96% specificity to predict contralateral lateralization. An A/C ratio in dominant AV >5.9 (74.67% sensitivity and 80% specificity) and dominant RASI >4.7 (35.21% sensitivity and 88.06% specificity) had the worst performance to predict ipsilateral lateralization. Complete biochemical and clinical cure was significantly more frequent in the patients with CS >50% [98.41% vs 42.86% (P < .001) and 41.94% vs 0% (P < .001)]. CS correlated with high aldosterone at diagnosis (P < .001) and low postoperative aldosterone levels at 1 month (P = .019). Postoperative biochemical hypoaldosteronism was more frequent in patients with CS >50% (70% vs 16.67%, P = .014). In multivariable analysis, a CS >50% was associated with complete biochemical cure [odds ratio (OR) 125, 95% confidence interval (CI) 11.904-5000; P = .001] and hypertension remission (OR 12.19, 95% CI 2.074-250; P = .023). A CS >50% was an independent predictor of complete clinical and biochemical cure. Moreover, it can predict unilateral primary aldosteronism and postoperative biochemical hypoaldosteronism. Our findings underscore the usefulness of CS for clinical decision-making.