Abstract

Abstract Context Current guidelines recommend adrenal venous sampling (AVS) to identify unilateral primary aldosteronism (UPA) before offering adrenalectomy. However, AVS is costly and technically challenging, limiting its use to expert centres. Objective To establish a model to predict UPA and therefore bypass the need for AVS prior to surgery. Design and Setting: The model was developed in a Chinese cohort and validated in an Australian cohort. Previously published prediction models of UPA were also tested. Participants: PA patients with a definite subtyping diagnosis based on AVS and/or surgery. Main Outcome Measure: Diagnostic value of the model. Results In the development cohort (268 UPA and 88 bilateral PA), combinations of different levels of low serum potassium (≤3. 0 or 3.5mmol/L), high PAC (≥15-30ng/dL), low PRC (≤2.5-10μIU/mL) and presence of unilateral nodule on adrenal CT (>8-15mm in diameter) showedspecificity of 1. 00 and sensitivity of 0.16-0.52. The model of serum potassium≤3.5mmol/l, PAC≥20 ng/dL, PRC≤5μIU/mL plus a unilateral nodule≥10mmhad the highest sensitivity of 0.52(0.45-0.58) and specificity of 1. 00(0.96-1. 00). In the validation cohort (84 UPA and 117 bilateral PA), the sensitivity and specificity of the model were 0.13(0. 07-0.22) and 1. 00(0.97-1. 00), respectively. Ten previous models were tested, and only one had a specificity of 1. 00 in our cohorts, but with a very low sensitivity [0. 07(0. 04-0.10) and 0. 01(0. 00-0. 06) in our development and validation cohorts, respectively]. Conclusions A combination of high PAC, low PRC, low serum potassium and unilateral adrenal nodule could accurately determine PA subtype in 13-52% of patients with UPA and obviate the need for AVS before surgery. Presentation: No date and time listed

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