Abstract
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. To establish a model to predict UPA, and therefore, bypass the need for AVS prior to surgery. The model was developed in a Chinese cohort and validated in an Australian cohort. Previously published prediction models of UPA were also tested. primary aldosteronism patients with a definite subtyping diagnosis based on AVS and/or surgery. Diagnostic value of the model. In the development cohort (268 UPA and 88 bilateral primary aldosteronism), combinations of different levels of low serum potassium (≤3.0 or 3.5 mmol/l), high PAC (≥15-30 ng/dl), low PRC (≤2.5-10 μIU/ml) and presence of unilateral nodule on adrenal CT (>8-15 mm in diameter) showed specificity of 1.00 and sensitivity of 0.16-0.52. The model of serum potassium 3.5 mmol/l or less, PAC at least 20 ng/dl, PRC 5 μIU/ml or less plus a unilateral nodule at least 10 mm had 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 primary aldosteronism), 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]. A combination of high PAC, low PRC, low serum potassium and unilateral adrenal nodule could accurately determine primary aldosteronism subtype in 13-52% of patients with UPA and obviate the need for AVS before surgery.
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