Aldosterone-potassium ratio predicts primary aldosteronism subtype
SourceJournal of Hypertension, 38, 7, (2020), pp. 1375-1383
Article / Letter to editor
Display more detailsDisplay less details
Journal of Hypertension
SubjectRadboudumc 16: Vascular damage RIHS: Radboud Institute for Health Sciences
OBJECTIVE: Prediction models have been developed to predict either unilateral or bilateral primary aldosteronism, and these have not been validated externally. We aimed to develop a simplified score to predict both subtypes and validate this externally. METHODS: Our development cohort was taken from 165 patients who underwent adrenal vein sampling (AVS) in two Asian tertiary centres. Unilateral disease was determined using both AVS and postoperative outcome. Multivariable analysis was used to construct prediction models. We validated our tool in a European cohort of 97 patients enrolled in the SPARTACUS trial who underwent AVS. Previously published prediction models were also tested in our cohorts. RESULTS: Backward stepwise logistic regression analysis yielded a final tool using baseline aldosterone-to-lowest-potassium ratio (APR, ng/dl/mmol/l), with an area under receiver-operating characteristic curve of 0.80 (95% CI 0.70-0.89). In the Asian development cohort, probability of bilateral disease was 90.0% (with APR <5) and probability of unilateral disease was 91.4% (with APR >15). Similar results were seen in the European validation cohort. Combining both cohorts, probability of bilateral disease was 76.7% (with APR <5), and probability for unilateral was 91.7% (with APR >15). Other models had similar predictive ability but required more variables, and were less sensitive for identifying bilateral PA. CONCLUSION: The novel aldosterone-to-lowest-potassium ratio is a convenient score to guide clinicians and patients of various ethnicities on the probability of primary aldosteronism subtype. Using APR to identify patients more likely to benefit from AVS may be a cost-effective strategy to manage this common condition.
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.