ArticleClinical endocrinology2026
A Ten Year Overview of Adrenal Vein Sampling in Croatia: Insights and Outcomes.
Article in Clinical endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundAdrenal vein sampling (AVS) is the gold standard for subtype differentiation in primary aldosteronism (PA), yet it remains technically demanding and resource intensive. However, data on long-term performance, learning curves, and concordance with imaging in real-world clinical practice are limited.
methodsWe conducted a retrospective single-centre study including patients with PA who underwent AVS between January 2016 and June 2025. AVS was performed under continuous adrenocorticotropic hormone stimulation using a sequential sampling protocol. Procedural success, learning curve, and diagnostic concordance with computed tomography (CT) were evaluated.
resultsA total of 251 patients underwent 268 AVS procedures. Overall procedural success was achieved in 79% of cases. When stratified by radiologist experience, success rates increased significantly from 70% during the first 3 years to 87.5% in the subsequent 7 years (p = 0.003), demonstrating a clear learning curve. Repeat procedures were required in 7% of patients and were successful in 82% of cases. Among 240 patients with conclusive AVS results, concordance between CT and AVS was 61%. CT demonstrated a sensitivity of 69% and specificity of 55% for correct PA subtype classification, with substantial false-positive and false-negative rates.
conclusionsCT alone is an unreliable surrogate for subtype classification in PA and may lead to inappropriate management decisions. In contrast, AVS achieves high and progressively improving success rates, largely driven by radiologist experience, while also providing reliable diagnostic information for subtype classification. These findings support centralising AVS procedures in institutions with extensive experience, emphasising its crucial role in the optimal management of PA.
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