Tools to Predict Unilateral Primary Aldosteronism and Optimise Patient Selection for Adrenal Vein Sampling: A...

Area of Science:

• Endocrinology
• Hypertension Management
• Diagnostic Accuracy

Background:

• Primary aldosteronism (PA) is the most common endocrine cause of hypertension.
• Adrenal vein sampling (AVS) is crucial for differentiating unilateral from bilateral PA.
• AVS is invasive and technically demanding, necessitating improved patient selection.

Purpose of the Study:

• To evaluate the diagnostic accuracy of published algorithms for predicting unilateral PA.
• To facilitate informed patient selection for adrenal vein sampling (AVS).
• To optimize the use of AVS for patients with primary aldosteronism.

Main Methods:

• Systematic review of Medline and EMBASE databases.
• Identification and evaluation of published models predicting unilateral PA.
• Gold standard for evaluation included AVS and/or surgical outcomes.

Main Results:

• 28 studies evaluated 63 unique predictive algorithms; 14 were multi-cohort validated.
• A top-performing algorithm combining serum potassium, CT imaging, PAC, ARR, and female sex showed high sensitivity (78-96%) for unilateral PA.
• This algorithm could correctly select 234-289 out of 1000 PA patients for AVS, while allowing 143-324 to bypass the procedure.

Conclusions:

• Accurate algorithms can guide AVS selection, reserving the invasive procedure for high-probability unilateral PA cases.
• Improved patient selection reduces unnecessary AVS procedures, complications, and healthcare costs.
• Further validation of top algorithms in diverse cohorts is recommended for routine clinical practice.