Abstract
BACKGROUND: Rates of screening for primary aldosteronism in patients who meet the criteria are exceedingly low (1%-3%). To help clinicians prioritize screening in patients most likely to benefit, we developed a risk-prediction model. METHODS: Using national Veterans Health Administration data, we identified patients who met the criteria for primary aldosteronism screening between 2000 and 2019. We performed multivariable logistic regression to identify characteristics associated with positive primary aldosteronism testing before generating a risk-scoring system based on the coefficients (0< β < 0.5 = 1 pt, 0.5 ≤ β < 1 = 2 pts, 1 ≤ β < 1.5 = 3 pts) and then tested the system performance using an internal validation cohort. RESULTS: We identified 502,190 patients who met primary aldosteronism screening criteria, of whom 1.6% were screened and 15% tested positive. Based on the regression model, we generated a risk-scoring system based on a total of 9 possible points in which age under 50, absence of smoking history, and resistant hypertension each scored 1 point; elevated serum sodium 2 points; and hypokalemia 3 points. Rates of positive screening increased with risk score, with 5.6% to 6.7% of those scoring 0 points testing positive; 7.9% to 9.0% 1 point; 8.6% to 10% 2 points; 13% to 14% 3 points; 21% 4 points; 22% to 38% 5 points; 27% to 38% 6 points; 42% to 49% 7 points; and 50% to 51% ≥8 points. CONCLUSION: In hypertensive patients who meet the criteria for primary aldosteronism screening, rates of positive screening range from 5.6% to 51%. Use of our risk-predication model incorporating these factors can identify patients most likely to benefit from testing.