ABSTRACT
Objective:
To establish and validate a
nomogram-based predictive model for idiopathic
hyperaldosteronism (IHA).
Methods:
This
cross-sectional study was conducted with the collected clinical and biochemical data of
patients with primary
aldosteronism (PA) including 249
patients with unilateral primary
aldosteronism (UPA) and 107
patients with IHA,
who were treated at the Department of
Endocrinology of the First Affiliated
Hospital of Chongqing Medical
University from November 2013 to November 2022.
Plasma aldosterone concentration (PAC) and
plasma renin concentration (PRC) were measured by
chemiluminescence. Stepwise
regression analysis was applied to select the key predictors of IHA, and a
nomogram-based scoring model was developed. The model was validated in another external independent cohort of
patients with PA including 62
patients with UPA and 43
patients with IHA,
who were diagnosed at the Department of
Endocrinology, First Affiliated
Hospital of Zhengzhou
University. An independent-sample t
test, Mann-Whitney U test, and χ2 test were used for
statistical analysis.
Results:
In the
training cohort, in comparison with the UPA group, the IHA group showed a higher
serum potassium level [M(Q1, Q3), 3.4 (3.1, 3.8) mmol/L vs. 2.7 (2.1, 3.1) mmol/L] and higher PRC [4.0 (2.1, 8.2) mU/L vs. 1.5 (0.6, 3.4) mU/L] and a lower PAC post-saline infusion test (SIT) [305 (222, 416) pmol/L vs. 720 (443, 1 136) pmol/L] and a lower rate of unilateral adrenal nodules [33.6% (36/107) vs. 81.1% (202/249)]; the intergroup differences in these measurements were statistically significant (all P<0.001).
Serum potassium level, PRC, PAC post-SIT, and the rate of unilateral adrenal nodules showed
similar performance in the IHA group in the validation cohort. After stepwise
regression analysis for all significant variables in the
training cohort, a scoring model based on a
nomogram was constructed, and the predictive
parameters included the rate of unilateral adrenal nodules,
serum potassium concentration, PAC post-SIT, and PRC in the
standing position. When the total score was ≥14, the model showed a
sensitivity of 0.65 and
specificity of 0.90 in the
training cohort and a
sensitivity of 0.56 and
specificity of 1.00 in the validation cohort.
Conclusion:
The
nomogram was used to successfully develop a model for prediction of IHA that could facilitate selection of
patients with IHA
who required medication directly.