A novel clinical-imaging nomogram for predicting primary aldosteronism in patients with hypertension

This study aimed to develop and validate the accuracy of a clinical-imaging index nomogram in predicting primary aldosteronism (PA) in patients with hypertension. This case-control study enrolled 404 hypertension patients in the First Affiliated Hospital of Nanjing Medical University, China, from April 2017 to September 2021. The patients were randomly divided into the training set (n = 283, 70%) and the validation set (n = 121, 30%). Univariate and multivariate logistic regression analyses were performed to identify independent predictors of PA, which were then used construct a nomogram. The receiver operating characteristic (ROC) curve and calibration plot were drawn to assess the predictive value. The accuracies of our nomogram and other known prediction models were compared using decision curve analyses (DCA). Four significant variables (history of hypokalemia [OR = 2.684, 95% CI: 1.281-5.623, P < 0.001], typical imaging feature [OR = 2.316, 95% CI: 1.166-4.601, P = 0.003], 24 h urine potassium [OR = 0.956, 95% CI: 0.932-0.980, P < 0.001], plasma renin activity [PRA] [OR = 1.423, 95% CI: 1.161-1.744, P < 0.001]) in the multivariate logistic regression analysis were sifted out, and used to build the nomogram. The predictive nomogram yielded an AUC of 0.890 (95% CI, 0.853-0.927) in the training set and 0.860 (95% CI, 0.793-0.927) in the validation set. Predicted and actual probability of PA matched well in the nomogram. Moreover, the DCA showed that the nomogram gained a net benefit in clinical practice in predicting PA when the threshold value was set between 0.1 and 1.0. Our four-variable nomogram was accurate in predicting PA patients and might be introduced into clinical management.