Online prediction model for primary aldosteronism in patients with hypertension in Chinese population: A two-center retrospective study.

ABSTRACT:

Background

The prevalence of primary aldosteronism (PA) varies from 5% to 20% in patients with hypertension but is largely underdiagnosed. Expanding screening for PA to all patients with hypertension to improve diagnostic efficiency is needed. A novel and portable prediction tool that can expand screening for PA is highly desirable.

Methods

Clinical characteristics and laboratory data of 1,314 patients with hypertension were collected for modeling and randomly divided into a training cohort (919 of 1,314, 70%) and an internal validation cohort (395 of 1,314, 30%). Additionally, an external dataset (n = 285) was used for model validation. Machine learning algorithms were applied to develop a discriminant model. Sensitivity, specificity, and accuracy were used to evaluate the

SUBMITTER: Lin W 

PROVIDER: S-EPMC9380986 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature