Causal Deep Neural Network-Based Model for First-Line Hypertension Management.

ABSTRACT:

Objective

To develop and validate a machine learning model that predicts the most successful antihypertensive treatment for an individual.

Patients and methods

The causal, deep neural network-based model was trained on data from 16,917 newly diagnosed hypertensive patients attending Mayo Clinic's primary care practices from January 1, 2005, to December 31, 2021. Eligibility criteria included a diagnosis of primary hypertension, blood pressure and creatinine measurements before antihypertensive treatment, treatment within 9 months of diagnosis, and at least 1 year of follow up. The primary outcome was model performance in predicting the likelihood of a successful antihypertensive treatment 1 year from the start of treatment. Treatment success was defined as achieving blood pr

SUBMITTER: Herzog L 

PROVIDER: S-EPMC11975727 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature