Prediction model of obstructive sleep apnea-related hypertension: Machine learning-based development and interpretation study.

ABSTRACT:

Background

Obstructive sleep apnea (OSA) is a globally prevalent disease closely associated with hypertension. To date, no predictive model for OSA-related hypertension has been established. We aimed to use machine learning (ML) to construct a model to analyze risk factors and predict OSA-related hypertension.

Materials and methods

We retrospectively collected the clinical data of OSA patients diagnosed by polysomnography from October 2019 to December 2021 and randomly divided them into training and validation sets. A total of 1,493 OSA patients with 27 variables were included. Independent risk factors for the risk of OSA-related hypertension were screened by the multifactorial logistic regression models. Six ML algorithms, including the logistic regression (LR), the gradien

SUBMITTER: Shi Y 

PROVIDER: S-EPMC9760810 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature