Identification of Multimorbidity Patterns in Rheumatoid Arthritis Through Machine Learning.

ABSTRACT:

Objective

Recognizing that the interrelationships between chronic conditions that complicate rheumatoid arthritis (RA) are poorly understood, we aimed to identify patterns of multimorbidity and to define their prevalence in RA through machine learning.

Methods

We constructed RA and age- and sex-matched (1:1) non-RA cohorts within a large commercial insurance database (MarketScan) and the Veterans Health Administration (VHA). Chronic conditions (n = 44) were identified from diagnosis codes from outpatient and inpatient encounters. Exploratory factor analysis was performed separately in both databases, stratified by RA diagnosis and sex, to identify multimorbidity patterns. The association of RA with different multimorbidity patterns was determined using conditional logistic r

SUBMITTER: England BR 

PROVIDER: S-EPMC10009900 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature