Ontology highlight
ABSTRACT: Background
Adherence to tuberculosis (TB) treatment is key to optimal health outcomes. Programmatic definitions of treatment success may mask heterogeneity in care engagement patterns that increase risk of unfavorable outcomes.Methods
Using patient-level medication refill data, latent-class growth modelling was used to identify longitudinal trajectories of care engagement among participants who programmatically achieved treatment success. Logistic regression was conducted to investigate participant-level characteristics associated with trajectory class membership.Results
Among 548 participants, we identified three trajectories: Class 1 (consistent engagement; 84.1%), Class 2 (suboptimal engagement after 2 months; 7.7%) and Class 3 (suboptimal engagement from initiat
SUBMITTER: Medina Marino A
PROVIDER: S-EPMC12425060 | biostudies-literature | 2025 Sep
REPOSITORIES: biostudies-literature