Automated Chronic Obstructive Pulmonary Disease Phenotyping and Control Assessment in Primary Care: Retrospective Multicenter Study Using the Seleida Model.

ABSTRACT:

Background

Chronic obstructive pulmonary disease (COPD) remains a leading global health burden. In primary care, the inconsistent availability of spirometry and symptom scores limits the detection of patients with poor disease control. There is a pressing need for scalable, data-driven tools that leverage routinely collected clinical information to support timely, equitable, and guideline-concordant interventions.

Objective

This study aims to validate the performance of Seleida-a fully automated, deterministic, and bijective model for COPD control assessment and phenotyping-using real-world primary care data and to evaluate its feasibility for integration into electronic health record (EHR)-based informatics systems.

Methods

Seleida estimates the probability of poor c

SUBMITTER: Maya Viejo JD 

PROVIDER: S-EPMC12517459 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature