Estimating rate of lung function change using clinical spirometry data.

ABSTRACT:

Rationale

In chronic obstructive pulmonary disease (COPD), accurately estimating lung function from electronic health record (EHR) data would be beneficial but requires addressing complexities in clinically obtained testing. This study compared analytic methods for estimating rate of forced expiratory volume in one second (FEV₁) change from EHR data.

Methods

We estimated rate of FEV₁ change in patients with COPD from a single centre who had ≥3 outpatient tests spanning at least 1 year. Estimates were calculated as both an absolute mL/year and a relative %/year using non-regressive (Total Change, Average Change) and regressive (Quantile, RANSAC, Huber) methods. We compared distributions of the estimates across methods focusing on extreme values. Univaria

SUBMITTER: Balasubramanian A 

PROVIDER: S-EPMC11459324 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature