1. Estimating rate of lung function change using clinical spirometry data
- Author
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Robert A Wise, Nadia N Hansel, Nirupama Putcha, Meredith C McCormack, Aparna Balasubramanian, Christopher Cervantes, Andrew S Gearhart, Ashraf Fawzy, and Anil Singh
- Subjects
Medicine ,Diseases of the respiratory system ,RC705-779 - 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. Univariate zero-inflated negative binomial regressions tested associations between estimates and all-cause or COPD hospitalisations. Results were validated in an external cohort.Results Among 1417 participants, median rate of change was approximately −30 mL/year or −2%/year. Non-regressive methods frequently generated erroneous estimates due to outlier first measurements or short intervals between tests. Average change yielded the most extreme estimates (minimum=−3761 mL/year), while regressive methods, and Huber specifically, minimised extreme estimates. Huber, Total Change and Quantile FEV1 slope estimates were associated with all-cause hospitalisations (Huber incidence rate ratio 0.98, 95% CI 0.97 to 0.99, p
- Published
- 2024
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