ArticleInternational journal of chronic obstructive pulmonary disease2020
Prediction of Spirometric Indices Using Forced Oscillometric Indices in Patients with Asthma, COPD, and Interstitial Lung Disease.
Article in International journal of chronic obstructive pulmonary disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Estimation of pulmonary function from time-resolved dynamic chest radiography using machine learning in patients with respiratory disease.Journal of applied clinical medical physics · 2026Article
- Applications of Forced Oscillatory Technique in Obstructive and Restrictive Pulmonary Diseases: A Concise State of the Art.Journal of clinical medicine · 2025Review
- Environmental Arsenic Exposure, Biomarkers and Lung Function in Children from Yaqui Communities in Sonora, Mexico.Journal of xenobiotics · 2025Article
- The impact of respiratory reactance in oscillometry on survival in patients with idiopathic pulmonary fibrosis.BMC pulmonary medicine · 2024Article
- Prediction of Pulmonary Function Parameters Based on a Combination Algorithm.Bioengineering (Basel, Switzerland) · 2022Article
- Oscillation Mechanics, Integer and Fractional Respiratory Modeling in COPD: Effect of Obstruction Severity.International journal of chronic obstructive pulmonary disease · 2020Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Objective: Spirometry is sometimes difficult to perform in elderly patients and patients with cognitive impairment. Forced oscillometry (FOT) is a simple, noninvasive technique used for measuring respiratory impedance. The aim of this study was to develop regression equations to estimate vital capacity (VC), forced vital capacity (FVC), and forced expiratory volume in 1 s (FEV Materials and Methods: We retrospectively included data on 683 consecutive patients with asthma (388), COPD (128), or ILD (167) in this study. We generated regression equations for VC, FVC, and FEV Results: Actual and estimated VC, FVC, and FEV Conclusion: These results suggest that our method is not highly accurate. Further studies are needed to generate more accurate regression equations for estimating spirometric indices based on FOT measurements.
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Registered trials
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