Evidence map›Paper›PMID 41997614›Full record

Observational studyBMJ open respiratory research2026

Respiratory oscillometry identifies disease progression in interstitial lung disease.

Robert Dube, Osmin Am Duran, Ilan Azuelos, Maxime Cormier, Ronald J Dandurand, Deborah Assayag

Abstract readObservational Study
In one paragraph

Observational study in BMJ open respiratory research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Robert DubeDepartment of Medicine, McGill University, Montreal, Quebec, Canada.
Osmin Am DuranResearch Institute, McGill University Health Centre, Montreal, Quebec, Canada.
Ilan AzuelosDepartment of Medicine, McGill University, Montreal, Quebec, Canada.
Maxime CormierDepartment of Medicine, McGill University, Montreal, Quebec, Canada.
Ronald J DandurandResearch Institute, McGill University Health Centre, Montreal, Quebec, Canada.
Deborah AssayagDepartment of Medicine, McGill University, Montreal, Quebec, Canada deborah.assayag@mcgill.ca.ORCID http://orcid.org/0000-0002-2497-9984

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRespiratory oscillometry is an effort-independent method of evaluating lung function. Its role in the monitoring of interstitial lung disease (ILD) is unclear. This observational longitudinal study assessed the relationship between oscillometry and pulmonary function test (PFT) parameters in ILD over time and determined whether oscillometry can detect disease progression.

methodsParticipants underwent PFT and oscillometry within the same visit at two time points. Oscillometry parameters of interest included resistance at 5 Hz (R

resultsOf the 43 participants enrolled, 17 (40%) demonstrated interval clinical worsening over a median follow-up of 384 days. Spirometry parameters displayed moderate-to-strong correlations with all oscillometry parameters, especially the reactance measures AX and X

conclusionReactance measures of oscillometry remained correlated with traditional lung function tests over time. Oscillometry parameters also showed significant temporal differences between participants with and without evidence of clinical worsening, unlike spirometry measures, which did not capture progression. These findings suggest that oscillometry may hold value in the longitudinal monitoring of ILD.

Indexed as

Lung Diseases, InterstitialOscillometryRespiratory Function TestsAgedDisease ProgressionFemaleHumansLongitudinal StudiesLungMaleMiddle AgedSpirometryInterstitial FibrosisRespiratory Function Test

Identifiers

PMID41997614
PMCPMC13110701

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.