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Intra-breath Oscillometry is Associated With Patient-reported Symptoms and 6-minute Walk Distance at 6 Months After Mild COVID-19 Infection

2025· article· en· W4410276902 on OpenAlexaff
Tadahisa Numakura, Jun Wu, Nyarko Christiana Cynthia, Hiroshi Ota, Natalia Belousova, Margaret S. Herridge, Angela Cheung, Ella Huszti, Zoltán Hantos, Chung‐Wai Chow

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicVoice and Speech Disorders
Canadian institutionsToronto General HospitalUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsMedicineCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Internal medicineIntensive care medicineVirologyDiseaseInfectious disease (medical specialty)

Abstract

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Abstract Background: The mechanisms responsible for the persistent respiratory symptoms with mild acute COVID-19, defined by management as outpatients, have not been fully characterized as most patients have normal spirometry. Oscillometry is a different pulmonary function test that measures respiratory impedance to superimposed small pressure signals during normal breathing. It is highly sensitive to changes in lung mechanics. The current standard oscillometry output provides measurement of the mean impedance of a tidal breath. Intra-breath oscillometry is a novel technique that tracks respiratory impedance during tidal breathing to provide more detailed information about changes in lung mechanics. No studies have assessed respiratory function after acute COVID-19 infection using intra-breath oscillometry. Methods: Mild acute COVID-19 patients were enrolled in the CANCOV study at the University Health Network, and evaluated with oscillometry, spirometry, patient-reported symptom checklist, 6-minute walk distance (6MWD) test and Borg dyspnea scale between August 2020 and March 2022. Date of infection was defined by symptom onset and/or positive rapid antigen test. The intra-breath oscillometry metrics of interest were resistance at end-expiration (ReE) and end-inspiration (ReI) and reactance at end-expiration (XeE) and end-inspiration (XeI). Regression analyses were used to identify association between intra-breath oscillometry, symptoms, 6MWD and Borg dyspnea score with adjustment for age, sex and height. Results: The cohort consisted of 177 outpatients with 57.3% females and median age of 45.2 years. Spirometry was normal at 6 months post-infection. Median (IQR) z-scores of forced vital capacity (FVC) and forced expiratory volume in 1 second (FEV1)/FVC were 0.09 (-0.57, 0.66) and -0.22 (-0.76, 0.14); the FEV1/FVC ratio was 0.80 (0.77, 0.84), respectively. Most patients (51.7%) reported persistent symptoms including chest heaviness/tightness/pain, shortness of breath, breathing harder/faster at rest, breathing faster than normal, and fatigue. Moreover, 21.1% had functional impairment as reflected by 6MWD < lower limit of normal. Logistic regression identified ReE, ReI, XeE and XeI to be highly associated with patient-reported symptoms (P < 0.05). Linear regression revealed these metrics to be significantly associated with 6MWD and Borg dyspnea scores (P < 0.05). In contrast, spirometry did not show significant associations with patient-reported symptoms, 6MWD or Borg dyspnea score. Conclusions: At 6-months after mild acute COVID-19 infection, intra-breath oscillometry identified abnormal lung mechanics that were indiscernible by standard oscillometry and spirometry. Furthermore, the intra-breath measures were significantly associated with subjective respiratory symptoms and objective metrics that include the Borg dyspnea score and functional outcome as captured by the 6MWD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.299
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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