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International Delphi study: Interpreting respiratory oscillometry in adults with asthma or COPD

2025· article· W4416639854 on OpenAlexaff
Li Ping Chung, Bruce Thompson, Gregory G. King, Omar S. Usmani, Salman Siddiqui, Ronald J. Dandurand, Monica Kraft, Claude S. Farah

Bibliographic record

Venuenot available
Typearticle
Language
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsPulmonologistsCOPDAsthmaDelphi methodDiseasePulmonologistSpirometry

Abstract

fetched live from OpenAlex

Background: Respiratory oscillometry measures the mechanics if the airways, chest wall and lung parenchyma during tidal breathing, with growing utility in many respiratory diseases. Uncertainty though in the interpretation of oscillometry is a barrier to routine everyday use. Aim: To aid the interpretation of oscillometry in patients with asthma or COPD by generating expert consensus statements. Methods: Using the Delphi process, initial statements on oscillometry use were proposed, refined(brainstorming round), and assessed by 60 pulmonologists form 22 countries over 3 rounds. Consensus was defined as ≥70% agreement. Results: Pulmonologists agreed oscillometry was useful to assess abnormal lung function, its severity, and measure bronchodilator response (BDR). There was high consensus for using Z-scores for resistance(R5,85%), reactance (X5, 92%) and area under the reactance curve (AX, 79%) to identify abnormal lung function. Experts agreed in using percentage change for R5, X5 and AX to measure BDR. Figure 1: Guidance on interpretign oscillometry erj;66/suppl_69/PA396/F1 F1 F1 Conclusion: Focusing on a few key parameters, our study gives confidence in aiding clinicians in interpreting oscillometry to assess abnormal lung function, disease severity, disease progression, and BDR in everyday clinical practice based on current evidence and expert consensus.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.096
metaresearch head score (Gemma)0.126
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.510

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0960.126
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0020.004
Open science0.0010.008
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.059
GPT teacher head0.442
Teacher spread0.383 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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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