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Record W4415476931 · doi:10.1183/23120541.00889-2025

A comparison of pulmonary capillary blood volume and membrane diffusing capacity assessed <i>via</i> two pulmonary diffusing capacity approaches

2025· article· en· W4415476931 on OpenAlexafffund
Andrew W. D’Souza, Andrew R. Brotto, Thomas G. Williams, Desi P. Fuhr, Michael K. Stickland

Bibliographic record

VenueERJ Open Research · 2025
Typearticle
Languageen
FieldChemistry
Topicthermodynamics and calorimetric analyses
Canadian institutionsCovenant HealthUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsDiffusing capacityPulmonary Diffusing CapacityCapillary actionPulmonary function testingSpirometryOxygenBlood volumeVolume (thermodynamics)

Abstract

fetched live from OpenAlex

Background The combined measurement of pulmonary diffusing capacity for carbon monoxide ( D LCO ) and nitric oxide ( D LNO ) permits the interrogation of pulmonary capillary blood volume ( V c ) and membrane diffusing capacity ( D m ) from a single-breath hold, providing a less onerous means of evaluating pulmonary microvascular function than the classic Roughton–Forster multiple fractions of inspired oxygen approach (m F iO 2 – D LCO ). Despite its growing utility, the concordance between D LCO , V c and D m derived from the D LCO / D LNO and m F iO 2 – D LCO approaches remains unclear. Thus, we sought to evaluate the agreement between D LCO , V c and D m measured via the single-breath D LCO / D LNO and the m F iO 2 – D LCO approaches at baseline as well as during exercise and postural stress. We hypothesised that there would be strong agreement between the two approaches for D LCO and V c . Methods 16 healthy young adults (5 female; age: 24±4 years) completed two experimental visits: 1) cycling at 30% and 60% of peak oxygen consumption ( V ′ O 2 peak ), and 2) postural stress (supine-to-60°head-up tilt (HUT)). D LCO , V c and D m were measured via the combined D LCO / D LNO (Hypair) and m F IO 2 – D LCO approaches (randomised) at each stage. Results During baseline and exercise, D LCO demonstrated excellent agreement between measurement approaches (baseline intraclass correlation coefficient (ICC) 0.92 (95% CI 0.79–0.97); 30% V ′ O 2 peak ICC 0.89 (95% CI 0.71–0.96); 60% V ′ O 2 peak ICC 0.94 (95% CI 0.93–0.98), all p<0.001). V c exhibited moderate-to-very good agreement (baseline ICC 0.61 (95% CI 0.17–0.85); 30% V ′ O 2 peak ICC 0.77 (95% CI 0.46–0.91); 60% V ′ O 2 peak ICC 0.51 (95% CI 0.01–0.81), all p≤0.022), while D m had poor-to-moderate agreement (baseline ICC 0.19 (95% CI −0.32–0.62), p=0.228; 30% V ′ O 2 peak ICC 0.43 (95% CI −0.08–0.77), p=0.046; 60% V ′ O 2 peak ICC 0.51 (95% CI −0.01–0.82), p=0.026). Similar results were observed during postural stress. Conclusion These data indicate that D LCO and V c , but not D m , derived from the D LCO / D LNO and m F IO 2 – D LCO approach are comparable.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.191
GPT teacher head0.391
Teacher spread0.200 · 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 designBench or experimental
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 routes2
Has abstractyes

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