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Record W4408230852 · doi:10.1183/23120541.00038-2025

The utility of spirometry and single breath gas transfer measurements to identify low total lung capacity

2025· article· en· W4408230852 on OpenAlexaff
Ben Knox‐Brown, Sanja Stanojevic, Karl Sylvester

Bibliographic record

VenueERJ Open Research · 2025
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineSpirometryLungLung volumesIntensive care medicineInternal medicineAsthma

Abstract

fetched live from OpenAlex

Background Measurement of total lung capacity (TLC) requires large and expensive equipment. We aimed to investigate whether spirometric restriction and low alveolar volume measured by single breath gas transfer (V A) can be used to identify those with a low TLC. Methods We retrospectively analysed data from adults referred to Cambridge University Hospitals between January 2016 and December 2023. We investigated the utility of spirometric restriction (forced vital capacity (FVC) < lower limit of normal (LLN) with forced expiratory volume in 1 s /FVC ≥LLN) and reduced V A ( pleth V A to identify TLCpleth Results Data from 7923 patients were included. The majority (94%) of patients were of European ancestry, 51% were female. Mean age was 58 years. 11% of patients had a TLCpleth V A pleth pleth V A pleth V A pleth Conclusions A FVC in the healthy range is an effective tool for ruling out restriction. Low V A can be used to accurately identify those with a low TLC, negating the need for formal measurement of static lung volumes when identifying restrictive lung disease.

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)0.006
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.140
GPT teacher head0.434
Teacher spread0.295 · 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 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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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