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Record W4403175962 · doi:10.1101/2024.10.07.24315006

Functional respiratory abnormalities in adults who vape daily

2024· preprint· en· W4403175962 on OpenAlexaff
Ariane Lechasseur, Marc Fortin, Krystelle Godbout, Marie‐Ève Boulay, Keven Bergeron, Joanie Routhier, Geneviève Parent-Racine, Annie Roy, Geneviève Boutin, François Maltais, Andréanne Côté, Mathieu C. Morissette

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldHealth Professions
TopicPediatric health and respiratory diseases
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsRespiratory systemMedicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract Despite the widespread use of vaping, a very limited number of clinical studies have investigated the effects of this habit on the lungs of healthy individuals. Our group recently initiated the Vap ing A dverse L ung and Heart E vents Coho rt (VapALERT), a prospective study aiming to identify the impacts of vaping on respiratory and cardiovascular health. We elected to report early findings from the pulmonary function tests performed at the initial visit of the first 83 participants recruited so far. Almost 80% of volunteers with no diagnosis of lung disease and who vape daily have an abnormal airway reactivity to metacholine and/or lung clearance index and/or diffusion capacity. We can conclude from this study that adult individuals who vape daily are very likely to present asymptomatic functional respiratory abnormalities, especially airway hyperresponsiveness, ventilation heterogeneity and reduced gas diffusion regardless of past or current tobacco and/or cannabis smoking. Longitudinal studies are crucial to determine how respiratory abnormalities observed in individuals who vape will progress over time.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.068
GPT teacher head0.382
Teacher spread0.314 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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