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Record W2968420140 · doi:10.1113/ep087956

Modelling the effects of age and sex on the resistive and viscoelastic components of the work of breathing during exercise

2019· article· en· W2968420140 on OpenAlexafffund
Yannick Molgat‐Seon, Paolo B. Dominelli, Jordan A. Guenette, A. William Sheel

Bibliographic record

VenueExperimental Physiology · 2019
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsUniversity of WaterlooUniversity of WinnipegSt. Paul's HospitalUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchBritish Columbia Lung Association
KeywordsViscoelasticityResistive touchscreenAgeingVentilation (architecture)MedicineSex characteristicsPsychologyInternal medicinePhysiologyMaterials sciencePhysicsComposite materialThermodynamicsComputer science

Abstract

fetched live from OpenAlex

New Findings What is the central question of this study? What is the effect of age and sex on the resistive and viscoelastic components of work of breathing (Wb) during exercise? What is the main finding and its importance? The resistive and viscoelastic components of Wb were higher in older adults, regardless of sex. The resistive, but not viscoelastic, component of Wb was higher in females than in males, regardless of age. These findings contribute to improving our understanding of the effects of ageing and sex on the mechanical ventilatory response to exercise. Abstract Healthy ageing and biological sex each affect the work of breathing (Wb) for a given minute ventilation ( ). Age‐related structural changes to the respiratory system lead to an increase in both the resistive and viscoelastic components of Wb; however, it is unclear whether healthy ageing differentially alters the mechanics of breathing in males and females. We analysed data from 22 older (60–80 years, n = 12 females) and 22 younger (20–30 years, n = 11 females) males and females that underwent an incremental cycle exercise test to exhaustion. and Wb were assessed at rest and throughout exercise. Wb– data for each participant were fitted to a non‐linear equation (i.e. Wb = a 3 + b 2) that partitions Wb into resistive (i.e. a 3) and viscoelastic (i.e. b 2) components. We then modelled the effects of healthy ageing and biological sex on each component of Wb. Overall, the model fit was excellent (r2: 0.99 ± 0.01). There was a significant main effect of age and sex on the resistive component of Wb (both P < 0.05), and a significant main effect of age (P < 0.001), but not sex (P = 0.309), on the viscoelastic component of Wb. No significant interactions between age and sex on a 3 or b 2 were noted (both P > 0.05). Our findings indicate that during exercise: (i) the higher total Wb in females relative to males is due to a higher resistive, but not viscoelastic, component of Wb, and (ii) regardless of sex, the higher Wb in older adults relative to younger adults is due to higher resistive and viscoelastic components of Wb.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.012
GPT teacher head0.261
Teacher spread0.249 · 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 designSimulation or modeling
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

Citations22
Published2019
Admission routes2
Has abstractyes

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