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Record W4286500618 · doi:10.1113/jp283252

Exertional dyspnoea in patients with mild‐to‐severe chronic obstructive pulmonary disease: neuromechanical mechanisms

2022· article· en· W4286500618 on OpenAlexafffund
Matthew D. James, Devin B. Phillips, Sandra G. Vincent, Sara J. Abdallah, Adamo A. Donovan, Juan P. de‐Torres, J. Alberto Neder, Benjamin M. Smith, Dennis Jensen, Denis E. O’Donnell

Bibliographic record

VenueThe Journal of Physiology · 2022
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsMcGill University Health CentreKingston Health Sciences CentreMcGill UniversityQueen's University
FundersCanadian Institutes of Health Research
KeywordsMedicineCardiologyCOPDInternal medicinePulmonary diseasePhysical therapyElectromyographyTidal volumePhysical medicine and rehabilitationRespiratory system

Abstract

fetched live from OpenAlex

Abstract In patients with chronic obstructive pulmonary disease (COPD), exertional dyspnoea generally arises when there is imbalance between ventilatory demand and capacity, but the neurophysiological mechanisms are unclear. We therefore determined if disparity between elevated inspiratory neural drive (IND) and tidal volume ( V T ) responses (neuromechanical dissociation) impacted dyspnoea intensity and quality during exercise, across the COPD severity spectrum. In this two‐centre, cross‐sectional observational study, 89 participants with COPD divided into tertiles of FEV 1 %predicted (Tertile 1 = FEV 1 = 87 ± 9%, Tertile 2 = 60 ± 9%, Tertile 3 = 32 ± 8%) and 18 non‐smoking controls, completed a symptom‐limited cardiopulmonary exercise test (CPET) with measurement of IND by diaphragm electromyography (EMGdi (%max)). The association between increasing dyspnoea intensity and EMGdi (%max) during CPET was strong ( r = 0.730, P < 0.001) and not different between the four groups who showed marked heterogeneity in pulmonary gas exchange and mechanical abnormalities. Significant inspiratory constraints (tidal volume/inspiratory capacity ( V T /IC) ≥ 70%) and onset of neuromechanical dissociation (EMGdi (%max): V T /IC > 0.75) occurred at progressively lower minute ventilation () from Control to Tertile 3. Lower resting IC meant earlier onset of neuromechanical dissociation, heightened dyspnoea intensity and greater propensity (93% in Tertile 3) to select qualitative descriptors of ‘unsatisfied inspiration’. We concluded that, regardless of marked variation in mechanical and pulmonary gas exchange abnormalities in our study sample, exertional dyspnoea intensity was linked to the magnitude of EMGdi (%max). Moreover, onset of critical inspiratory constraints and attendant neuromechanical dissociation amplified dyspnoea intensity at higher exercise intensities. Simple measurements of IC and breathing pattern during CPET provide useful insights into mechanisms of dyspnoea and exercise intolerance in individuals with COPD. image Key points Dyspnoea during exercise is a common and troublesome symptom reported by patients with chronic obstructive pulmonary disease (COPD) and is linked to an elevated inspiratory neural drive (IND). The precise mechanisms of elevated IND and dyspnoea across the continuum of airflow obstruction severity in COPD remains unclear. The present study sought to determine the mechanisms of elevated IND (by diaphragm EMG, EMGdi (%max)) and dyspnoea during cardiopulmonary exercise testing (CPET) across the continuum of COPD severity. There was a strong association between increasing dyspnoea intensity and EMGdi (%max) during CPET across the COPD continuum despite significant heterogeneity in underlying pulmonary gas exchange and respiratory mechanical impairments. Critical inspiratory constraints occurred at progressively lower ventilation during exercise with worsening severity of COPD. This was associated with the progressively lower resting inspiratory capacity with worsening disease severity. Earlier critical inspiratory constraint was associated with earlier neuromechanical dissociation and greater likelihood of reporting the sensation of ‘unsatisfied inspiration’.

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)0.002
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.011
GPT teacher head0.254
Teacher spread0.243 · 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

Citations44
Published2022
Admission routes2
Has abstractyes

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