The effect of diaphragm fatigue on the multidimensional components of dyspnoea and diaphragm electromyography during exercise in healthy males
Bibliographic record
Abstract
Key points Diaphragm fatigue may increase the intensity (sensory dimension) and unpleasantness (affective dimension) of dyspnoea, which may partially explain why diaphragm fatigue negatively affects exercise performance. We hypothesized that diaphragm fatigue would negatively affect exercise performance via increases in both the intensity and unpleasantness of dyspnoea, and that the increase in dyspnoea would be mechanistically linked to an increase in diaphragmatic EMG (EMG di ), a surrogate measure of neural respiratory drive. Fatiguing the diaphragm prior to exercise reduced cycling performance and increased both the intensity and unpleasantness of dyspnoea. The change in submaximal dyspnoea unpleasantness was significantly correlated with the change in cycling performance. Pre‐fatigue of the diaphragm did not increase EMG di during exercise and is therefore unrelated to the increase in either the sensory or affective dimension of exertional dyspnoea. Abstract The purpose of this study was to examine the effect of diaphragm fatigue on the multidimensional components of dyspnoea and diaphragm electromyography (EMG di ) during cycling. Sixteen healthy males (age = 27 ± 5 yr, = 45.8 ± 9.8 ml kg −1 min −1 ) completed two high‐intensity, time‐to‐exhaustion cycling tests in randomized order: (i) inspiratory pressure threshold loading (PTL) prior to exercise to induce diaphragm fatigue (pre‐DF) and (ii) no PTL (control). Diaphragm fatigue after PTL was confirmed via cervical magnetic stimulation of the phrenic nerves. Dyspnoea intensity and unpleasantness were measured throughout exercise with the 0–10 category‐ratio Borg scale and following exercise using the Multidimensional Dyspnoea Profile (MDP). EMG di was continuously recorded via a multipair oesophageal electrode catheter. Time‐to‐exhaustion decreased with pre‐DF vs . control (9.0 ± 5.5 vs . 10.7 ± 7.5 min, P = 0.023). Pre‐DF increased dyspnoea intensity ratings by 0.6 ± 1.0 Borg 0–10 units at the highest equivalent submaximal exercise time (HESET) a participant could achieve in both conditions ( P = 0.020). Dyspnoea unpleasantness ratings increased with pre‐DF by 0.5 ± 1.0, 0.7 ± 1.2 and 0.9 ± 1.4 (all P < 0.05) Borg 0–10 units during the 2nd, 3rd and 4th minutes of exercise, respectively. There was a significant correlation between the change in breathing unpleasantness ratings at HESET and the change in time‐to‐exhaustion ( r = 0.66, P = 0.006). The immediate perception domain, a combination of peak unpleasantness and specific dyspnoea descriptor intensity ratings, was the only component of the MDP that was significantly increased with pre‐DF (4.3 ± 1.9 vs . 3.6 ± 1.8, P = 0.04). There were no significant differences in EMG di . In conclusion, diaphragm fatigue has negative effects on multiple domains of dyspnoea, which may partially explain why exercise performance decreases with it.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".