Exercise-induced diaphragm fatigue in a Paralympic champion rower with spinal cord injury
Bibliographic record
Abstract
The aim of this case report was to determine whether maximal upper body exercise was sufficient to induce diaphragm fatigue in a Paralympic champion adaptive rower with low-lesion spinal cord injury (SCI). An elite arms-only oarsman (age: 28 yr; stature: 1.89 m; and mass: 90.4 kg) with motor-complete SCI (T12) performed a 1,000-m time trial on an adapted rowing ergometer. Exercise measurements comprised pulmonary ventilation and gas exchange, diaphragm EMG-derived indexes of neural respiratory drive, and intrathoracic pressure-derived indexes of respiratory mechanics. Diaphragm fatigue was assessed by measuring pre- to postexercise changes in the twitch transdiaphragmatic pressure (Pdi,tw) response to anterolateral magnetic stimulation of the phrenic nerves. The time trial (248 ± 25 W, 3.9 min) elicited a peak O2 uptake of 3.46 l/min and a peak pulmonary ventilation of 150 l/min (57% MVV). Breath-to-stroke ratio was 1:1 during the initial 400 m and 2:1 thereafter. The ratio of inspiratory transdiaphragmatic pressure to diaphragm EMG (neuromuscular efficiency) fell from rest to 600 m (16.0 vs. 3.0). Potentiated Pdi,tw was substantially reduced (−33%) at 15–20 min postexercise, with only partial recovery (−12%) at 30–35 min. This is the first report of exercise-induced diaphragm fatigue in SCI. The decrease in diaphragm neuromuscular efficiency during exercise suggests that the fatigue was partly due to factors independent of ventilation (e.g., posture and locomotion). NEW & NOTEWORTHY This case report provides the first objective evidence of exercise-induced diaphragm fatigue in spinal cord injury (SCI) and, for that matter, in any population undertaking upper body exercise. Our data support the notion that high levels of exercise hyperpnea and factors other than ventilation (e.g., posture and locomotion) are responsible for the fatigue noted after upper body exercise. The findings extend our understanding of the limits of physiological function in SCI.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".