Oxygen supplementation during exercise improves leg muscle fatigue in chronic fibrotic interstitial lung disease
Bibliographic record
Abstract
Background Exercise-induced hypoxaemia is a hallmark of chronic fibrotic interstitial lung disease ( f -ILD). It remains unclear whether patients’ severe hypoxaemia may exaggerate locomotor muscle fatigue and, if so, to what extent oxygen (O 2 ) supplementation can ameliorate these abnormalities. Methods Fifteen patients (12 males, 9 with idiopathic pulmonary fibrosis) performed a constant-load (60% peak work rate) cycle test to symptom limitation (Tlim) while breathing medical air. Fifteen age-matched and sex-matched controls cycled up to patients’ Tlim. Patients repeated the exercise test on supplemental O 2 (42%±7%) for the same duration. Near-infrared spectroscopy assessed vastus lateralis oxyhaemoglobin concentration ((HbO 2 )). Pre-exercise to postexercise variation in twitch force (∆Tw) induced by femoral nerve magnetic stimulation quantified muscle fatigue. Results Patients showed severe hypoxaemia (lowest O 2 saturation by pulse oximetry=80.0%±7.6%) which was associated with a blunted increase in muscle (HbO 2) during exercise vs controls (+1.3±0.3 µmol vs +4.4±0.4 µmol, respectively; p<0.001). Despite exercising at work rates ∼ one-third lower than controls (42±13 W vs 66±13 W), ∆Tw was greater in patients (∆Tw/external work performed by the leg muscles=−0.59±0.21 %/kJ vs −0.25±0.19 %/kJ; p<0.001). Reversal of exertional hypoxaemia with supplemental O 2 was associated with a significant increase in muscle (HbO 2) , leading to a reduced decrease in ∆Tw in patients (−0.33±0.19 %/kJ; p<0.001 vs air). Supplemental O 2 significantly improved leg discomfort (p=0.005). Conclusion O 2 supplementation during exercise improves leg muscle oxygenation and fatigue in f -ILD. Lessening peripheral muscle fatigue to enhance exercise tolerance is a neglected therapeutic target that deserves clinical attention in this patient population.
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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 | 0.000 |
| 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) | 0.001 | 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".