Skeletal muscle oxygenation and regional blood volume during incremental limb loading in interstitial lung disease
Bibliographic record
Abstract
Introduction Individuals with interstitial lung disease (ILD) exhibit reduced exercise capacity and exertional hypoxaemia. The role of peripheral (muscle) limitation to exercise tolerance in ILD is not well studied to date. Methods A prospective cross-sectional study examined skeletal muscle oxygen saturation (SmO2) and regional blood volume of the knee extensors and elbow flexors during incremental limb loading in healthy people and people with varying severity of ILD. Isotonic concentric exercise was performed on an isokinetic dynamometer.SmO2and regional blood volume were measured by near-infrared spectroscopy over the vastus lateralis and biceps. Results Thirteen people who were dependent on oxygen, candidates for lung transplant and with severe ILD (forced vital capacity (FVC) 59±20% predicted), 10 people who were not oxygen dependent with mild ILD (FVC 81±17% predicted) and 13 healthy people (FVC 101±14% predicted) were included. Total haemoglobin, a marker of regional blood volume, was lower at task failure in the knee extensors in participants with severe ILD compared to healthy participants (p=0.05). At task failure for both knee-extensor loading and elbow-flexor loading,SmO2was decreased to similar levels across all groups, but occurred at lower total workloads in the ILD groups (all p<0.01). Conclusions Overall, people with severe ILD had lower levels of total work and experienced less increase in blood volume in the knee extensors after knee-extensor loading compared to healthy people. Peripheral muscle dysfunction in severe ILD may have contributed to muscle deoxygenation at lower workloads.
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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) | 0.001 | 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".