Skeletal limb muscle oxygenation and regional blood volume during incremental loading in interstitial lung disease
Bibliographic record
Abstract
Introduction: It is not known whether skeletal muscle oxygenation (SmO2) decreases during exercise in interstitial lung disease (ILD). The aim was to compare SmO2 and blood volume of knee extensors and elbow flexors during incremental loading in healthy people and people with varying severity of ILD. Methods: We examined changes in SmO2 and total hemoglobin, a marker of regional blood volume, by near infrared spectroscopy during incremental isotonic exercise. Loading started at 10% of maximal voluntary isometric contraction (MVIC) and increased by 10% MVIC every two minutes until task failure. Results: 13 oxygen dependent lung transplant candidates with severe ILD (8 men, 65(5) years, FVC 59(20)% predicted), 10 non-oxygen dependent people with milder ILD (6 men, 60(9) years, FVC 81 (17)% predicted) and 13 healthy people (8 men, 60 (9) years) were included. At task failure for knee extensor and elbow flexor loading, SmO2 decreased to similar levels across all groups, but occurred at lower total workloads in the ILD groups (all p<0.01). Oxygen saturation measured by pulse oximetry was preserved. Total hemoglobin was lower in the knee extensors in severe ILD compared with healthy participants at task failure (p=0.05). During incremental loading, there was a decline over time for SmO2, oxygenated and deoxygenated hemoglobin in all three groups (all p< 0.001), but no between-group differences. Conclusion: The decrease in SmO2 in active muscles may reflect increased muscle oxygen extraction or reduced oxygen delivery during exercise. Blood flow redistribution may be reduced to the exercising muscle in the severe ILD group.
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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".