Responses to exercise in systemic sclerosis‐associated interstitial lung disease
Bibliographic record
Abstract
Abstract Introduction Pulmonary complications in systemic sclerosis (SSc) significantly increase morbidity and mortality. Our aim was to determine the factors limiting exercise capacity in SSc patients with and without interstitial lung disease (ILD), and to identify and quantify abnormalities during exercise that might assist in clinical assessment of this complication. Methods Fifteen patients with SSc and ILD (SSc‐ILD) were compared with 10 patients with SSc without ILD and 9 age‐ and sex‐matched normal volunteers. Subjects performed symptom‐limited incremental treadmill exercise with online measurement of respiratory gas exchange, arterial blood gas sampling and measurement of neurohormones in venous blood. Results Patients with SSc‐ILD had lower exercise capacity than SSc patients without ILD or normal subjects (peak oxygen consumption (PV̇O2) (17.1 [4.2] vs. 22.0 [4.7] and 23.0 [5.4] ml kg−1 min−1, respectively, mean [SD], p < 0.01 ANOVA), but PV̇O2 did not correlate with static pulmonary function measurements. Ventilatory equivalent for CO2 (V̇E/V̇CO2; nadir) was higher in SSc‐ILD patients than the other two groups (36.6 [8.0] vs. 29.9 [4.4] and 30.0 [2.5], p < 0.005) as were peak exercise dead‐space tidal volume ratio (0.44 [0.06] vs. 0.26 [0.09] and 0.26 [0.05], p < 0.001) and peak exercise alveolar–arterial difference (28.9 [16.9] vs. 18.8 [14.0] and 11.5 [6.9] mmHg, p < 0.05). Atrial natriuretic peptide was elevated in both SSc patient groups. Conclusions SSc‐ILD results in lower exercise capacity than SSc without ILD, and abnormalities of gas exchange are seen. The possible use of cardiopulmonary exercise testing to identify disease and quantify impairment in SSc‐ILD merits further study.
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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".