MRC chronic Dyspnea Scale: Relationships with cardiopulmonary exercise testing and 6-minute walk test in idiopathic pulmonary fibrosis patients: a prospective study
Bibliographic record
Abstract
BACKGROUND: Exertional dyspnea is the most prominent and disabling feature in idiopathic pulmonary fibrosis (IPF). The Medical Research Chronic (MRC) chronic dyspnea score as well as physiological measurements obtained during cardiopulmonary exercise testing (CPET) and the 6-minute walk test (6MWT) are shown to provide information on the severity and survival of disease. METHODS: We prospectively recruited IPF patients and examined the relationship between the MRC score and either CPET or 6MWT parameters known to reflect physiologic derangements limiting exercise capacity in IPF patients RESULTS: Twenty-five patients with IPF were included in the study. Significant correlations were found between the MRC score and the distance (r = -.781, p < 0.001), the SPO2 at the initiation and the end (r = -.542, p = 0.005 and r = -.713, p < 0.001 respectively) and the desaturation index (r = .634, p = 0.001) for the 6MWT; the MRC score and VO2 peak/kg (r = -.731, p < 0.001), SPO2 at peak exercise (r = -. 682, p < 0.001), VE/VCO2 slope (r = .731, p < 0.001), VE/VCO2 at AT (r = .630, p = 0.002) and the Borg scale at peak exercise (r = .50, p = 0.01) for the CPET. In multiple logistic regression analysis, the only variable independently related to the MRC is the distance walked at the 6MWT. CONCLUSION: In this population of IPF patients a good correlation was found between the MRC chronic dyspnoea score and physiological parameters obtained during maximal and submaximal exercise testing known to reflect ventilatory impairment and exercise limitation as well as disease severity and survival. This finding is described for the first time in the literature in this group of patients as far as we know and could explain why a simple chronic dyspnea score provides reliable prognostic information on IPF.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".