mMRC dyspnoea scale indicates impaired quality of life and increased pain in patients with idiopathic pulmonary fibrosis
Bibliographic record
Abstract
This study was undertaken to investigate idiopathic pulmonary fibrosis (IPF) patients' health-related quality of life (HRQoL) and symptoms in a real-life cross-sectional study. Our secondary aim was to create a simple identification method for patients with increased need for palliative care by studying the relationship between modified Medical Research Council (mMRC) dyspnoea scale, HRQoL and symptoms. We sent a self-rating HRQoL questionnaire (RAND-36) and modified Edmonton Symptom Assessment Scale (ESAS) to 300 IPF patients; 84% of the patients responded to these questionnaires. The most prevalent (>80%) symptoms were tiredness, breathlessness, cough and pain in movement. An increasing mMRC score showed a linear relationship (p<0.001) to impaired HRQoL in all dimensions of RAND-36 and the severity of all symptoms in ESAS. Dimensions of RAND-36 fell below general population reference values in patients with mMRC score ≥2. The intensity of pain in movement (p<0.001) and at rest (p=0.041), and the prevalence of chest pain (p<0.001) had a positive linear relationship to increased mMRC score. An increasing mMRC score reflects impaired HRQoL and a high symptom burden. In clinical practice, the mMRC scale could be used for screening and identification of IPF patients with increased need for palliative care.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".