The clinical frailty scale is associated with progression of fibrotic interstitial lung disease – a multicentre cohort study.
Bibliographic record
Abstract
Background: Previous studies have shown the importance of frailty in patients with fibrotic interstitial lung disease (ILD). We aimed to determine whether the Clinical Frailty Scale (CFS) is associated with disease progression in this population. Methods: Patients were included from the prospective multicenter Canadian Registry for Pulmonary Fibrosis. The CFS was assessed using information from initial visits. Joint models (longitudinal mixed effect and Cox proportional hazards submodels) accounting for informative dropout due to death or lung transplant were used to compare trajectories of forced vital capacity (FVC), diffusing capacity for CO (DLCO) and 6-minute walk distance (6MWD) %-predicted in fit (CFS 1-3) vs vulnerable/frail (CFS ≥4) patients over 5 years from CFS assessment. Results: 858 patients were classified as fit (54%) and 729 as vulnerable or frail (46%). Mean age±SD was 64±12 in fit and 68±12 years in vulnerable/frail patients. FVC, DLCO, and 6MWD %-predicted at baseline were 78±20, 57±20 and 82±24 in fit vs 68±21, 45±18 and 63±22 in vulnerable/frail patients, respectively. Fit versus vulnerable/frail patients had the following mean annual change (95% CI): FVC -1.55 (-2.04 to -1.15) vs -2.12 (-3.11 to -1.24), p=0.03; DLCO -1.96 (-2.44 to -1.57) vs -2.42 (-3.48 to -1.93), p=0.20; and 6MWD -2.23 (-2.89 to -1.60) vs -3.96 (-5.69 to -2.31), p=0.001. Differences in trajectories remained similar with adjustment for age, sex, body mass index, ever smoking, ILD diagnosis, and drug treatment. Conclusion: The simple and practical CFS might contribute to estimation of pulmonary and functional disease progression in patients with fibrotic ILD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".