Prevalence and prognostic impact of physical frailty in interstitial lung disease: A prospective cohort study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Physical frailty is associated with increased mortality and hospitalizations in older adults. We describe the prevalence of physical frailty and its prognostic impact in patients with a spectrum of fibrotic interstitial lung disease (ILD). METHODS: Patients with fibrotic ILD at the McMaster University ILD programme were prospectively followed up from November 2015 to March 2020. Baseline data were used to classify patients as non-frail (score = 0), pre-frail (score = 1-2) or frail (score = 3-5) based on modified Fried physical frailty criteria. The association between physical frailty and mortality was assessed using time-to-event models, adjusted for age, sex, lung function and diagnosis using the ILD Gender-Age-Physiology (ILD-GAP) score. RESULTS: We included 463 patients (55% male, mean [SD] age 68 [11] years); 82 (18%) were non-frail, 258 (56%) pre-frail and 123 (26%) frail. The most common ILD diagnoses were idiopathic pulmonary fibrosis (n = 183, 40%) and connective tissue disease-associated-ILD (n = 79, 17%). Mean time since diagnosis was 2.7 ± 4.6 years. There were 56 deaths within the median follow-up of 1.71 (interquartile range [IQR] 1.24, 2.31) years. Both frail and pre-frail individuals had a higher risk of death compared to those categorized as non-frail at baseline (adjusted hazard ratio [aHR] 4.14, 95% CI 1.27-13.5 for pre-frail and aHR 4.41, 95% CI 1.29-15.1 for frail). CONCLUSION: Physical frailty is prevalent in patients with ILD and is independently associated with an increased risk of death. Assessment of physical frailty provides additional prognostic value to recognized risk scores such as the ILD-GAP score, and may present a modifiable target for intervention.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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".