Functional ageing in fibrotic interstitial lung disease: the impact of frailty on adverse health outcomes
Bibliographic record
Abstract
BACKGROUND: Accelerated biological and functional ageing is common in fibrotic interstitial lung disease (ILD); however, their impact on adverse health outcomes has not been evaluated in this population. METHODS: Patients were prospectively recruited from a specialised ILD clinic. Functional ageing was determined by frailty index and biological age by measurement of absolute telomere length (aTL) from patients' peripheral blood leukocytes. Adverse health outcomes included health-related quality of life (St George's Respiratory Questionnaire), number and length of respiratory and non-respiratory hospitalisations, medication tolerability and time to death or lung transplantation. Multivariable models were used to determine the risks and rates of adverse health outcomes associated with the frailty index and aTL. RESULTS: 540 patients with fibrotic ILD, including 100 with idiopathic pulmonary fibrosis (IPF), provided 749 frailty index assessments, with 189 patients providing blood samples. The frailty index was strongly associated with quality of life, rate of hospitalisation, time to hospital discharge and mortality, including adjustment for age, sex, disease severity and IPF diagnosis. Mortality prognostication was improved by the addition of the frailty index to commonly used clinical parameters and previously validated composite indices. Conversely, aTL was not associated with most adverse health outcomes. The effect of chronological age on outcomes was mediated primarily by the frailty index, and to a lesser extent by aTL. CONCLUSIONS: Functional ageing is associated with adverse health outcomes in patients with fibrotic ILD, indicating the need for consideration of the individual functional age into clinical decision-making.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".