Clinical implications of frailty assessed in hospitalized patients with acute-exacerbation of interstitial lung disease
Bibliographic record
Abstract
Background Approximately 50% of patients with interstitial lung disease (ILD) experience frailty, which remains unexplored in acute exacerbations of ILD (AE-ILD). A better understanding may help with prognostication and resource planning. We evaluated the association of frailty with clinical characteristics, physical function, hospital outcomes, and post-AE-ILD recovery. Methods Retrospective cohort study of AE-ILD patients (01/2015–10/2019) with frailty (proportion ≥0.25) on a 30-item cumulative-deficits index. Frail and non-frail patients were compared for pre- and post-hospitalization clinical characteristics, adjusted for age, sex, and ILD diagnosis. One-year mortality, considering transplantation as a competing risk, was analysed adjusting for age, frailty, and Charlson Comorbidity Index (CCI). Results 89 AE-ILD patients were admitted (median: 67 years, 63% idiopathic pulmonary fibrosis). 31 were frail, which was associated with older age, greater CCI, lower 6-min walk distance, and decreased independence pre-hospitalization. Frail patients had more major complications (32% vs 10%, p = .01) and required more multidisciplinary support during hospitalization. Frailty was not associated with 1-year mortality (HR: 0.97, 95%CI: [0.45–2.10]) factoring transplantation as a competing risk. Conclusions Frailty was associated with reduced exercise capacity, increased comorbidities and hospital complications. Identifying frailty may highlight those requiring additional multidisciplinary support, but further study is needed to explore whether frailty is modifiable with AE-ILD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".