Associations between Patient-reported Outcomes and Death or Lung Transplant in Idiopathic Pulmonary Fibrosis. Data from the Idiopathic Pulmonary Fibrosis Prospective Outcomes Registry
Bibliographic record
Abstract
Abstract Rationale Progression of idiopathic pulmonary fibrosis (IPF) is accompanied by worsening of symptoms, exercise capacity, and health-related quality of life. However, the utility of patient-reported outcomes as predictors of mortality remains uncertain. Objectives To assess whether patient-reported outcomes are independently associated with mortality beyond clinical risk factors in patients with IPF. Methods Data from the observational IPF Prospective Outcomes Registry were used to examine associations between patient-reported outcomes at enrollment and the composite outcome of death or lung transplant in the following year. Associations were examined using univariable models and models adjusted for age and clinical variables that have been associated with death or lung transplant in patients with IPF in this cohort (oxygen use, forced vital capacity % predicted, and diffusing capacity of the lungs for carbon monoxide % predicted at enrollment). Results Among 662 patients, 45 died and 12 underwent lung transplant over 1 year. In the model adjusted for age and clinical variables that were associated with death or lung transplant, worse scores on the St. George’s Respiratory Questionnaire (SGRQ) total score (hazard ratio [HR], 1.22 [95% confidence interval (CI), 1.01–1.48] per 10-point increase), SGRQ activity score (HR, 1.25 [95% CI, 1.02–1.54] per 10-point increase) and SGRQ symptoms score (HR, 1.17 [95% CI, 1.01–1.36] per 10-point increase) were associated with death or lung transplant over 1 year. Conclusions Patient-reported outcomes that assess symptoms and physical activity are independently associated with mortality in patients with IPF.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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".