Anchoring Patient Voices to Shape the Future of Patient-reported Outcomes
Bibliographic record
Abstract
Patients with interstitial lung disease (ILD) frequently experience symptoms such as cough, dyspnea, and fatigue.These symptoms not only affect the patient's quality of life (QOL) (1) but also have prognostic significance in predicting mortality (2).Immunosuppressive treatments for inflammatory ILD may improve dyspnea (3), whereas diseasemodifying antifibrotic medications slow disease progression in fibrotic ILD without significantly improving QOL (4, 5).From a patient perspective, this can mean taking medications that do not alleviate symptoms and may cause considerable side effects.To date, the only interventions shown to improve QOL in ILD are ambulatory oxygen (6), pulmonary rehabilitation, and morphine therapy for cough (7), none of which prolong survival in this progressive disease.Recently, there has been a shift in the research community to ensure studies not only assess therapeutic efficacy on objective clinical outcomes, such as forced vital capacity, but also incorporate patient voices and priorities.A recent mixed-methods
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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 | 0.039 | 0.206 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.062 | 0.070 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".