NOTE-FY Project: International stakeholder engagement on research in nocturnal oxygen therapy for pulmonary fibrosis
Bibliographic record
Abstract
Background: Nocturnal hypoxemia (NH) is common in pulmonary fibrosis (PF). Current practice and guideline recommendations for assessing and treating NH lack robust evidence. This study aimed to establish a global perspective on research priorities and outcome measures of importance in nocturnal oxygen therapy for PF. Methods: People with PF and healthcare professionals (HCPs) including clinicians and researchers with expertise in PF, sleep medicine, and oxygen therapy, were recruited internationally to participate in an online survey followed by virtual focus groups. Results: 68 people with PF and 73 HCPs from 29 countries completed the survey, with 14 and 36 joining the focus groups, respectively. Top research questions from people with PF were 1) treatment effects of NH on symptoms, 2) safety and tolerability of nocturnal oxygen therapy, and 3) patient and clinician awareness of the significance of NH. Top HCP research questions were 1) effects of treating NH on mortality, quality of life, and pulmonary hypertension (PH), and 2) thresholds for screening and/or initiating treatment of NH in PF. For outcome measures of importance, both groups prioritised quality of life. In addition, people with PF highly ranked forced vital capacity, nocturnal oxygenation status, and apnoea-hypopnoea index, while HCPs selected long-term sequelae such as survival and development of PH. Impact of NH and sleep disturbance on cognitive performance was raised by people with PF as an additional key research topic, which was agreed by HCPs. Conclusion: This study provides important insights into stakeholders' priorities to guide research on the evaluation and treatment of NH in PF.
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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 | 0.107 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.033 | 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".