Research priorities to address the global burden of chronic obstructive pulmonary disease (COPD) in the next decade
Bibliographic record
Abstract
BACKGROUND: The global prevalence of chronic obstructive pulmonary disease (COPD) has increased markedly in recent decades. Given the scarcity of resources available to address global health challenges and respiratory medicine being relatively under-invested in, it is important to define research priorities for COPD globally. In this paper, we aim to identify a ranked set of COPD research priorities that need to be addressed in the next 10 years to substantially reduce the global impact of COPD. METHODS: We adapted the Child Health and Nutrition Research Initiative (CHNRI) methodology to identify global COPD research priorities. RESULTS: 62 experts contributed 230 research ideas, which were scored by 34 researchers according to six pre-defined criteria: answerability, effectiveness, feasibility, deliverability, burden reduction, and equity. The top-ranked research priority was the need for new effective strategies to support smoking cessation. Of the top 20 overall research priorities, six were focused on feasible and cost-effective pulmonary rehabilitation delivery and access, particularly in primary/community care and low-resource settings. Three of the top 10 overall priorities called for research on improved screening and accurate diagnostic methods for COPD in low-resource primary care settings. Further ideas that drew support involved a better understanding of risk factors for COPD, development of effective training programmes for health workers and physicians in low resource settings, and evaluation of novel interventions to encourage physical activity. CONCLUSIONS: The experts agreed that the most pressing feasible research questions to address in the next decade for COPD reduction were on prevention, diagnosis and rehabilitation of COPD, especially in low resource settings. The largest gains should be expected in low- and middle-income countries (LMIC) settings, as the large majority of COPD deaths occur in those settings. Research priorities identified by this systematic international process should inform and motivate policymakers, funders, and researchers to support and conduct research to reduce the global burden of COPD.
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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 | 0.195 | 0.166 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".