Opioids in COPD: a cause of death or a marker of illness severity?
Bibliographic record
Abstract
We thank J. Downar and colleagues for their interest in our study [1] and their contributions to this important clinical issue. Downar and colleagues view our findings through the lens of palliative medicine. We recognise the role of opioids for symptom relief among individuals with chronic obstructive pulmonary disease (COPD) as part of end-of-life care. We intentionally excluded individuals who were receiving palliative care from our study, acknowledging that “goals of care and indications for opioid use may differ in this context” [1]. Our goal was instead to evaluate, from a respiratory safety perspective, the use of opioid drugs among the broader older adult COPD population. Our previous work on opioids in COPD [2] suggests that musculoskeletal pain is probably the main reason for opioid drug receipt in the older adult COPD population rather than respiratory symptoms. Opioids combined with non-opioid agents, like acetaminophen or aspirin, accounted for close to 90% of opioid use among older adults with COPD [2]. These combination opioid/non-opioid agents are unlikely to be used in end-of-life care and their use more likely reflects treatment of musculoskeletal pain, which commonly occurs in COPD [3, 4]. Opioids were also less commonly used among individuals with COPD with frequent exacerbations [2] and this group is more likely to be troubled by refractory respiratory symptoms. Less common use of opioids by these individuals supports the argument that opioids are prescribed for reasons other than palliation of respiratory symptoms. New opioid drug use is associated with increased respiratory-related morbidity and mortality in nonpalliative COPD
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".