Incident opioid drug use and adverse respiratory outcomes among older adults with COPD
Bibliographic record
Abstract
We evaluated risk of adverse respiratory outcomes associated with incident opioid use among older adults with chronic obstructive pulmonary diseases (COPD).This was a retrospective population-based cohort study using a validated algorithm applied to health administrative data to identify adults aged 66 years and older with COPD. Inverse probability of treatment weighting using the propensity score was used to estimate hazard ratios comparing adverse respiratory outcomes within 30 days of incident opioid use compared to controls.Incident opioid use was associated with significantly increased emergency room visits for COPD or pneumonia (HR 1.14, 95% CI 1.00-1.29; p=0.04), COPD or pneumonia-related mortality (HR 2.16, 95% CI 1.61-2.88; p<0.0001) and all-cause mortality (HR 1.76, 95% CI 1.57-1.98; p<0.0001), but significantly decreased outpatient exacerbations (HR 0.88, 95% CI 0.83-0.94; p=0.0002). Use of more potent opioid-only agents was associated with significantly increased outpatient exacerbations, emergency room visits and hospitalisations for COPD or pneumonia, and COPD or pneumonia-related and all-cause mortality.Incident opioid use, and in particular use of the generally more potent opioid-only agents, was associated with increased risk for adverse respiratory outcomes, including respiratory-related mortality, among older adults with COPD. Potential adverse respiratory outcomes should be considered when prescribing new opioids in this population.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".