Factors associated with opioid dispensation for patients with COPD and lung cancer in the last year of life: A retrospective analysis
Bibliographic record
Abstract
BACKGROUND: For patients in late stages of chronic obstructive pulmonary disease (COPD), dyspnea is often refractory to conventional treatment. We know little about the use of opioids in ameliorating dyspnea in this population. In this study we explored factors associated with opioid dispensation within the last year of life and differences in opioid dispensation for persons with lung cancer or COPD. METHODS: In this retrospective cohort study we used administrative health data gained from 1,035 residents of Saskatchewan, Canada to examine patterns of community opioid dispensation in the last year of life. Factors associated with opioid use were determined using multiple logistic regression. RESULTS: When compared with those with lung cancer, fewer patients with COPD were given opioids within the last week of life; the last month of life, and the last 3 months of life. After adjusting for relevant predictors, patients with lung cancer were more than twice as likely as those with COPD to fill prescriptions for the following: morphine (odds ratio [OR] 2.36, 95% confidence interval [CI]: 1.52-3.67); hydromorphone (OR 2.69, 95% CI: 1.53-4.72); transdermal fentanyl (OR 2.25, 95% CI: 1.28-3.98); or any of these opioids (OR 2.61, 95% CI: 1.80-3.80). CONCLUSION: These opioids are dispensed only for a small proportion of patients with COPD at the end of their lives. Future researchers could explore the efficacy and safety of opioid use for patients with advanced COPD, and whether their limited use is justified.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".