<p>End-of-life care in individuals with respiratory diseases: a population study comparing the dying experience between those with chronic obstructive pulmonary disease and lung cancer</p>
Bibliographic record
Abstract
Purpose: Among individuals with COPD and/or lung cancer, to describe end-of-life health service utilization, costs, and place of death; to identify predictors of home palliative care use, and to assess benefits associated with palliative care use. Patients and methods: We conducted a retrospective population-based study using provincial linked health administrative data (Ontario, Canada) between 2010 and 2015. We examined health care use in the last 90 days of life in adults 35 years and older with physician-diagnosed COPD and/or lung cancer identified using a validated algorithm and the Ontario Cancer Registry, respectively. Four mutually exclusive groups were considered: (i) COPD only, (ii) lung cancer only, (iii) COPD and lung cancer, and (iv) neither COPD nor lung cancer. Multivariable generalized linear models were employed. Results: Of 445,488 eligible deaths, 34% had COPD only, 4% had lung cancer only, 5% had both and 57% had neither. Individuals with COPD only received less palliative care (20% vs 57%) than those with lung cancer only. After adjustment, people with lung cancer only were far more likely to receive palliative care (OR=4.22, 4.08-4.37) compared to those with neither diagnosis, while individuals with COPD only were less likely to receive palliative care (OR=0.82, 0.81-0.84). Home palliative care use was associated with reduced death and fewer days in acute care, and less cost, regardless of the diagnosis. Conclusion: Although individuals with lung cancer were much more likely to receive palliative care than those with COPD, both populations were underserviced. Results suggest greater involvement of palliative care may improve the dying experience of these populations and reduce costs.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".