Toward Optimal End‐of‐Life Care for Patients with Advanced Chronic Obstructive Pulmonary Disease: Insights from a Multicentre Study
Bibliographic record
Abstract
BACKGROUND: Understanding patients' needs and perspectives is fundamental to improving end-of-life (EOL) care. However, little is known of what quality care means to patients who have advanced lung disease. OBJECTIVES: To describe ratings of importance and satisfaction with elements of EOL care, informational needs, decision-making preferences, obstacles to a preferred location of death, clinical outcomes, and health care use before and during an index hospital admission for patients who have advanced chronic obstructive pulmonary disease (COPD). METHODS: A questionnaire with regard to quality EOL care was administered to patients older than 55 years of age who had advanced medical disease in five Canadian teaching hospitals. RESULTS: For 118 hospitalized patients who had advanced COPD, the following items were rated as extremely important for EOL care: not being kept alive on life support when there is little hope for meaningful recovery (54.9% of respondents), symptom relief (46.6%), provision of care and health services after discharge (40.0%), trust and confidence in physicians (39.7%), and not being a burden on caregivers (39.6%). Compared with patients who had metastatic cancer, patients with COPD had lower (P<0.05) satisfaction with care, interest in information about prognosis, cardiopulmonary resuscitation or mechanical ventilation, and referral rates to palliative care, whereas use of acute care services was higher (P<0.05) for patients who had advanced COPD. CONCLUSION: Canadian patients who have advanced COPD identify several priorities for improving care. Avoidance of prolonged or unwanted life support requires more effective communication, decision making and goal setting. Patients also deserve better symptom control and postdischarge strategies to minimize perceived burdens on caregivers, emergency room visits and hospital admissions.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".