Patient preferences in severe COPD and asthma: a comprehensive literature review
Bibliographic record
Abstract
BACKGROUND: Management of chronic incurable diseases such as chronic obstructive pulmonary disease (COPD) and asthma is difficult. Incorporation of patient preferences is widely encouraged. PURPOSE: To summarize original research articles determining patient preference in moderate-to-severe disease. METHODS: Acceptable articles consisted of original research determining preferences for any aspect of care in patients with COPD/asthma. The target population included those with severe disease; however, articles were accepted if they separated outcomes by severity or if the majority had at least moderate-to-severe disease. We also accepted simulation research based on scenarios describing situations involving moderate-to-severe disease that elicited preferences. Two reviewers searched Medline and Embase for articles published from the date of inception of the databases until the end of November 2014, with differences resolved through consensus discussion. Data were tabulated and analyzed descriptively. RESULTS: About 478 articles identified, 448 were rejected and 30 analyzed. There were 25 on COPD and five on asthma. Themes identified as most important in COPD were symptom relief (dyspnea/breathlessness), a positive patient-physician relationship, quality-of-life impairments, and information availability. Patients strongly preferred sponsors' inhalers. At end-of-life, 69% preferred receiving CPR, 70% wanted noninvasive, and 58% invasive mechanical intervention. While patients with asthma preferred treatments that increased symptom-free days, they were willing to trade days without symptoms for a reduction in adverse events and greater convenience. Asthma patients were willing to pay for waking up once and not needing their inhaler over waking up once overnight and needing their inhaler. CONCLUSION: Few studies have examined patient preference in these diseases. More research is needed to fill in knowledge gaps.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".