Development of a Decision Aid for Adult Cystic Fibrosis Patients considering Referral for Lung Transplantation
Bibliographic record
Abstract
Context Most adults with cystic fibrosis are eventually required to make a decision about referral for lung transplantation. Objective To identify the decisional needs of these patients and to develop a decision aid to address these needs. Methods A comprehensive review of the literature, a review of Canadian transplant statistics from 2002 to 2006, and a self-assessment survey of patients who had already made a decision about referral were performed to identify the decisional needs of patients. A decision aid was then developed and evaluated by an expert panel of health care professionals and patients. Results Transplant referral patterns vary widely among Canadian cystic fibrosis clinics. Canadian patients with cystic fibrosis who were not residing in transplant centers between 2002 and 2006 were significantly less likely to undergo lung transplants ( P < .001). Decisional needs identified by patients included wanting more information on (1) relocation to the transplant center, (2) the benefits and risks of surgery, and (3) how to cope with anxiety and depression when making the decision. In response to these identified needs, a decision aid for lung transplantation was developed. A panel of health care professionals and patients reviewed the decision aid and agreed that the content was appropriate, easy to understand, and unbiased. Conclusion The decisional needs of patients with cystic fibrosis who are considering lung transplantation are not being addressed in Canadian cystic fibrosis clinics, especially in clinics outside of transplant centers. An evidence-based decision aid could serve as a useful tool to help address these needs.
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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 | 0.021 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".