Transition of transplant patients with cystic fibrosis to adult care: today's challenges
Bibliographic record
Abstract
One of the most trying ordeals for patients with cystic fibrosis is moving from one care setting to another. When the patient is facing the crisis of failing health and the need for lung transplantation, the transition can seem even more overwhelming. In Toronto, patients are transferred from pediatric to adult care at age 18. Moving a teenager with cystic fibrosis to the adult system presents many challenges, and even greater challenges arise when the patient has received a lung transplant or is awaiting one. Two pediatric and adult cystic fibrosis teams have worked closely with the lung transplant teams to create a smooth transition system. This article outlines both programs and presents a case study to explore the challenges for the teams in deciding the best place to meet the needs of the patients and their families. These families offer us a look at coping with change at a time of great stress and at how we as healthcare providers can support them through the system.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".