Cystic fibrosis foundation consensus statements for the care of cystic fibrosis lung transplant recipients
Bibliographic record
Abstract
Cystic fibrosis (CF) is the indication for transplantation in approximately 15% of recipients worldwide, and Cystic Fibrosis Lung Transplant Recipients (CFLTRs) have excellent long-term outcomes. Yet, CFLTRs have unique comorbidities that require specialized care. The objective of this document is to provide recommendations to CF and lung transplant clinicians for the management of perioperative and underlying comorbidities of CFLTRs and the impact of transplantation on these comorbidities. The Cystic Fibrosis Foundation (CFF) organized a multidisciplinary committee to develop CF Lung Transplant Clinical Care Recommendations. Three workgroups were formed to develop focused questions. Following a literature search, consensus recommendations were developed by the committee members based on literature review, committee experience and iterative revisions, and in response to public comment. The committee formulated 32 recommendation statements in the topics related to infectious disease, endocrine, gastroenterology, pharmacology, mental health and family planning. Broadly, the committee recommends close coordination of care between the lung transplant team, the cystic fibrosis care center, and specialists in other disciplines with experience in the care of CF and lung transplant recipients. These consensus statements will help lung transplant providers care for CFLTRs in order to improve post-transplant outcomes in this population.
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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 | 0.059 | 0.093 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".