Standards for the care of people with cystic fibrosis; establishing and maintaining health
Bibliographic record
Abstract
This is the second in a series of four papers updating the European Cystic Fibrosis Society (ECFS) standards for the care of people with CF. This paper focuses on establishing and maintaining health. The guidance is produced using an evidence-based framework and with wide stakeholder engagement, including people from the CF community. Authors provided a narrative description of their topic and statements, which were more directive. These statements were reviewed by a Delphi exercise, achieving good levels of agreement from a wide group for all statements. This guidance reinforces the importance of a multi-disciplinary CF team, but also describes developing models of care including virtual consultations. The framework for health is reinforced, including the need for a physically active lifestyle and the strict avoidance of all recreational inhalations, including e-cigarettes. Progress with cystic fibrosis transmembrane conductance regulator (CFTR) modulator therapy is reviewed, including emerging adverse events and advice for dose reduction and interruption. This paper contains guidance that is pertinent to all people with CF regardless of age and eligibility for and access to modulator therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".