Improved survival albeit with persistent disparities in prognosis for people with cystic fibrosis in European countries
Bibliographic record
Abstract
Cystic fibrosis (CF), an autosomal recessive disease related to mutations in the gene encoding for the cystic fibrosis transmembrane conductance regulator (CFTR) protein, is the most prevalent severe genetic disease in Caucasian populations [1]. Although the disease affects multiple organs, respiratory disease is the major manifestation of CF and is often responsible for premature death [2], which often occurred in the first years of life before the implementation of modern CF care [3]. Over the past decades, progress in therapeutic management has resulted in a dramatic improvement in the prognosis of people with CF [4]. In a study published more than 20 years ago, Fogarty et al . [5] compared median age at death in seven countries (USA, and Australasian and European countries) and reported that median age at death improved from 8 years in 1974 to 21 years in 1994, albeit with marked differences between countries. More recent studies have confirmed improvement in median age of survival, which was 40.6 years in US patients and 50.9 years in Canadian patients, in a study that used data from between 2009 and 2013 [6]. In European countries, contemporary studies have reported increases in the number of adults with CF [7, 8], with a better prognosis in countries belonging to the European Union (EU) than in those outside of the EU [7, 8], mostly located in Eastern Europe, in which access to appropriate CF care is less available [9]. Collectively these data suggest that prognosis improvement in patients with CF is heavily dependent on the quality of the CF healthcare system. Survival is improving for people with cystic fibrosis in European countries albeit with persistent disparities in prognosis among countries
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".