Analysis of a large cohort of cystic fibrosis patients with severe liver disease indicates lung function decline does not significantly differ from that of the general cystic fibrosis population
Bibliographic record
Abstract
Previous reports of lung function in cystic fibrosis (CF) patients with liver disease have shown worse, similar, or even better forced expiratory volume in 1 second (FEV1), compared to CF patients without liver disease. Varying definitions of CF liver disease likely contribute to these inconsistent relationships reported between CF lung function and liver disease. We retrospectively evaluated spirometric data in 179 subjects (62% male; 58% Phe508del homozygous) with severe CF liver disease (CFLD; defined by presence of portal hypertension due to cirrhosis). FEV1 values were referenced to both a normal population (FEV1% predicted) and CF population (CF-specific FEV1 percentile). We utilized a linear mixed model with repeated measures to assess changes in lung function (before and after diagnosis of CFLD), relative to both the normal and CF populations. At diagnosis of CFLD, the mean FEV1 was 81% predicted, or at the 53rd percentile referenced to CF patients without CFLD. There was a significant difference in post-CFLD slope compared to pre-CFLD slope (post-pre) using FEV1% predicted (-1.94, p-value < 0.0001). However, there was insignificant evidence of this difference using the CF-specific FEV1 percentile measure (-0.99, p-value = 0.1268). Although FEV1% predicted values declined in patients following CFLD diagnosis, there was not significant evidence of lung function decline in CF-specific FEV1 percentiles. Thus, the observed study cohort indicates diagnosis of severe CFLD was not associated with worsened CF lung disease when compared to a large CF reference population.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".