Lung Clearance Index and Structural Lung Disease on Computed Tomography in Early Cystic Fibrosis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
RATIONALE: The lung clearance index is a measure of ventilation distribution derived from the multiple-breath washout technique. It has been suggested as a surrogate for chest computed tomography to detect structural lung abnormalities in individuals with cystic fibrosis (CF); however, the associations between lung clearance index and early structural lung disease are unclear. OBJECTIVES: We assessed the ability of the lung clearance index to reflect structural lung disease on the basis of chest computed tomography across the entire pediatric age range. METHODS: Lung clearance index was assessed in 42 infants (ages 0-2 yr), 39 preschool children (ages 3-6 yr), and 38 school-age children (7-16 yr) with CF before chest computed tomography and in 72 healthy control subjects. Scans were evaluated for CF-related structural lung disease using the Perth-Rotterdam Annotated Grid Morphometric Analysis for Cystic Fibrosis quantitative outcome measure. MEASUREMENTS AND MAIN RESULTS: In infants with CF, lung clearance index is insensitive to structural disease (κ = -0.03 [95% confidence interval, -0.05 to 0.16]). In preschool children with CF, lung clearance index correlates with total disease extent. In school-age children, lung clearance index correlates with extent of total disease, bronchiectasis, and air trapping. In preschool and school-age children, lung clearance index has a good positive predictive value (83-86%) but a poor negative predictive value (50-55%) to detect the presence of bronchiectasis. CONCLUSIONS: These data suggest that lung clearance index may be a useful surveillance tool to monitor structural lung disease in preschool and school-age children with CF. However, lung clearance index cannot replace chest computed tomography to screen for bronchiectasis in this 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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it