Multiple-breath washout as a lung function test in cystic fibrosis. a cystic fibrosis foundation workshop report
Bibliographic record
Abstract
The lung clearance index (LCI) is a lung function parameter derived from the multiple-breath washout (MBW) test. Although first developed 60 years ago, the technique was not widely used for many years. Recent technological advances in equipment design have produced gains in popularity for this test among cystic fibrosis (CF) researchers and clinicians, particularly for testing preschool-aged children. LCI has been shown to be feasible and sensitive to early CF lung disease in patients of all ages from infancy to adulthood. A workshop was convened in January 2014 by the North American Cystic Fibrosis Foundation to determine the readiness of the LCI for use in multicenter clinical trials as well as clinical care. The workshop concluded that the MBW text is a valuable potential outcome measure for CF clinical trials in preschool-aged patients and in older patients with FEV1 in the normal range. However, gaps in knowledge about the choice of device, gas, and standardization across systems are key issues precluding its use as a clinical trial end point in infants. Based on the current evidence, there are insufficient data to support the use of LCI or MBW parameters in the routine clinical management of patients with CF.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".