Fraction of exhaled nitric oxide increases in children treated with elexacaftor-tezacaftor-ivacaftor
Bibliographic record
Abstract
Introduction: Airway nitric oxide (FENO) in people with cystic fibrosis (CF) is lower than normal and ivacaftor results in an early and sustained increase in FENO in treated individuals (Grasemann H et al. Eur Respir J. 2020). The effect of elexacaftor-tezacaftor-ivacaftor (ETI) on airway NO is not known. We aimed to study the effect of ETI on FENO in children with CF. Methods: This is a prospective observational study in children with CF 6-18 years old and started on ETI therapy. The study was approved by the local REB. FENO was measured before and 1-3 months after ETI initiation at regular clinic visits using a Niox Vero device. Comparisons between pre and post were made with t-test or Wilcoxon test, where appropriate. Results: Thirty-eight patients (median 14.8 yrs, IQR 11.5-16.9) were included, 21 were male, 24 F508del homozygous, 28 were naïve to CFTR modulator therapy, and 10 switched from lumacaftor-ivacaftor to ETI. Baseline and follow-up FENO (median, IQ range) values are shown in the table. There was no correlation between FENO or changes in FENO with sweat chloride levels or pulmonary function (FEV1). Conclusions: ETI results in an increase in FENO in treated children with CF 1-3 months after initiation of therapy. The increase in FENO seems more robust in F508del/F508del patients naïve to CFTR modulator therapy compared to those switched from lumacaftor-ivacaftor or those with a single F508del allele.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".