Exploring reduced pulmonary exacerbation rates in cystic fibrosis: a pandemic or modulator effect?
Bibliographic record
Abstract
Background: The impact of elexacaftor-tezacaftor-ivacaftor (ETI) on pulmonary exacerbations (PEx) in cystic fibrosis (CF) is difficult to estimate since ETI availability coincided with the COVID-19 pandemic. Later access to ETI in Canada created a natural experiment to adjust for the impact of the pandemic on PEx rates. The objective for this study was to compare PEx rates pre- and post-ETI in the USA using Canada as a control group. Methods: This retrospective cohort study utilised data from the US and Canadian CF patient registries from 1 January 2015 to 31 December 2022. Individuals with at least one F508del mutation and ≥12 years old were followed. Poisson regression was used to estimate PEx rates per 100 person-years of follow-up. A difference-in-difference approach was used to estimate the impact of ETI alone. Results: Longitudinal data from 22 590 US individuals and 3271 Canadians were analysed. Pre-pandemic, the PEx rate was significantly higher in the USA (70.6, 95% CI 70.1-71.2) compared to Canada (53.1, 95% CI 51.9-54.3). During the COVID-19 pandemic, the PEx rate decreased to 30.2 (95% CI 28.8-31.8) in Canada; whereas in the USA, the rates decreased to 14.7 (95% CI 14.3-15.1). After adjusting for covariates, the ETI effect was 2.48 times (95% percentile interval 2.26-2.70) that of the pandemic effect. Conclusions: Public health measures imposed during the pandemic resulted in a reduction in the number of PEx for both countries; however, the impact of ETI on reducing the rate of PEx was more than double the effect of the COVID-19 pandemic.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| 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".