Survival comparison of patients with cystic fibrosis in Canada and the <scp>USA</scp>
Bibliographic record
Abstract
National Cystic Fibrosis registries have found a striking difference in median survival between Canada and the USA (Fig. 1).1 Median survival currently favours Canada by over 10 years; for 2009–2013, Canada 50.9 years versus USA 40.6 years. The adjusted risk for death was 34% lower in Canada than in the USA; hazard ratio = 0.66 (95% confidence interval (CI) 0.54, 0.81; P = 0.002. North American Registry Data are based on high quality, prospective data and very large sample sizes; Canada, n = 5941; USA, n = 45 448. This difference is not explained by differences in medication use, such as long-term oral azithromycin, nor mucolytics (hypertonic saline and dornase-alpha are used significantly more in the USA). Nor is it explained by rates of Pseudomonas colonisation, nor deltaF508 homozygosity, which are similar in both countries. Lung transplantation rates may partially explain the difference, with 10.3% of patients transplanted in Canada, compared to 6.5% in the USA. The authors hypothesise that the most likely explanation is the substantial differences in both health care delivery and insurance status. Although Canadian patients have universal health cover, US patients have multiple categories of insurance – including no cover. Indeed, US patients with either ‘unknown’ or no health insurance had the worst survival rates; hazard ratio = 0.23 (95% CI 0.14, 0.37; P < 0.001). The authors conclude that these survival differences warrant further research.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".