Survival in Cystic Fibrosis: Trends, Clinical Factors, and Prediction Models
Bibliographic record
Abstract
Cystic fibrosis (CF) is an autosomal recessive genetic disease that results in multiple medical complications, and ultimately decreased survival of affected patients. Due to multiple advances in early diagnosis, nutrition, and aggressive treatment of complications, survival of these patients has improved dramatically in the past 40 years. However, despite improved care, patients still die at a relatively young age, most commonly due to respiratory failure. In order to extend survival, the sickest patients with CF are considered for lung transplant. An accurate understanding of a CF patient's expected survival and health trajectory is critical for appropriate patient selection and timing of transplantation. This review discusses how survival in CF has changed over the past four decades, the clinical factors that are associated with survival, as well as the use of models to predict survival and optimal timing of lung transplant in patients with CF.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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".