Clinical Characteristics and Predictors of Reduced Survival for Adult-diagnosed Cystic Fibrosis. Analysis of the Canadian CF Registry
Bibliographic record
Abstract
RATIONALE: Individuals diagnosed with cystic fibrosis (CF) as adults represent a growing subpopulation of CF cases, but there are limited studies describing their characteristics and prognosis. OBJECTIVES: The objectives of this study were to describe the clinical characteristics of individuals with adult-diagnosed CF, estimate survival rates in this population, and identify clinical predictors of reduced survival at baseline. METHODS: The Canadian CF Patient Registry was used to identify patients with CF who were ≥18 years of age at diagnosis and received a diagnosis between 1990 and 2014. Clinical characteristics were described and the Kaplan-Meier method was used to estimate lung-transplant-free survival. Multivariable Cox regression analysis and adjusted survival curves were employed to identify important predictors of reduced survival at the time of diagnosis (i.e., baseline) and to produce adjusted effects. RESULTS: A total of 362 adults were diagnosed with CF during the study period. The median follow-up time was 7.7 years and 48 individuals experienced an event (15 transplants, 33 deaths without transplant). The median age at diagnosis was 34.3 years, with the majority of individuals presenting with pulmonary and/or gastrointestinal symptoms (71%). Lung-transplant-free survival was 88% at 10 years and 86% at 15 years. Age at diagnosis (hazard ratio [HR], 1.24 per 5-year increase, 95% confidence interval [CI], 1.09-1.43), diabetes (HR, 4.19; 95% CI, 1.35-13.01), and lung function (HR, 1.35 per 5% decrease in forced expiratory volume in 1 second % predicted; 95% CI, 1.24-1.48) at baseline were important predictors of reduced survival. CONCLUSIONS: CF care providers can use this information to inform individuals who received a diagnosis of CF as adults about their prognosis and to guide the necessity of treatments, specifically with regard to those who are at high risk for a worse prognosis.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".