Ten year survival by NYHA functional class in heart failure outpatients referred to specialized multidisciplinary heart failure clinics 1999 to 2011
Bibliographic record
Abstract
Background: Over the last decade, new heart failure treatments have been introduced and proven in large randomized trials. However, it is less clear if these advances are translated into regular clinical practice in both metropolitan and rural environments. The Canadian Heart Failure Network (CHFN) of 27 outpatient HF clinics enrolled and followed 16,683 HF patients referred from both academic and community centers in widely dispersed communities across Canada from 1999 to 2011. HF treatment was prescribed by the local physicians with access to national and international guidelines. Methods: Statistical analyses of the patient database were conducted on detailed patient management and outcomes. We describe the ten year survival of these national ambulatory HF outpatients by their NYHA class at CHFN first visit. Results: 16,683 HF patients were identified at their initial visit as ≥18 years of age with a documented NYHA class. 3,730 (22.4%) patients died during 10 year follow-up. The patient demographics were: age 64.8 (14.3) years, male/female 69/31%, ischemic/non ischemic 53/47%, years of HF 2.6 (4.6). At the time of their first CHFN outpatient visit, 13.2% were NYHA class I, 40.1% class II, 42.6% class III, and 4.1% class IV. Based on NYHA class and univariable associations, proportional hazard survival curves (Kaplan Meier) were derived (p<0.001). With NYHA class I as the reference, the hazard ratio for class II was 1.78 (CI's 1.54, 2.06), class III was 3.51 (3.05, 4.04), and class IV 5.74 (4.81, 6.85). Survival by NYHA Class Conclusions: Baseline NYHA class remains a powerful predictor of survival in this contemporary ambulatory HF population. However, treatment to target doses, repeated education, and close follow-up remain crucial to optimize clinical outcomes.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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, 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".