Prognostic implications of NYHA class and NT-proBNP levels in mild heart failure: a PARADIGM-HF analysis
Bibliographic record
Abstract
Abstract Background Treatment recommendations for heart failure (HF) with reduced ejection fraction are primarily centered on New York Heart Association (NYHA) classification, such that apparently asymptomatic patients might not be eligible for disease-modifying therapies. NYHA classification, however, may be particularly limited to discriminate mild forms of HF. Purpose The present study aimed to determine the relationship between NYHA classification and an objective measure of HF severity (N-terminal pro–B-type natriuretic peptide [NT pro-BNP]), and their association with long-term prognosis in the PARADIGM-HF trial. Methods We compared PARADIGM-HF patients classified as NYHA class I, II, and III at randomization (NYHA class IV patients or with unavailable NYHA class were excluded [n=73]). We present kernel density estimation (KDE) plots–a non-parametric way to describe the underlying distribution of a variable–to compare NT-proBNP levels across NYHA classes. Logistic regression and the area under the receiver operating characteristic curve (AUC) were used to assess the ability to predict a patient's NYHA class using NT-proBNP levels. Time-to-event data were calculated with Kaplan–Meier estimates and NYHA class were further stratified by median baseline NT-proBNP (< or ≥1600 pg/ml). The primary outcome was cardiovascular death or first HF hospitalization. Results 8326 patients were included in this analysis (median age, 64 years; women, 22%; and median left ventricular ejection fraction, 30%). Of 389 patients classified as NYHA class I at randomization, 228 (59%) changed functional class during the first year after randomization. For log-transformed NT-proBNP, KDE overlapped substantially across NYHA classes (Figure 1A). NT-proBNP levels were a poor predictor of NYHA classification: for NYHA class I vs. II, AUC (95% confidence interval [CI]) was 0.51 (0.48–0.54); for NHYA I vs. III, 0.57 (0.54–0.60); and for NYHA II vs. III, 0.56 (0.54–0.57). NYHA class III patients displayed a distinctively higher rate of cardiovascular deaths or first HF hospitalizations (Figure 1B). NYHA class I and II patients revealed lower event rates that were not significantly different (NYHA II vs. I, HR 1.24 [0.97–1.58]). Stratification by NT-proBNP levels identified subgroups with distinctive risk, such that NYHA I patients with high NT-proBNP levels (n=175) had a higher event rate than patients with low NT-proBNP with any NYHA class (Figure 1C). Conclusion NYHA class I and II patients overlapped substantially in objective HF measures and long-term prognosis. NYHA classification remains a powerful predictor of cardiovascular events but might be limited to differentiate mild forms of HF, as apparently asymptomatic patients based on physician-defined functional class might become symptomatic within a year and conceal subjects at substantial risk for adverse outcomes. Funding Acknowledgement Type of funding sources: None.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".