Increase in BNP in Response to Endothelin-Receptor Antagonist Atrasentan Is Associated With Incident Heart Failure
Bibliographic record
Abstract
BACKGROUND: The endothelin receptor antagonist atrasentan reduced the risk of kidney failure in patients with type 2 diabetes mellitus and chronic kidney disease (CKD) in the SONAR (Study of Diabetic Nephropathy with Atrasentan) trial, although with a numerically higher incidence of heart failure (HF) hospitalization. OBJECTIVES: The purpose of this study was to assess if early changes in B-type natriuretic peptide (BNP) and body weight during atrasentan treatment predict HF risk. METHODS: Participants with type 2 diabetes and CKD entered an open-label enrichment phase to assess response to atrasentan 0.75 mg/day. Participants without substantial fluid retention (>3 kg body weight increase or BNP increase to >300 pg/mL), were randomized to atrasentan 0.75 mg/day or placebo. Cox proportional hazards regression was used to assess the effects of atrasentan vs placebo on the prespecified safety outcome of HF hospitalizations. RESULTS: Among 3,668 patients, 73 (4.0%) participants in the atrasentan and 51 (2.8%) in the placebo group developed HF (HR: 1.39; 95% CI: 0.97-1.99; P = 0.072). In a multivariable analysis, HF risk was associated with higher baseline BNP (HR: 2.32; 95% CI: 1.81-2.97) and percent increase in BNP during response enrichment (HR: 1.46; 95% CI: 1.08-1.98). Body weight change was not associated with HF. Exclusion of patients with at least 25% BNP increase during enrichment attenuated the risk of HF with atrasentan (HR: 1.02; 95% CI: 0.66-1.56) while retaining nephroprotective effects (HR: 0.58; 95% CI: 0.44-0.78). CONCLUSIONS: In patients with type 2 diabetes and CKD, baseline BNP and early changes in BNP in response to atrasentan were associated with HF hospitalization, highlighting the importance of natriuretic peptide monitoring upon initiation of atrasentan treatment. (Study Of Diabetic Nephropathy With Atrasentan [SONAR]; NCT01858532).
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".