Serum uric acid, influence of sacubitril/valsartan, and cardiovascular outcomes in heart failure with preserved ejection fraction: PARAGON-HF
Bibliographic record
Abstract
Abstract Background Serum uric acid (SUA) is a biomarker of several pathobiologies relevant to the pathogenesis of heart failure with preserved ejection fraction (HFpEF), though by itself may also worsen outcomes. In HF with reduced EF, SUA is independently associated with adverse outcomes and sacubitril/valsartan reduces SUA compared to enalapril. These effects in HFpEF have not been delineated. Purpose To determine the prognostic value of SUA, relationship of change in SUA to quality of life and outcomes, and influence of sacubitril/valsartan on SUA in HFpEF. Methods We analyzed 4,795 participants from the Prospective Comparison of ARNI with ARB Global Outcomes in HF with Preserved Ejection Fraction (PARAGON-HF) trial. We related baseline hyperuricemia to the primary outcome (CV death and total HF hospitalization), its components, myocardial infarction or stroke, and a renal composite outcome. At the 4-month visit, the relationship between SUA change and Kansas City Cardiomyopathy Questionnaire overall summary score (KCCQ-OSS) and several biomarkers including N-terminal pro-B-type natriuretic peptide (NT-proBNP) were also assessed. We simultaneously adjusted for baseline and time-updated SUA to determine whether lowering SUA was associated with clinical benefit. Results Average age was 73±8 years and 52% were women. After multivariable adjustment, hyperuricemia was associated with increased risk for most outcomes (primary outcome HR 1.61, 95% CI 1.37, 1.90, Fig 1A). The treatment effect of sacubitril/valsartan for the primary outcome was not modified by baseline SUA (interaction p=0.11). Sacubitril/valsartan reduced SUA −0.38 mg/dL (95% CI: −0.45, −0.31) compared with valsartan (Fig 1B), with greater effect in those with baseline hyperuricemia (−0.50 mg/dL) (interaction p=0.013). Change in SUA was independently and inversely associated with change in KCCQ-OSS (p=0.019) and eGFR (p<0.001), but not NT-proBNP (p=0.52). Time-updated SUA was a stronger predictor of adverse outcomes over baseline SUA. Conclusions SUA independently predicts adverse outcomes in HFpEF. Sacubitril/valsartan significantly reduces SUA compared to valsartan, an effect that was stronger in those with higher baseline SUA, and reducing SUA was associated with improved outcomes. Funding Acknowledgement Type of funding source: Private company. Main funding source(s): Novartis
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 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".