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Record W3081335451 · doi:10.1002/ejhf.1984

Serum Uric Acid, Influence of Sacubitril–Valsartan, and Cardiovascular Outcomes in Heart Failure with Preserved Ejection Fraction: PARAGON-HF

2020· article· en· W3081335451 on OpenAlexaff
Senthil Selvaraj, Brian Claggett, Marc A. Pfeffer, Akshay S. Desai, Finnian R. Mc Causland, Martina M. McGrath, Inder S. Anand, Dirk J. van Veldhuisen, Lars Køber, Stefan Janssens, John G.F. Cleland, Burkert Pieske, Jean L. Rouleau, Michael R. Zile, Victor Shi, Martin Lefkowitz, John J.V. McMurray, Scott D. Solomon

Bibliographic record

VenueEuropean Journal of Heart Failure · 2020
Typearticle
Languageen
FieldMedicine
TopicGout, Hyperuricemia, Uric Acid
Canadian institutionsUniversité de MontréalMontreal Clinical Research InstituteMontreal Heart Institute
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsSacubitril, ValsartanMedicineHeart failureEjection fractionSacubitrilInternal medicineCardiologyValsartanUric acidBlood pressure

Abstract

fetched live from OpenAlex

AIMS: This study aimed to determine the prognostic value of serum uric acid (SUA) on outcomes in heart failure (HF) with preserved ejection fraction (HFpEF), and whether sacubitril-valsartan reduces SUA and use of SUA-related therapies. METHODS AND RESULTS: We analysed 4795 participants from the Prospective Comparison of ARNI [angiotensin receptor-neprilysin inhibitor] with ARB [angiotensin-receptor blockers] Global Outcomes in HF with Preserved Ejection Fraction (PARAGON-HF) trial. We related baseline hyperuricaemia (using age and gender adjusted assay definitions) to the primary outcome [cardiovascular (CV) death and total HF hospitalizations]. We assessed the associations between changes in SUA and Kansas City Cardiomyopathy Questionnaire Overall Summary Score (KCCQ-OSS) and other cardiac biomarkers from baseline to 4 months. We simultaneously adjusted for baseline and time-updated SUA to determine whether lowering SUA was associated with clinical benefit. The mean (± standard deviation) age of patients was 73 ± 8 years and 52% were women. After multivariable adjustment, hyperuricaemia was associated with increased risk for the primary outcome [rate ratio 1.61, 95% confidence interval (CI) 1.37-1.90]. The treatment effect of sacubitril-valsartan for the primary endpoint was not significantly modified by hyperuricaemia (P-value for interaction = 0.14). Sacubitril-valsartan reduced SUA by 0.38 mg/dL (95% CI 0.31-0.45) compared with valsartan at 4 months, with greater effect in those with elevated SUA vs. normal SUA (-0.51 mg/dL vs. -0.32 mg/dL) (P-value for interaction = 0.031). Sacubitril-valsartan reduced the odds of initiating SUA-related treatments by 32% during follow-up (P < 0.001). After multivariable adjustment, change in SUA was inversely associated with change in KCCQ-OSS and directly associated with high-sensitivity troponin T (P < 0.05). Time-updated SUA was a stronger predictor of adverse outcomes than baseline SUA. CONCLUSIONS: Serum uric acid independently predicted adverse outcomes in HFpEF. Sacubitril-valsartan reduced SUA and the initiation of related therapy compared with valsartan. Reductions in SUA were associated with improved outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.230
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations58
Published2020
Admission routes1
Has abstractyes

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