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Global Differences in Heart Failure With Preserved Ejection Fraction

2021· article· en· W3156633975 on OpenAlexaff
Jasper Tromp, Brian Claggett, Jiankang Liu, Alice M. Jackson, Pardeep S. Jhund, Lars Køber, J Widimský, S. А. Boytsov, Vijay Chopra, Inder S. Anand, Junbo Ge, Chen‐Huan Chen, Aldo P. Maggioni, Felipe A. Martínez, Milton Packer, Marc A. Pfeffer, Burkert Pieske, Margaret M. Redfield, Jean L. Rouleau, Dirk J. van Veldhuisen, Faı̈ez Zannad, Michael R. Zile, Adel R. Rizkala, Akiko Inubushi-Molessa, Martin Lefkowitz, Victor Shi, John J.V. McMurray, Scott D. Solomon, Carolyn S.P. Lam

Bibliographic record

VenueCirculation Heart Failure · 2021
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsMontreal Heart Institute
FundersNational Center for Advancing Translational SciencesNational Heart, Lung, and Blood InstituteNational Institute on AgingRelypsaRespicardiaAmerican RegentVifor PharmaDaiichi-SankyoARCA BiopharmaUniversity of GlasgowPfizerBiogenModernaCytokineticsUniversity of OxfordJazz PharmaceuticalsIronwood Pharmaceuticals, IncorporatedSanofi PasteurCelladon CorporationDefense Acquisition Program AdministrationBoston Scientific CorporationAlnylam PharmaceuticalsNovo NordiskMyoKardiaDaiichi Sankyo EuropeServierGilead SciencesBayer HealthCareNational Institute of Diabetes and Digestive and Kidney DiseasesSanofiLivaNovaGlaxoSmithKlineAmgenAstraZenecaEli Lilly and CompanyBristol-Myers Squibb
KeywordsMedicineHeart failureEjection fractionCardiologyInternal medicineStroke volumeHeart failure with preserved ejection fraction

Abstract

fetched live from OpenAlex

Background: Heart failure with preserved ejection fraction (HFpEF) is a global public health problem with important regional differences. We investigated these differences in the PARAGON-HF trial (Prospective Comparison of Angiotensin Receptor Neprilysin Inhibitor With Angiotensin Receptor Blocker Global Outcomes in HFpEF), the largest and most inclusive global HFpEF trial. Methods: We studied differences in clinical characteristics, outcomes, and treatment effects of sacubitril/valsartan in 4796 patients with HFpEF from the PARAGON-HF trial, grouped according to geographic region. Results: Regional differences in patient characteristics and comorbidities were observed: patients from Western Europe were oldest (mean 75±7 years) with the highest prevalence of atrial fibrillation/flutter (36%); Central/Eastern European patients were youngest (mean 71±8 years) with the highest prevalence of coronary artery disease (50%); North American patients had the highest prevalence of obesity (65%) and diabetes (49%); Latin American patients were younger (73±9 years) and had a high prevalence of obesity (53%); and Asia-Pacific patients had a high prevalence of diabetes (44%), despite a low prevalence of obesity (26%). Rates of the primary composite end point of total hospitalizations for HF and death from cardiovascular causes were lower in patients from Central Europe (9 per 100 patient-years) and highest in patients from North America (28 per 100 patient-years), which was primarily driven by a greater number of total hospitalizations for HF. The effect of treatment with sacubitril-valsartan was not modified by region (interaction P >0.05). Conclusions: Among patients with HFpEF recruited worldwide in PARAGON-HF, there were important regional differences in clinical characteristics and outcomes, which may have implications for the design of future clinical trials. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01920711.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.271
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), 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

Citations63
Published2021
Admission routes1
Has abstractyes

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