MétaCan
Menu
← Back to cohort
Record W4403812679 · doi:10.1093/eurheartj/ehae666.910

Race in heart failure: a pooled participant-level analysis of the global PARADIGM-HF and PARAGON-HF trials

2024· article· en· W4403812679 on OpenAlexaff
Henri Lu, Brian Claggett, Milton Packer, Michael A. Pfeffer, Eldrin F. Lewis, Karl Swedberg, Jean L. Rouleau, Michael R. Zile, Martin Lefkowitz, Akshay S. Desai, Pardeep S. Jhund, John J.V. McMurray, Scott D. Solomon, Muthiah Vaduganathan

Bibliographic record

VenueEuropean Heart Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsMedicineHeart failureRace (biology)Internal medicineGerontologyCardiology

Abstract

fetched live from OpenAlex

Abstract Background Mechanisms of disease pathobiology, prognosis, and potentially treatment responses might vary by race in patients with heart failure (HF). Early experiences with neprilysin inhibition suggested possible increased risks of angioedema, especially among Black individuals. We aimed to examine the safety and efficacy profile of sacubitril/valsartan in a pooled participant-level dataset of 2 large cohorts of patients with HF by self-reported race. Methods PARADIGM-HF and PARAGON-HF were multicenter, randomized clinical trials testing sacubitril/valsartan against a renin-angiotensin system inhibitor (RASi, enalapril or valsartan, respectively) in patients with HF and LVEF ≤40% (PARADIGM-HF) or LVEF ≥45% (PARAGON-HF). We included all patients with available data on self-reported race and categorized patients as White, Asian, or Black. We assessed adjudicated outcomes including the composite of first HF hospitalization (HFH) or cardiovascular (CV) death, its components, and angioedema by racial group. Results Among 12,097 included participants, 9,451 (78.1%) were White, 2,116 (17.5%) were Asian, and 530 (4.4%) were Black. Asian participants were from 19 countries, with highest enrollment from India, China, and the Philippines. Black participants were from 18 countries, with highest enrollment from the US, South Africa, and Brazil. Black patients had the worst baseline health status (adjusted KCCQ-OSS mean 70.3), while White (71.4) and Asian patients (76.4) had better health status; P<0.001. Over 2.4-years of median follow-up, Black (adjusted HR 1.67; 95% CI 1.37-1.89; P<0.001) and Asian patients (adjusted HR 1.32; 95% CI 1.16-1.50; P<0.001) experienced higher risks of the primary outcome compared with White patients (Figure 1). The treatment effects of sacubitril/valsartan vs. RASi on the primary endpoint were consistent among White (HR 0.84; 95% CI: 0.77-0.91), Asian (HR 0.92; 95% CI: 0.78-1.10), and Black patients (HR 0.79; 95% CI: 0.58-1.07; Pinteraction = 0.39). In light of higher baseline risks, Black patients accrued the greatest absolute risk reduction with sacubitril/valsartan (Figure 2). Consistent treatment benefits by race were also observed for the individual components (CV death alone and first HFH alone). Rates of any adjudicated angioedema were numerically higher with sacubitril/valsartan vs. RASi across race groups (White 0.4% vs. 0.2%; Asian 0.6% vs. 0.2%; Black 2.3% vs. 0.8%), however no patient in either trial experienced airway compromise or required mechanical airway protection. Conclusions In a pooled experience of over 12,000 participants enrolled in 2 trials conducted across 56 countries, Black and Asian patients exhibited a higher risk of CV events than White patients. Rates of non-serious angioedema were numerically higher with sacubitril/valsartan across race groups. The relative CV benefits of sacubitril/valsartan were consistent across races, with greatest absolute benefits observed in Black patients.

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)0.019
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.012
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.131
GPT teacher head0.373
Teacher spread0.242 · 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 designMeta-analysis
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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Heart Journal→Same topicHeart Failure Treatment and Management→French-language works237,207→