Evidence mapPaperPMID 39441333Full record

ReviewHeart failure reviews2025

Changing the paradigm in heart failure: shifting from treatment to prevention.

Alex J Chang, Yilin Liang, Michael P Girouard, Ankeet S Bhatt, Alexander T Sandhu, Andrew J Sauer, Stephen J Greene, Josephine Harrington, Alan S Go, Andrew P Ambrosy

Abstract readReview
PubMed Publisher
In one paragraph

Review in Heart failure reviews, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Alex J ChangDepartment of Medicine, Kaiser Permanente San Francisco Medical Center, 2425 Geary Boulevard, San Francisco, CA, 94115, USA.
Yilin LiangDepartment of Medicine, Kaiser Permanente San Francisco Medical Center, 2425 Geary Boulevard, San Francisco, CA, 94115, USA.
Michael P GirouardDepartment of Cardiology, Kaiser Permanente San Francisco Medical Center, 2425 Geary Boulevard, San Francisco, CA, 94115, USA.
Ankeet S BhattDepartment of Cardiology, Kaiser Permanente San Francisco Medical Center, 2425 Geary Boulevard, San Francisco, CA, 94115, USA.
Alexander T SandhuDivision of Cardiovascular Medicine, Stanford University, 300 Pasteur Drive, Stanford, CA, 94305, USA.
Andrew J SauerSaint Luke's Mid America Heart Institute, University of Missouri-Kansas City, 4401 Wornall Rd, Kansas City, MO, 64111, USA.
Stephen J GreeneDuke Clinical Research Institute, Division of Cardiology, Duke University School of Medicine, 2301 Erwin Road, Durham, NC, 27710, USA.
Josephine HarringtonDuke Clinical Research Institute, Division of Cardiology, Duke University School of Medicine, 2301 Erwin Road, Durham, NC, 27710, USA.
Alan S GoDivision of Research, Division of Research, Kaiser Permanente Northern California, 4480 Hacienda Drive, Pleasanton, CA, 94588, USA.
Andrew P AmbrosyDepartment of Cardiology, Kaiser Permanente San Francisco Medical Center, 2425 Geary Boulevard, San Francisco, CA, 94115, USA. andrew.p.ambrosy@kp.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Heart failure (HF) poses a major global health challenge with rising prevalence, significant morbidity and mortality, and substantial associated healthcare costs. With aging of the population and an increasing burden of comorbidities, the complex interplay between cardiovascular, kidney, and metabolic risk factors have been thrust into the spotlight and have broadened the traditional focus from HF treatment to an increased emphasis on prevention. In recognition of the evolving HF landscape, the American Heart Association released the PREVENT models which are comprehensive risk assessment tools that estimate 10- and 30-year risk of incident cardiovascular disease and its subtypes, including atherosclerotic cardiovascular disease (ASCVD) and, for the first time, HF. While it is an accurate risk estimation tool and represents a step forward in improving risk stratification for primary prevention of HF, there remain several limitations and unknowns like model performance across disaggregated racial and ethnic groups, the role of traditional ASCVD vs. HF-specific risk factors, HF prediction among those with known ASCVD, and the use of traditional regression techniques in lieu of potentially more powerful machine learning-based modeling approaches. Furthermore, it remains unclear how to optimize risk estimation in clinical care. The emergence of multiple novel pharmacological therapies that prevent incident HF, including sodium-glucose co-transporter 2 (SGLT2) inhibitors, glucagon-like peptide 1 (GLP1) receptor agonists, and nonsteroidal mineralocorticoid receptor antagonists (MRAs), highlights the importance of accurate HF risk prediction. To provide HF prevention with these effective but costly therapies, we must understand the optimal strategy in sequencing and combining these therapies and prioritize patients at highest risk. Such implementation requires both accurate risk stratification and a better understanding of how to communicate risk to patients and providers. This state-of-the-art review aims to provide a comprehensive overview of recent trends in HF prevention, including risk assessment, care management strategies, and emerging and novel treatments.

Indexed as

Heart FailureHumansPrimary PreventionRisk AssessmentRisk FactorsCardiovascular-Kidney-MetabolicHeart FailureLifestylePharmacotherapiesPreventionRisk stratification

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.