Evidence map›Paper›PMID 40634239›Full record

ReviewESC heart failure2025

Clinical endpoints in pragmatic heart failure trials: From data collection to clinical endpoint classification.

Veraprapas Kittipibul, Harriette G C Van Spall, William Schuyler Jones, Marat Fudim, Robert J Mentz, Kevin Anstrom, Bertram Pitt, Patrice Desvigne-Nickens, Jerome L Fleg, Camilla Hage and 4 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in ESC heart failure, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

14 authors.

Veraprapas KittipibulDivision of Cardiology, Duke University Medical Center, Durham, North Carolina, USA.ORCID https://orcid.org/0000-0002-9107-1837
Harriette G C Van SpallPopulation Health Research Institute, Hamilton, Ontario, Canada.
William Schuyler JonesDivision of Cardiology, Duke University Medical Center, Durham, North Carolina, USA.
Marat FudimDivision of Cardiology, Duke University Medical Center, Durham, North Carolina, USA.
Robert J MentzDivision of Cardiology, Duke University Medical Center, Durham, North Carolina, USA.
Kevin AnstromCollaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Bertram PittDivision of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA.
Patrice Desvigne-NickensDivision of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, Maryland, USA.
Jerome L FlegDivision of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, Maryland, USA.
Camilla HageDepartment of Medicine, Karolinska Institutet, Stockholm, Sweden.
Stefan JamesUppsala Clinical Research Center and Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden.
Claes HeldUppsala Clinical Research Center and Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden.
Lars LundDepartment of Medicine, Karolinska Institutet, Stockholm, Sweden.
Adam DeVoreDivision of Cardiology, Duke University Medical Center, Durham, North Carolina, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical endpoint classification (CEC)-that is, evaluation of clinical events using pre-defined criteria-is commonly conducted in clinical trial operations to ensure systematic and consistent assessment of endpoints needed to assess the intervention's safety and efficacy. This is particularly relevant for heart failure (HF) trials given the subjective decision-making around hospitalizations and variation in how worsening HF events are managed (both in hospital and in ambulatory settings). Several CEC strategies have been adopted to address the growing need for pragmatic clinical trials that enhance generalizability and minimize research burden on trial sites and patients. This review summarizes common CEC strategies including the traditional approach, investigator-reported endpoints, CEC using real-world data and CEC utilizing large language models. We summarize CEC strategies used in recent HF pragmatic trials and present challenges and considerations for CEC in HF pragmatic trials from the selection of clinical endpoints and data collection to CEC.

Indexed as

Data CollectionEndpoint DeterminationHeart FailurePragmatic Clinical Trials as TopicHumansclinical endpoint classificationendpointsheart failureoutcomespragmatic clinical trial

Identifiers

PMID40634239
PMCPMC12450825

What Socratic holds

Textmetadata
LicenceCC BY-NC
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.