Evidence map›Paper›PMID 39227442›Full record

ReviewNature medicine2024

Integrating liver endpoints in clinical trials of cardiovascular and kidney disease.

Faiez Zannad, Arun J Sanyal, Javed Butler, Veronica Miller, Stephen A Harrison

Erratum issuedAbstract readReview
PubMed Publisher
In one paragraph

Review in Nature medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

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  20. Liver native T1 mapping for predicting cardiovascular outcomes across stages of heart failure.Clinical research in cardiology : official journal of the German Cardiac Society · 2025
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Faiez ZannadUniversité de Lorraine, Inserm Clinical Investigation Center at Institut Lorrain du Coeur et des Vaisseaux, University Hospital of Nancy, Nancy, France. f.zannad@chru-nancy.fr.ORCID 0000-0001-7456-1570
Arun J SanyalDepartment of Internal Medicine, Virginia Commonwealth University School of Medicine, Richmond, VA, USA.ORCID 0000-0001-8682-5748
Javed ButlerBaylor Scott and White Research Institute, Dallas, TX, USA.
Veronica MillerForum for Collaborative Research, Washington DC; University of California Berkeley School of Public Health, Berkeley, CA, USA.ORCID 0000-0002-6543-3224
Stephen A HarrisonVisiting Professor of Hepatology Radcliffe Department of Medicine, University of Oxford, Oxford, UK.ORCID 0000-0001-8285-2204

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The intersection of cardiovascular disease, metabolic disorders and chronic kidney disease represents a complex clinical picture challenging healthcare systems worldwide. Metabolic-dysfunction-associated steatotic liver disease (MASLD) often manifests sequentially or concomitantly with these diseases, and may share underlying mechanisms and risk factors. Growing evidence suggests that new therapies could have benefits across these diseases, but trial sponsors and investigators tend to be reluctant to include patients with comorbidities-particularly liver diseases-in clinical trials. In this Perspective, we call for inclusion of patients with MASLD and measurement of liver outcomes in cardio-kidney-metabolic trials, when data suggest mechanistically plausible benefits and liver and cardiovascular safety. We discuss the implications of this new paradigm for clinical trial design and considerations for regulatory approval. Finally, we outline the challenges to implementing such an approach and provide recommendations for future clinical trial conduct.

Indexed as

Cardiovascular DiseasesClinical Trials as TopicFatty LiverHumansKidney DiseasesLiverRenal Insufficiency, Chronic

Identifiers

What OpenQuestion 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 OpenQuestion graph.