Evidence map›Paper›PMID 37850602›Full record

ReviewHeart rhythm2022

Opportunities and challenges in heart rhythm research: Rationale and development of an electrophysiology collaboratory.

Duy T Nguyen, Kenneth C Bilchick, Sanjiv M Narayan, Mina K Chung, Kevin L Thomas, Kenneth R Laurita, Marmar Vaseghi, Roopinder Sandhu, Mihail G Chelu, Prince J Kannankeril and 13 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Heart rhythm, 2022. 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. 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

23 authors.

Duy T NguyenStanford University, Stanford, California. Electronic address: dtnwyn@gmail.com.
Kenneth C BilchickUniversity of Virginia Health System, Charlottesville, Virginia.
Sanjiv M NarayanStanford University, Stanford, California.
Mina K ChungDepartment of Cardiology, Cleveland Clinic, Cleveland, Ohio.
Kevin L ThomasDuke University Medical Center, Durham, North Carolina.
Kenneth R LauritaCase Western Reserve University, Cleveland, Ohio.
Marmar VaseghiUniversity of California, Los Angeles Cardiac Arrhythmia Center, Los Angeles, California.
Roopinder SandhuDepartment of Cardiology and Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California.
Mihail G CheluBaylor College of Medicine, Houston, Texas.
Prince J KannankerilVanderbilt University Medical Center, Nashville, Tennessee.
Douglas L PackerMayo Clinic, Rochester, Minnesota.
David D McManusUniversity of Massachusetts Medical School, Worcester, Massachusetts.
Atul VermaSouthlake Regional Health Center, Toronto, Ontario, Canada.
Matthew SingletonWellSpan Health, York, Pennsylvania.
Khaldoun TarakjiMedtronic, Mounds View, Minnesota.
Sana M Al-KhatibDuke University Medical Center, Durham, North Carolina.
Jonathan R KaltmanChildren's National Hospital, Washington, District of Columbia.
Ravi C BalijepalliNational Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland.
George F Van HareOffice of Cardiovascular Devices, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland.
Jodie L HurwitzNorth Texas Heart Center, Dallas, Texas.
Andrea M RussoCooper University Hospital, Camden, New Jersey.
Fred M KusumotoMayo Clinic Florida, Jacksonville, Florida.
Christine M AlbertDepartment of Cardiology and Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California.

Funding

Machine Learning in Atrial FibrillationR01HL149134 · NHLBI · STANFORD UNIVERSITY · PI NARAYAN, SANJIV M · 2020 to 2024
$3.8M
Novel mechanisms and treatment of arrhythmia during resuscitationR01HL142754 · NHLBI · CASE WESTERN RESERVE UNIVERSITY · PI KENNETH LAURITA, Lance D Wilson · 2020 to 2026
$3.4M
Machine Learning for Ventricular ArrhythmiasR01HL162260 · NHLBI · STANFORD UNIVERSITY · PI Sanjiv M Narayan · 2023 to 2026
$2.5M
NHLBI NIH HHS R01 HL142754NHLBI NIH HHS R01 HL149134NHLBI NIH HHS R01 HL162260
6 · The paper itself

Abstract

There are many challenges in the current landscape of electrophysiology (EP) clinical and translational research, including increasing costs and complexity, competing demands, regulatory requirements, and challenges with study implementation. This review seeks to broadly discuss the state of EP research, including challenges and opportunities. Included here are results from a Heart Rhythm Society (HRS) Research Committee member survey detailing HRS members' perspectives regarding both barriers to clinical and translational research and opportunities to address these challenges. We also provide stakeholder perspectives on barriers and opportunities for future EP research, including input from representatives of the U.S. Food and Drug Administration, industry, and research funding institutions that participated in a Research Collaboratory Summit convened by HRS. This review further summarizes the experiences of the heart failure and heart valve communities and how they have approached similar challenges in their own fields. We then explore potential solutions, including various models of research ecosystems designed to identify research challenges and to coordinate ways to address them in a collaborative fashion in order to optimize innovation, increase efficiency of evidence generation, and advance the development of new therapeutic products. The objectives of the proposed collaborative cardiac EP research community are to encourage and support scientific discourse, research efficiency, and evidence generation by exploring collaborative and equitable solutions in which stakeholders within the EP community can interact to address knowledge gaps, innovate, and advance new therapies.

Indexed as

Cardiac ElectrophysiologyEcosystemTranslational Research, BiomedicalCollaborative communityCollaboratoryElectrophysiologyResearch opportunities

Identifiers

PMID37850602
PMCPMC10824490

What OpenQuestion holds

Textmetadata
LicenceTDM
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.