Evidence map›Paper›PMID 37555041›Full record

ArticleJTCVS techniques2023

An experimental model of chronic severe mitral regurgitation.

Martha M O McGilvray, Tari-Ann E Yates, Lynn Pauls, Meghan O Kelly, Nicholas Razo, Stacie McElligott, Glenn J Foster, Jie Zheng, Jonathan K Zoller, Christian Zemlin and 1 more

Abstract read
In one paragraph

Article in JTCVS techniques, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Left atrial and ventricular remodeling in chronic mitral regurgitation.The Journal of thoracic and cardiovascular surgery · 2025
    Article
  3. Animal and cellular models of atrial fibrillation: a review.Frontiers in cardiovascular medicine · 2025
    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

11 authors.

Martha M O McGilvrayDivision of Cardiothoracic Surgery, Department of Surgery, Washington University School of Medicine, Barnes-Jewish Hospital, St Louis, Mo.
Tari-Ann E YatesDivision of Cardiothoracic Surgery, Department of Surgery, Washington University School of Medicine, Barnes-Jewish Hospital, St Louis, Mo.
Lynn PaulsDivision of Cardiothoracic Anesthesiology, Department of Anesthesiology, Washington University School of Medicine, Barnes-Jewish Hospital, St. Louis, Mo.
Meghan O KellyDivision of Cardiothoracic Surgery, Department of Surgery, Washington University School of Medicine, Barnes-Jewish Hospital, St Louis, Mo.
Nicholas RazoDivision of Cardiothoracic Surgery, Department of Surgery, Washington University School of Medicine, St Louis, Mo.
Stacie McElligottDivision of Cardiothoracic Surgery, Department of Surgery, Washington University School of Medicine, Barnes-Jewish Hospital, St Louis, Mo.
Glenn J FosterCenter for Clinical Imaging and Research, Washington University School of Medicine, St Louis, Mo.
Jie ZhengMallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo.
Jonathan K ZollerDivision of Cardiothoracic Anesthesiology, Department of Anesthesiology, Washington University School of Medicine, Barnes-Jewish Hospital, St. Louis, Mo.
Christian ZemlinDivision of Cardiothoracic Surgery, Department of Surgery, Washington University School of Medicine, St Louis, Mo.
Ralph J DamianoDivision of Cardiothoracic Surgery, Department of Surgery, Washington University School of Medicine, Barnes-Jewish Hospital, St Louis, Mo.

Funding

SURGICAL TREATMENT OF VENTRICULAR TACHYARRHYTHMIASR01HL032257 · NHLBI · WASHINGTON UNIVERSITY · PI DAMIANO, RALPH J, ZEMLIN, CHRISTIAN W · 1985 to 2025
$10.4M
BASIC SCIENCE RESEARCH TRAINING: CARDIOPULMONARY SURGERYT32HL007776 · NHLBI · WASHINGTON UNIVERSITY · PI DAMIANO, RALPH J · 1994 to 2020
$4.6M
NHLBI NIH HHS R01 HL032257NHLBI NIH HHS T32 HL007776
6 · The paper itself

Abstract

Objective: To develop a minimally invasive, reproducible model of chronic severe mitral regurgitation (MR) that replicates the clinical phenotype of left atrial (LA) and left ventricular dilation and susceptibility to atrial fibrillation. Methods: Under transesophageal echocardiographic guidance, chordae tendinae were avulsed using endovascular forceps until the ratio of regurgitant jet area to LA area was ≥70%. Animals survived for an average of 8.6 ± 1.6 months (standard deviation) and imaged with monthly transthoracic echocardiography (TTE). Animals underwent baseline and preterminal magnetic resonance imaging. Terminal studies included TTE, transesophageal echocardiography, and rapid atrial pacing to test inducibility of atrial tachyarrhythmias. Results: Eight dogs underwent creation of severe MR and interval monitoring. Two were excluded-one died from acute heart failure, and the other had resolution of MR. Six dogs underwent the full experimental protocol; only one required medical management of clinical heart failure. MR remained severe over time, with a mean terminal regurgitant jet area to LA area of 71 ± 14% (standard deviation) and regurgitant fraction of 52 ± 11%. Mean LA volume increased over 130% (TTE: 163 ± 147%, Conclusions: Within the 6 dogs that successfully completed the full experimental protocol, this model replicated the clinical phenotype of severe MR, which led to marked structural and electrophysiologic cardiac remodeling. This model allowed for precise measurements at repeated time points and will facilitate future studies to elucidate the mechanisms of atrial and ventricular remodeling secondary to MR and the pathophysiology of valvular atrial fibrillation.

Indexed as

arrhythmiasatrial fibrillationcardiac magnetic resonance imagingechocardiographylarge animal modelmitral regurgitationtranslational research

Identifiers

PMID37555041
PMCPMC10405169

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Registered trials

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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.