Evidence map›Paper›PMID 39469127›Full record

ArticleFrontiers in cardiovascular medicine2024

Imminent risk of LVEF decline in asymptomatic patients with primary mitral regurgitation.

Jingyi Zheng, Shao-Wei Huang, Mustafa I Ahmed, Betty Pat, Steven G Lloyd, Oleg F Sharifov, Thomas S Denney, Louis J Dell'Italia

Abstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Article
  4. 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

8 authors.

Jingyi ZhengDepartment of Mathematics and Statistics, Auburn University, Auburn, AL, United States.
Shao-Wei HuangDepartment of Mathematics and Statistics, Auburn University, Auburn, AL, United States.
Mustafa I AhmedDivision of Cardiovascular Disease, University of Alabama at Birmingham, Birmingham, AL, United States.
Betty PatDivision of Cardiovascular Disease, University of Alabama at Birmingham, Birmingham, AL, United States.
Steven G LloydDivision of Cardiovascular Disease, University of Alabama at Birmingham, Birmingham, AL, United States.
Oleg F SharifovDivision of Cardiovascular Disease, University of Alabama at Birmingham, Birmingham, AL, United States.
Thomas S DenneyDepartment of Electrical and Computer Engineering, Samuel Ginn College of Engineering, Auburn University, Auburn, AL, United States.
Louis J Dell'ItaliaDivision of Cardiovascular Disease, University of Alabama at Birmingham, Birmingham, AL, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: 2020 American College of Cardiology/American Heart Association (ACC/AHA) Guidelines state that the ideal time for mitral valve surgery in primary mitral regurgitation (PMR) is when the LV approaches but has not yet reached echocardiographic LV ejection fraction (EF) < 60% or LV end-systolic dimension (ESD) > 40 mm. However, it is difficult to know the imminent risk of crossing this threshold when the surgical outcome is less optimal. Objective: Using machine learning and statistical models, we have shown that cardiac magnetic resonance (CMR) LV sphericity index (SI) and LV mid circumferential strain rate (SR Methods: 33 asymptomatic PMR patients with moderate to severe mitral regurgitation had CMR with tissue tagging at baseline and every 6 months for 18 months. Two types of models were employed to predict LVEF < 60% at 18 months: a model using CMR features at a single time point (e.g., baseline) and a model utilizing repeated measurements over time. Results: CMR LVEF decreased below 60% in 13 patients over 18 months. LVEF varied over time with an inverse relation to mean arterial pressure and mean end-systolic wall stress. Random Forest models utilizing LV SI, LV mid SR Conclusion: The variability of LVEF due to blood pressure dependence may require a longitudinal study that incorporates LVEF, LVESD, SR

Indexed as

asymptomatic primary mitral regurgitationcardiac MRILV circumferential strain rateLVEF declinemachine learningpredictive longitudinal modeling

Identifiers

PMID39469127
PMCPMC11513293

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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.