Evidence map›Paper›PMID 33837494›Full record

ArticleAnnals of biomedical engineering2021

Pre-surgical Prediction of Ischemic Mitral Regurgitation Recurrence Using In Vivo Mitral Valve Leaflet Strains.

Harshita Narang, Bruno V Rego, Amir H Khalighi, Ahmed Aly, Alison M Pouch, Robert C Gorman, Joseph H Gorman Iii, Michael S Sacks

Open access · greenAbstract read
In one paragraph

Article in Annals of biomedical engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
3.3field-weighted citation impact, top 7% of its field
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

25 citing papers in PubMed, 25 citations in OpenAlex.

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  16. The effects of leaflet material properties on the simulated function of regurgitant mitral valves.Journal of the mechanical behavior of biomedical materials · 2023
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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 at 2 institutions in 1 country.

Harshita NarangJames T. Willerson Center for Cardiovascular Modeling and Simulation, Oden Institute for Computational Engineering and Sciences, Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA.
Bruno V RegoJames T. Willerson Center for Cardiovascular Modeling and Simulation, Oden Institute for Computational Engineering and Sciences, Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA.
Amir H KhalighiJames T. Willerson Center for Cardiovascular Modeling and Simulation, Oden Institute for Computational Engineering and Sciences, Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA.
Ahmed AlyGorman Cardiovascular Research Group, Smilow Center for Translational Research, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Alison M PouchGorman Cardiovascular Research Group, Smilow Center for Translational Research, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Robert C GormanGorman Cardiovascular Research Group, Smilow Center for Translational Research, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Joseph H Gorman IiiGorman Cardiovascular Research Group, Smilow Center for Translational Research, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Michael S SacksJames T. Willerson Center for Cardiovascular Modeling and Simulation, Oden Institute for Computational Engineering and Sciences, Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA. msacks@oden.utexas.edu.ORCID http://orcid.org/0000-0002-3199-2204
The University of Texas at Austin · USUniversity of Pennsylvania · US

Funding

Surgery to Prevent Post Infarction Ventricular RemodelingR01HL063954 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI GORMAN, ROBERT C · 2001 to 2018
$9.8M
Quantitative Methods for Optimizing IMR RepairR01HL073021 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI GORMAN, ROBERT C, SACKS, MICHAEL S · 2004 to 2022
$7.6M
Remodeling potential of the mitral valve following surgical repairR01HL119297 · NHLBI · UNIVERSITY OF TEXAS AT AUSTIN · PI GORMAN, JOSEPH H, SACKS, MICHAEL S · 2013 to 2017
$6.6M
Echocardiography to Predict Recurrent IMR After Surgical Mitral Valve ReplacementR01HL103723 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI GORMAN, ROBERT C, HUNG, JUDY W · 2011 to 2020
$5.3M
A Platform for Outcomes Data Sharing and Pre-Operative Image-Guided Mechanistic Assessment for Bicuspid Aortic Valve Repair SurgeryK01HL141643 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI POUCH, ALISON MARIE · 2018 to 2022
$532k
4D ventricle-valve model risk stratification for planning surgical treatment of ischemic mitral regurgitationF30HL142138 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI ALY, AHMED · 2018 to 2020
$114k
NHLBI NIH HHS F30 HL142138NHLBI NIH HHS K01 HL141643NHLBI NIH HHS R01 HL063954NHLBI NIH HHS R01 HL073021NHLBI NIH HHS R01 HL103723NHLBI NIH HHS R01 HL119297NIH HHS R01-HL073021NIH HHS R01-HL119297
6 · The paper itself

Abstract

Ischemic mitral regurgitation (IMR) is a prevalent cardiac disease associated with substantial morbidity and mortality. Contemporary surgical treatments continue to have limited long-term success, in part due to the complex and multi-factorial nature of IMR. There is thus a need to better understand IMR etiology to guide optimal patient specific treatments. Herein, we applied our finite element-based shape-matching technique to non-invasively estimate peak systolic leaflet strains in human mitral valves (MVs) from in-vivo 3D echocardiographic images taken immediately prior to and post-annuloplasty repair. From a total of 21 MVs, we found statistically significant differences in pre-surgical MV size, shape, and deformation patterns between the with and without IMR recurrence patient groups at 6 months post-surgery. Recurrent MVs had significantly less compressive circumferential strains in the anterior commissure region compared to the recurrent MVs (p = 0.0223) and were significantly larger. A logistic regression analysis revealed that average pre-surgical circumferential leaflet strain in the Carpentier A1 region independently predicted 6-month recurrence of IMR (optimal cutoff value - 18%, p = 0.0362). Collectively, these results suggest greater disease progression in the recurrent group and underscore the highly patient-specific nature of IMR. Importantly, the ability to identify such factors pre-surgically could be used to guide optimal treatment methods to reduce post-surgical IMR recurrence.

Indexed as

Echocardiography, Three-DimensionalHumansImage Processing, Computer-AssistedMitral Valve InsufficiencyRecurrenceRegression AnalysisSystoleFinite element methodIschemic mitral regurgitationTransesophageal echocardiography

Identifiers

PMID33837494
PMCPMC9134826
OpenAlexW3147220754

What OpenQuestion holds

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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.