Evidence map›Paper›PMID 37168656›Full record

ReviewFrontiers in cardiovascular medicine2023

Looking towards the future: patient-specific computational modeling to optimize outcomes for transcatheter mitral valve repair.

Paul Wong, Andrew D Wisneski, Amitoj Sandhu, Zhongjie Wang, Vaikom S Mahadevan, Tom C Nguyen, Julius M Guccione

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in cardiovascular medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.2field-weighted citation impact, top 11% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

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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

7 authors at 1 institution in 1 country.

Paul WongSchool of Medicine, University of California San Francisco, San Francisco, CA, United States.
Andrew D WisneskiDivision of Cardiothoracic Surgery, Department of Surgery, University of California San Francisco, San Francisco, CA, United States.
Amitoj SandhuDivision of Cardiology, Department of Medicine, University of California San Francisco, San Francisco, CA, United States.
Zhongjie WangDivision of Cardiothoracic Surgery, Department of Surgery, University of California San Francisco, San Francisco, CA, United States.
Vaikom S MahadevanDivision of Cardiology, Department of Medicine, University of California San Francisco, San Francisco, CA, United States.
Tom C NguyenDivision of Cardiothoracic Surgery, Department of Surgery, University of California San Francisco, San Francisco, CA, United States.
Julius M GuccioneDivision of Cardiothoracic Surgery, Department of Surgery, University of California San Francisco, San Francisco, CA, United States.
University of California, San Francisco · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Severe mitral valve regurgitation (MR) is a heart valve disease that progresses to end-stage congestive heart failure and death if left untreated. Surgical repair or replacement of the mitral valve (MV) remains the gold standard for treatment of severe MR, with repair techniques aiming to restore the native geometry of the MV. However, patients with extensive co-morbidities may be ineligible for surgical intervention. With the emergence of transcatheter MV repair (TMVR) treatment paradigms for MR will evolve. The longer-term outcomes of TMVR and its effectiveness compared to surgical repair remain unknown given the differing patient eligibility for either treatment at this time. Advances in computational modeling will elucidate answers to these questions, employing techniques such as finite element method and fluid structure interactions. Use of clinical imaging will permit patient-specific MV models to be created with high accuracy and replicate MV pathophysiology. It is anticipated that TMVR technology will gradually expand to treat lower-risk patient groups, thus pre-procedural computational modeling will play a crucial role guiding clinicians towards the optimal intervention. Additionally, concerted efforts to create MV models will establish atlases of pathologies and biomechanics profiles which could delineate which patient populations would best benefit from specific surgical vs. TMVR options. In this review, we describe recent literature on MV computational modeling, its relevance to MV repair techniques, and future directions for translational application of computational modeling for treatment of MR.

Indexed as

computational modelingfinite elementfluid-Structure interactionmitral valvepatient specific modeltranscatheter mitral valve repair

Identifiers

PMID37168656
PMCPMC10164975
OpenAlexW4366827989

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.