Evidence map›Paper›PMID 40488515›Full record

ArticleEuropean journal of heart failure2025

Employment of artificial intelligence for an unbiased evaluation regarding the recovery of right ventricular function after mitral valve transcatheter edge-to-edge repair.

Vera Fortmeier, Amelie Hesse, Teresa Trenkwalder, Márton Tokodi, Attila Kovács, Elena Rippen, Jule Tervooren, Michelle Fett, Gerhard Harmsen, Shinsuke Yuasa and 12 more

Abstract readMulticenter Study
In one paragraph

Article in European journal of heart failure, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

22 authors.

Vera Fortmeier *Department of General and Interventional Cardiology, Heart and Diabetes Center Northrhine-Westfalia, Ruhr University Bochum, Bad Oeynhausen, Germany.
Amelie Hesse *Department of Internal Medicine I, Klinikum rechts der Isar, TUM University Hospital, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Teresa TrenkwalderDZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany.
Márton TokodiHeart and Vascular Center, Semmelweis University, Budapest, Hungary.
Attila KovácsHeart and Vascular Center, Semmelweis University, Budapest, Hungary.
Elena RippenDepartment of Internal Medicine I, Klinikum rechts der Isar, TUM University Hospital, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Jule TervoorenDepartment of Internal Medicine I, Klinikum rechts der Isar, TUM University Hospital, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Michelle FettDepartment of General and Interventional Cardiology, Heart and Diabetes Center Northrhine-Westfalia, Ruhr University Bochum, Bad Oeynhausen, Germany.
Gerhard HarmsenDepartment of Physics, University of Johannesburg, Auckland Park, South Africa.
Shinsuke YuasaDepartment of Cardiovascular Medicine, Okayama University, Okayama, Japan.
Moritz KühleinDepartment of Cardiovascular Diseases, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany.
Héctor Alfonso Alvarez CovarrubiasDepartment of Cardiovascular Diseases, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany.
Moritz von ScheidtDZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany.
Ferdinand RoskiDepartment of Cardiovascular Diseases, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany.
Muhammed GerçekDepartment of General and Interventional Cardiology, Heart and Diabetes Center Northrhine-Westfalia, Ruhr University Bochum, Bad Oeynhausen, Germany.
Tibor SchusterDepartment of Family Medicine, McGill University, Montreal, Canada.
N Patrick MayrInstitute of Anesthesiology, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich, Munich, Germany.
Erion XhepaDZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany.
Karl-Ludwig LaugwitzDepartment of Internal Medicine I, Klinikum rechts der Isar, TUM University Hospital, School of Medicine and Health, Technical University of Munich, Munich, Germany.
Michael JonerDZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany.
Volker RudolphDepartment of General and Interventional Cardiology, Heart and Diabetes Center Northrhine-Westfalia, Ruhr University Bochum, Bad Oeynhausen, Germany.
Mark LachmannDepartment of Internal Medicine I, Klinikum rechts der Isar, TUM University Hospital, School of Medicine and Health, Technical University of Munich, Munich, Germany.ORCID https://orcid.org/0000-0002-1798-550X

Funding

Argus Cognitive, Inc. and CardioSight, Inc.CardioSight, Inc.Else Kröner-Fresenius FoundationGerman Cardiac SocietyGerman Center for Cardiovascular ResearchGerman Heart FoundationJános Bolyai ResearchJános Bolyai Research Scholarship of the Hungarian Academy of SciencesNational Research, Development, and Innovation Fund FK 142573National Research, Development, and Innovation Office (NKFIH) of HungaryRuhr University BochumTechnical University of Munich
6 · The paper itself

Abstract

aimsLong-standing severe mitral regurgitation (MR) leads to left atrial (LA) enlargement, elevated pulmonary artery pressures, and ultimately right heart failure. While mitral valve transcatheter edge-to-edge repair (M-TEER) alleviates left-sided volume overload, its impact on right ventricular (RV) recovery is unclear. This study aims to use both conventional echocardiography and artificial intelligence to assess the recovery of RV function in patients undergoing M-TEER for severe MR. METHODS AND

resultsThe change in RV function from baseline to 3-month follow-up was analysed in a dual-centre registry of patients undergoing M-TEER for severe MR. RV function was conventionally assessed by measuring the tricuspid annular plane systolic excursion (TAPSE). Additionally, RV function was evaluated using a deep learning model that predicts RV ejection fraction (RVEF) based on two-dimensional apical four-chamber view echocardiographic videos. Among the 851 patients who underwent M-TEER, the 1-year survival rate was 86.8%. M-TEER resulted in a significant reduction in both LA volume and estimated systolic pulmonary artery pressure (sPAP) levels (median LA volume: from 123 ml [interquartile range, IQR 92-169 ml] to 104 ml [IQR 78-142 ml], p < 0.001; median sPAP: from 46 mmHg [IQR 35-58 mmHg] to 41 mmHg [IQR 32-54 mmHg], p = 0.036). In contrast, TAPSE remained unchanged (median: from 17 mm [IQR 14-21 mm] to 18 mm [IQR 15-21 mm], p = 0.603). The deep learning model confirmed this finding, showing no significant change in predicted RVEF after M-TEER (median: from 43.1% [IQR 39.1-47.4%] to 43.2% [IQR 39.2-47.2%], p = 0.475).

conclusionsWhile M-TEER improves left-sided haemodynamics, it does not lead to significant RV function recovery, as confirmed by both conventional echocardiography and artificial intelligence. This finding underscores the importance of treating patients before irreversible right heart damage occurs.

Indexed as

Artificial IntelligenceCardiac CatheterizationHeart Valve Prosthesis ImplantationMitral ValveMitral Valve InsufficiencyVentricular Function, RightAgedEchocardiographyFemaleFollow-Up StudiesHumansMaleRecovery of FunctionRegistriesRetrospective StudiesStroke VolumeDeep learningEchocardiographyMitral regurgitationRight ventricular dysfunctionTranscatheter edge‐to‐edge repair

Identifiers

PMID40488515
PMCPMC12765041

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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.