Evidence map›Paper›PMID 41135549›Full record

ArticleProgress in biomedical engineering (Bristol, England)2025

Predicting procedural outcomes in transcatheter aortic valve implantation: a scoping review of numerical patient-specific simulations.

Benedetta Grossi, Letizia Maria Perri, Valeria Raona, Ottavia Cozzi, Francesco Migliavacca, Gianluigi Condorelli, Giulio Stefanini, Giulia Luraghi

Abstract readScoping Review
In one paragraph

Article in Progress in biomedical engineering (Bristol, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Benedetta GrossiIRCCS Humanitas Research Hospital, Via Alessandro Manzoni 56, 20089 Rozzano, Milan, Italy.
Letizia Maria PerriDepartment of Chemistry, Materials and Chemical Engineering, Politecnico di Milano, Piazza L. da Vinci 32, 20133 Milan, Italy.ORCID 0009-0008-3298-2981
Valeria RaonaDepartment of Chemistry, Materials and Chemical Engineering, Politecnico di Milano, Piazza L. da Vinci 32, 20133 Milan, Italy.ORCID 0009-0007-2341-5873
Ottavia CozziIRCCS Humanitas Research Hospital, Via Alessandro Manzoni 56, 20089 Rozzano, Milan, Italy.
Francesco MigliavaccaDepartment of Chemistry, Materials and Chemical Engineering, Politecnico di Milano, Piazza L. da Vinci 32, 20133 Milan, Italy.ORCID 0000-0003-4644-630X
Gianluigi CondorelliIRCCS Humanitas Research Hospital, Via Alessandro Manzoni 56, 20089 Rozzano, Milan, Italy.
Giulio StefaniniIRCCS Humanitas Research Hospital, Via Alessandro Manzoni 56, 20089 Rozzano, Milan, Italy.
Giulia LuraghiDepartment of Chemistry, Materials and Chemical Engineering, Politecnico di Milano, Piazza L. da Vinci 32, 20133 Milan, Italy.ORCID 0000-0002-0434-8544

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcatheter aortic valve implantation (TAVI)-related post-operative complications remain significant clinical challenges, and current in-silico simulations fall short in predicting them accurately, limiting their clinical applicability. This scoping review evaluates the state of the art in TAVI computational modeling, identifying methodological gaps and proposing directions for refinement to enhance translational impact. Following PRISMA-ScR guidelines, 40 studies were included, with data extracted and summarized by evaluated outcomes. A quality assessment was performed using a 14-item rubric. Most studies focused on predicting paravalvular leak (65%) and conduction disturbances (20%). This review reveals substantial heterogeneity in modeling approaches, with limited standardization and varying degrees of validation. To improve clinical relevance, future efforts should prioritize model standardization, rigorous validation following ASME V&V guidelines, increased automation, and improved interpretability for clinical users. By ensuring robustness, efficiency, and clinical accessibility, in-silico models could transform TAVI outcome prediction and support personalized treatment planning, ultimately enhancing care standards in structural heart interventions.

Indexed as

Models, CardiovascularPatient-Specific ModelingTranscatheter Aortic Valve ReplacementComputer SimulationHumansTreatment Outcomeclinical outcome predictionpatient-specific numerical simulationssystematic reviewTAVI

Identifiers

PMID41135549
PMCPMC7619166

What OpenQuestion holds

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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.