Evidence map›Paper›PMID 41538484›Full record

ReviewEinstein (Sao Paulo, Brazil)2026

Proposing the ValvUS approach: integrating bedside tests and ultrasonography for severe valvular heart disease diagnosis.

Tarso Augusto Duenhas Accorsi, Henrique Barbosa Ribeiro, Ranna Santos Pessoa, Renato Paladino Nemoto, Wilson Mathias Junior, Philippe Pibarot, Flavio Tarasoutchi

Abstract readReview
In one paragraph

Review in Einstein (Sao Paulo, Brazil), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Tarso Augusto Duenhas AccorsiInstituto do Coração (InCor), Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil.ORCID http://orcid.org/0000-0002-8023-3466
Henrique Barbosa RibeiroInstituto do Coração (InCor), Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil.ORCID http://orcid.org/0000-0003-1273-1823
Ranna Santos PessoaInstituto do Coração (InCor), Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil.ORCID http://orcid.org/0000-0002-8328-6758
Renato Paladino NemotoInstituto do Coração (InCor), Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil.ORCID http://orcid.org/0000-0002-0292-4288
Wilson Mathias JuniorInstituto do Coração (InCor), Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil.ORCID http://orcid.org/0000-0003-0201-6754
Philippe PibarotDepartment of Medicine, Québec Heart & Lung Institute, Laval University, Québec City, Québec, Canada.ORCID http://orcid.org/0000-0002-3607-279X
Flavio TarasoutchiInstituto do Coração (InCor), Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil.ORCID http://orcid.org/0000-0002-9964-3289

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Valvular heart disease is increasingly prevalent, and bedside confirmation or exclusion of severe disease is needed to enable a rapid and cost-effective diagnostic workup. The physical examination skills of clinicians are insufficient for accurate diagnosis, making complementary tests generally necessary. Despite being commonly requested, electrocardiography and chest radiography present low positive and negative likelihood ratios. Incipient studies involving artificial intelligence have shown promising opportunities to support the diagnosis. In addition, solid current evidence demonstrates that point-of-care ultrasound enhances bedside diagnosis of several cardiovascular conditions. Echocardiographic skills can be acquired after only a few hours of training, which encourages routine bedside use with handling equipment. Despite the routine use of sonography in emergencies, large-scale simplified screening protocols for valvular disease remain lacking. Therefore, improving the accuracy of valvular heart disease diagnosis by integrating all bedside modalities needs to be better understood. We propose a simple, reproducible five-step point-of-care ultrasound protocol for diagnosing valvular heart disease (the ValvUS approach), applicable to all patients. The proposed visual assessment involves evaluating valvular movement, thickness, regurgitant flow, aliasing, and chamber dimensions. This evaluation should be interpreted in the context of traditional clinical probability to ensure the most accurate bedside diagnosis. Typical findings of severe valvular disease on electrocardiography and chest radiography, and particularly on point-of-care ultrasound, may improve the accuracy of bedside diagnosis after clinical assessment in the near future.

Indexed as

EchocardiographyHeart Valve DiseasesPoint-of-Care SystemsPoint-of-Care TestingElectrocardiographyHumansSeverity of Illness IndexUltrasonography

Identifiers

PMID41538484
PMCPMC12711230

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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.