Evidence map›Paper›PMID 39438502›Full record

ArticleScientific reports2024

Assessment of the relationship between central venous pressure waveform and the severity of tricuspid valve regurgitation using data science.

Shinichi Akabane, Masaaki Asamoto, Seiichi Azuma, Mikiya Otsuji, Kanji Uchida

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Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Shinichi AkabaneDepartment of Anesthesiology and Pain Relief Center, The University of Tokyo Hospital, Tokyo, Japan.
Masaaki AsamotoDepartment of Anesthesiology and Pain Relief Center, The University of Tokyo Hospital, Tokyo, Japan. ASAMOTOM-ANE@h.u-tokyo.ac.jp.ORCID 0000-0002-0770-2860
Seiichi AzumaDepartment of Anesthesiology and Pain Relief Center, The University of Tokyo Hospital, Tokyo, Japan.ORCID 0000-0002-7140-3320
Mikiya OtsujiDepartment of Anesthesiology, Tokyo Teishin Hospital, Tokyo, Japan.
Kanji UchidaDepartment of Anesthesiology and Pain Relief Center, The University of Tokyo Hospital, Tokyo, Japan.ORCID 0000-0001-9337-1916

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose The relationship between the height of the V wave in the central venous pressure (CVP) waveform and the severity of tricuspid regurgitation (TR) is well known. Their diagnostic ability is unconfirmed. This study explored CVP waveform variations with TR. Methods All patients who underwent preoperative echocardiography and CVP waveform measurements before surgery at our institution were included. Indices were created to capture each feature of the CVP waveform. The median value for each case was obtained and statistically analyzed according to the severity of TR. A deep learning technique, Transformer, was used to handle the complex features of CVP waveforms. Results This study included 436 cases. The values for C wave - Y descent, X descent - Y descent, and V wave - Y descent differed significantly in the Jonckheere-Terpstra test (p = 0.0018, 0.027, and 0.077, respectively). The area under the receiver operating characteristic (ROC) curve (AUC) for X descent - Y descent in two groups, none to moderate TR and severe TR, was 0.83 (95% confidence interval (CI) [0.68, 0.98]). For Transformer, the accuracy of the validation dataset was 0.97. Conclusions The shape of the CVP waveform varied with the severity of TR in a large dataset.

Indexed as

Central Venous PressureEchocardiographySeverity of Illness IndexTricuspid Valve InsufficiencyAgedFemaleHumansMaleMiddle AgedRetrospective StudiesROC Curve

Identifiers

PMID39438502
PMCPMC11496678

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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.