Evidence map›Paper›PMID 40980169›Full record

ArticleFrontiers in cardiovascular medicine2025

Construction of a right ventricular function assessment model in patients undergoing invasive mechanical ventilation based on VExUS grading and the classification and regression tree algorithm.

Jun Gao, Pan Gao, Yuanyuan Du, Jianjun Zhang, Jinrong Wang

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Article in Frontiers in cardiovascular medicine, 2025. 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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5 · Who and what money

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5 authors.

Jun Gao *Department of Critical Care Medicine, Harrison International Peace Hospital, Hengshui, China.
Pan Gao *Department of Critical Care Medicine, Harrison International Peace Hospital, Hengshui, China.
Yuanyuan Du *Department of Critical Care Medicine, Harrison International Peace Hospital, Hengshui, China.
Jianjun ZhangDepartment of Critical Care Medicine, Harrison International Peace Hospital, Hengshui, China.
Jinrong WangDepartment of Critical Care Medicine, Harrison International Peace Hospital, Hengshui, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Investigate the correlation between right ventricular function ultrasound indicators and the Venous Excess Ultrasound (VExUS) grading system in patients undergoing invasive mechanical ventilation (IMV), and develop a right ventricular function assessment model using VExUS grading and the Classification and Regression Tree (CART) algorithm. Methods: This cross-sectional study collected data from patients in the Department of Critical Care at Harrison International Peace Hospital who underwent tracheal intubation within 24-48 h from October 2023 to December 2024. Collected information comprised general clinical data, hematological indices, hemodynamic parameters, severity scores, right ventricular function ultrasound indicators, the maximum diameter of the inferior vena cava (IVCdmax), and Doppler spectra from the hepatic, portal and intrarenal veins. Patients were divided into two groups (VExUS 0 and VExUS ≥1) based on VExUS grading system to reflect the presence or absence of venous congestion. Baseline data were compared between groups, and Spearman's correlation analysis was performed to assess the relationship between VExUS grading and right ventricular function ultrasound indicators. Subsequently, a right ventricular function assessment model was constructed using the CART algorithm. Results: A total of 80 patients were enrolled, with 26 in the VExUS 0 group and 54 in the VExUS ≥1 group. In the VExUS ≥1 group, the proportion of male patients, levels of NT-proBNP, cTnI, central venous pressure, cumulative fluid balance, and the usage rate of diuretics were significantly higher than in the VExUS 0 group ( Conclusion: In patients undergoing IMV, IVCdmax, TAPSE, and the tricuspid E-wave peak show strong correlations with VExUS grading. A right ventricular function assessment model based on VExUS grading and the CART algorithm can effectively evaluate right ventricular performance and may serve as a useful tool in identifying venous congestion.

Indexed as

classification and regression tree (CART) algorithminvasive mechanical ventilationmodelright ventricular functionvenous excess ultrasound (VExUS) grading system

Identifiers

PMID40980169
PMCPMC12443755

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