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A predictive tool for the assessment of right ventricular dysfunction in non-high-risk patients with acute pulmonary embolism

BACKGROUND: Rapid and accurate identification of right ventricular (RV) dysfunction is essential for decreasing mortality associated with acute pulmonary embolism (PE), particularly for non-high-risk patients without hypotension on admission. This study aimed to develop a rapid and accurate tool for...

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Detalles Bibliográficos
Autores principales: Gao, Yizhuo, Chen, Lianghong, Jia, Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7842037/
https://www.ncbi.nlm.nih.gov/pubmed/33509132
http://dx.doi.org/10.1186/s12890-020-01380-8
Descripción
Sumario:BACKGROUND: Rapid and accurate identification of right ventricular (RV) dysfunction is essential for decreasing mortality associated with acute pulmonary embolism (PE), particularly for non-high-risk patients without hypotension on admission. This study aimed to develop a rapid and accurate tool for predicting the risk of RV dysfunction in non-high-risk patients with acute PE. METHODS: The medical records of non-high-risk patients with acute PE admitted to Shengjing Hospital of China Medical University between January 2011 and May 2020 were retrospectively analysed. The primary outcome of this study was RV dysfunction within 24 h after admission. The enrolled patients were randomized into training or validation sets as a ratio of 2:1. In the training set, a nomogram was developed, and the consistency was corroborated in the validation set. The areas under the receiver operating characteristic curves (AUCs) and 95% confidence intervals (CIs) were calculated. RESULTS: A total of 845 patients were enrolled, including 420 men and 425 women with an average age of 60.05 ± 15.43 years. Right ventricular dysfunction was identified in 240 patients (28.40%). The nomogram for RV dysfunction included N-terminal pro-brain natriuretic peptide, cardiac troponin I, and ventricular diameter ratios, which provided AUC values of 0.881 in the training dataset (95% confidence interval (CI): 0.868–0.898, p < 0.001) and 0.839 in the validation set (95% CI: 0.780–0.897, p < 0.001). The predictive tool was published as a web-based calculato (https://gaoyzcmu.shinyapps.io/APERVD/). CONCLUSIONS: The combination of CT and laboratory parameters forms a predictive tool that may facilitate the identification of RV dysfunction in non-high-risk patients with acute PE.