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Establishment and validation of a nomogram for predicting esophagogastric variceal bleeding in patients with liver cirrhosis. | LitMetric

Establishment and validation of a nomogram for predicting esophagogastric variceal bleeding in patients with liver cirrhosis.

World J Gastroenterol

Department of Gastroenterology, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha 410008, Hunan Province, China.

Published: March 2025


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Article Abstract

Background: Patients with decompensated liver cirrhosis suffering from esophagogastric variceal bleeding (EGVB) face high mortality.

Aim: To investigate the risk factors for EGVB in patients with liver cirrhosis and establish a diagnostic nomogram.

Methods: Patients with liver cirrhosis who met the inclusion criteria were randomly divided into training and validation cohorts in a 6:4 ratio in this retrospective research. Univariate analysis, least absolute shrinkage and selection operator regression, and multivariate analysis were employed to establish the nomogram model. Calibration curve, the area under the receiver operating characteristic curve (AUC), and decision curve analysis (DCA) were applied to assess the discrimination, accuracy, and clinical practicability of the nomogram, respectively.

Results: A total of 1115 patients were enrolled in this study. The nomogram was established based on white blood cells ( < 0.001), hemoglobin ( < 0.001), fibrinogen ( < 0.001), total bilirubin ( 0.007), activated partial thromboplastin time ( = 0.002), total bile acid ( 0.012), and ascites ( 0.006). The calibration curve indicated that the actual observation results were in good agreement with the prediction results of the model. The AUC values of the diagnostic model were 0.861 and 0.859 in the training and validation cohorts, respectively, which were higher than that of the aspartate aminotransferase-to-platelet ratio index, fibrosis index based on 4 factors, and aspartate aminotransferase-to-alanine aminotransferase ratio. Additionally, DCA indicated that the net benefit value of the model was higher than that of the other models.

Conclusion: This research constructed and validated a nomogram with perfect performance for predicting EGVB events in patients with liver cirrhosis, which could help clinicians with timely diagnosis, individualized treatment, and follow-up.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11886047PMC
http://dx.doi.org/10.3748/wjg.v31.i9.102714DOI Listing

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