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Development and validation of a predictive nomogram for myopenia in patients with decompensated cirrhosis
Xiaona Yuan1, Xin Yang2, Xueming Du2
1Department of Emergency Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Background And Aims:
Myopenia is common in patients with cirrhosis and is associated with adverse clinical outcomes. However, current methods for assessing and diagnosing muscle depletion limit their application. In this study, we aimed to develop a simple and reliable nomogram to identify concurrent myopenia in patients with decompensated cirrhosis (DC).
Methods:
A total of 462 patients with DC at Wuhan Union Hospital between January 2015 and August 2022 were included. They were randomly divided into either the development cohort (n = 323) or the validation cohort (n = 139). Independent risk factors were screened to establish the risk prediction nomogram of myopenia using multivariate logistic regression analysis. Discrimination, accuracy, and clinical utility values were evaluated by receiver operating characteristic curves, calibration curves, decision curve analysis, and clinical impact plots.
Results:
Hematemesis, corrected body mass index (BMI), and fibrinogen were effectively identified as predictors of myopenia in patients with DC. The nomogram showed an area under the curve of 0.748 and 0.795 in the development and validation cohorts. The sensitivity, specificity, and Youden index of the development cohort were 47.7 and 89.2%, and 0.369, respectively. Calibration curves and decision curve analysis confirmed great accuracy and clinical utility.
Conclusion:
We developed and internally validated a nomogram to identify myopenia in patients with DC, which may support timely nutritional and functional evaluation.
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