[A nomogram prediction model for individualized prediction of the risk of covert (minimal) hepatic encephalopathy occurrence in patients with liver cirrhosis].

<b>Objective:</b> To construct an individualized nomogram prediction model for predicting the risk of the occurrence of covert hepatic encephalopathy (CHE) in patients with liver cirrhosis. <b>Methods:</b> 325 cases of liver cirrhosis admitted from January 2020 to December 2022 were selected as the study subjects. Patients were divided into training (<i>n</i>=213) and validation (<i>n</i>=112) sets using a cluster randomization method. The risk factors for CHE occurrence in patients with cirrhosis in the training set were analyzed by univariate and multivariate logistic regression. A prediction model related to the nomogram was established. <b>Results:</b> Independent risk factors for the occurrence of CHE in patients with cirrhosis were a history of hepatic encephalopathy, co-infection, gastrointestinal bleeding, severe ascites, prothrombin time ≥16 seconds, high total bilirubin, and high blood ammonia levels (<i>P</i><0.05). Nomogram model validation results: The model had a net benefit for the training and validation sets, with C-indices of 0.830 (95%<i>CI</i>: 0.802-0.858) and 0.807 (95%<i>CI</i>: 0.877-0.837), respectively, within the range of 0-96%. The calibration curves of both sets were evenly close to the ideal curves. The AUCs for the ROC curves in both sets were 0.827 (95%<i>CI</i>: 0.796-0.858) and 0.811 (95%<i>CI</i>: 0.787-0.836), respectively. <b>Conclusion:</b> Patients with cirrhosis have many risk factors for CHE occurrence. The nomogram model constructed based on these risk factors possesses a good predictive value for assessing CHE occurrence in cirrhotic patients.