4.7 Article

Liver Disease Undernutrition Screening Tool Questionnaire Predicts Decompensation and Mortality in Cirrhotic Outpatients with Portal Hypertension

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NUTRIENTS
卷 15, 期 17, 页码 -

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MDPI
DOI: 10.3390/nu15173780

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liver cirrhosis; LDUST; undernutrition; Child-Pugh; MELD

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This study evaluated the ability of the Liver Disease Undernutrition Screening Tool (LDUST) to predict mortality and decompensation in outpatients with clinically significant portal hypertension (CSPH). The results showed that LDUST could help identify patients in need of nutritional supplementation and intervention. Combining LDUST with Child and MELD scores improved their decompensation prediction.
Background: Numerous scores are designed to predict outcomes of patients with liver cirrhosis. Our study aimed to evaluate the ability of the Liver Disease Undernutrition Screening Tool (LDUST) in predicting mortality and decompensation in outpatients with clinically significant portal hypertension (CSPH). We hypothesized that LDUST could help identify patients in need of nutritional supplementation and intervention. Methods: A prospective study of 57 CSPH patients (36.8% female, mean age: 63.5 & PLUSMN; 9.9 years) with a median follow-up of 41 months was conducted. Baseline liver function, nutrition, and sarcopenia were assessed, alongside LDUST. During follow-up, the occurrence of liver decompensation, hospital admission, need for emergency care, and mortality were evaluated. Results: A total of 56.1% of patients were Child A, and the most frequent etiology was alcohol (50.9%). Malnutrition risk according to LDUST raised mortality (HR: 25.96 (1.47-456.78)), decompensation (HR 9.78 (2.08-45.89)), and admission (HR 4.86 (1.09-21.61)) risks in multivariate Cox analysis. Combining LDUST with Child and MELD scores improved their decompensation prediction (0.936 vs. 0.811 and 0.866 vs. 0.700). Conclusions: The LDUST has a solid ability to predict complications in cirrhosis outpatients with CSPH, and its integration with Child and MELD models enhances their predictive power. LDUST implementation could identify individuals necessitating early nutritional support.

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