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Nomogram and Validity of a Model for Predicting Malnutrition in Patients on Liver Transplant Lists
María Teresa García-Rodríguez1, Sonia Pértega-Díaz2, Beatriz López-Calviño2
1Digestive Service, Instituto de Investigación Biomédica de A Coruña (INIBIC), Complexo Hospitalario Universitario de A Coruña (CHUAC), Xerencia de Xestión Integrada de A Coruña, SERGAS, Universidade da Coruña, Xubias de Arriba, 84, 15006, A Coruña, Spain. maria.teresa.garcia.rodriguez@sergas.es.
Background:
Malnutrition is associated with increased morbimortality in liver transplant patients, and it is important to identify factors related to nutritional status in these patients.
Aims:
Determine variables associated with malnutrition and create a nomogram in liver transplant candidates.
Methods:
Cross-sectional study (n = 110).
Variables:
demographic variables, imbalances due to the disease, transplant aetiology and analytical parameters. Physical examination was performed and degree of hepatic dysfunction calculated. Nutritional status was assessed: Controlling Nutritional Status, Spanish Society of Parenteral and Enteral Nutrition criteria, Nutritional Risk Index, Prognostic Nutritional Index or Onodera Index and The Subjective Global Assessment. Logistic regression analysis was performed. A predictive nomogram (discrimination and calibration analysis) was generated.
Results:
Malnourishment was defined according to at least 4 or more of the methods studied. Patients with ascites, encephalopathy and portal hypertension presented malnourishment more frequently. Malnutrition was associated with greater liver dysfunction and lower grip strength. Variables independently associated with malnourishment were encephalopathy and lower albumin values. A nomogram was created to predict malnourishment, with good discriminatory power and calibration.
Conclusions:
A score was developed for evaluating malnutrition risk. This would provide a tool that makes it possible to quickly and easily identify the risk of malnutrition in liver transplant candidates.
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