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  • Title: Complementarity of nutritional assessment tools to predict prolonged hospital stay and readmission in older patients with solid tumors: A secondary analysis of a cohort study.
    Author: Stefani GP, Crestani MS, Scott LM, Soares CH, Steemburgo T.
    Journal: Nutrition; 2023 Sep; 113():112089. PubMed ID: 37354653.
    Abstract:
    OBJECTIVE: The aim of this study was to investigate the complementarity of five nutritional risk screening tools (Nutritional Risk Screening 2002 [NRS-2002], Malnutrition Screening Tool [MST], Malnutrition Universal Screening Tool [MUST], Mini-Nutritional Assessment-Short Form [MNA-SF], and Patient-Generated Subjective Global Assessment SF [PG-SGA SF]) combined with three malnutrition diagnostic tools (SGA, PG-SGA, and Global Leadership Initiative on Malnutrition [GLIM]) and their ability to predict poor clinical outcomes in older patients with cancer. METHODS: Using data collected within 48 h of hospital admission, we conducted a prospective cohort study on nutritional risk (NRS-2002, MST, MUST, MNA-SF, and PG-SGA SF) and the presence of malnutrition (SGA, PG-SGA, and GLIM). Patients were grouped according to their nutritional risk and malnutrition status. Accuracy tests and logistic regression analysis were used to evaluate the ability of the combined tools to predict hospital length of stay and readmission. We evaluated 248 older patients (69.7 ± 7.2 y of age, 59.7% men; 27.4% with gastrointestinal tumors). The median length of stay was 4 d (3-9 d), and 65.3% of patients remained hospitalized for ≥ 4 d. RESULTS: The NRS-2002 combined with SGA and MST combined with SGA and GLIM had the highest specificity (> 80%) for predicting hospitalization. Nutritional risk assessed by MNA-SF and malnutrition assessed by PG-SGA were associated with 2.48- and 6.04-fold increased likelihood of hospitalization (≥ 4 d) and readmission (60 d), respectively. CONCLUSION: Concomitant application of MNA-SF (specific for older patients) with PG-SGA (specific for patients with cancer) might enhance the ability to predict length of stay and readmission in hospitalized older patients with solid tumors.
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