Malnutrition was an independent risk factor for readmission within 30 days or death within 90 days of discharge. Malnourished patients had higher rates of readmission, higher mortality rates, and longer lengths of stay and were more likely to be discharged to nursing homes.

Classification of a patient's nutrition status is important in the delivery of cost-effective health care. The Department of Veterans Affairs' nutrition status classification is a good one for assessing nutrition status quickly and reliably, especially when an algorithm is used. The results underscore the advantages of a classification system based on an algorithm when the system is designed to be used by many different staff across multiple facilities.

No abstract

Background: Identification of intensive care unit (ICU) patients who require nutrition intervention is crucial to initiating nutrition therapy. This prospective quality improvement study evaluated the Nutritional Risk Screening (NRS) 2002, Malnutrition Universal Screening Tool (MUST), and Nutrition Risk in Critically Ill (NUTRIC) score in comparison with the Veterans Administration Nutrition Status Classification (VANSC) tool to determine which best identified the need for nutrition intervention. Methods: A convenience sample of 150 ICU patients was evaluated using the VANSC, NRS 2002, MUST, and the NUTRIC score. The resultant score, need for nutrition intervention, and presence of malnutrition were recorded for patients. Interventions were defined as need for enteral or parenteral nutrition, nutritional supplements, or diet change. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), Matthews Correlation Coefficient (MCC), F1 score, and accuracy to predict need for nutrition intervention were calculated for each screening tool. Results: Of the 150 patients, 49 (33%) required 1 or more nutrition interventions. The NRS 2002 (0.878) and VANSC (0.816) had the highest sensitivity. The NUTRIC (0.921) and VANSC (0.911) had the highest specificity. The VANSC (0.816) and MUST (0.687) had the highest PPV. The VANSC (0.911) and NRS 2002 (0.872) had the highest NPV. The VANSC (0.727) and MUST (0.528) had the highest MCC. The VANSC (0.816) and MUST (0.680) had the highest F1 score. Conclusions: Trialing several tools to identify their efficacy and reliability individual setting may help determine the most appropriate tool to utilize for your patient population and specific goals. (Nutr Clin Pract. 2019;34:414-420)

BackgroundLow muscle mass has been correlated with adverse outcomes in patients who are critically ill. Methods to identify low muscularity such as computed tomography scans or bioelectrical impedance analyses are impractical for admission screening. Urinary creatinine excretion (UCE) and creatinine height index (CHI) are associated with muscularity and outcomes but require a 24‐h urine collection. The estimation of UCE from patient variables avoids the need for a 24‐h urine collection and may be clinically useful.MethodsVariables of age, height, weight, sex, plasma creatinine, blood urea nitrogen (BUN), glucose, sodium, potassium, chloride, and carbon dioxide from a deidentified data set of 967 patients who had UCE measured were used to develop models to predict UCE. The model identified with the best predictive ability was validated and then retrospectively applied to a separate sample of 120 veterans who were critically ill to examine if UCE and CHI predicted malnutrition or were associated with outcomes.ResultsA model was identified that included variables of plasma creatinine, BUN, age, and weight and was found to be highly correlated, moderately predictive of UCE, and statistically significant. Patients with model‐estimated CHI  60% had significantly lower body weight, body mass index, plasma creatinine, and sera albumin and prealbumin levels; were 8.0 times more likely to be diagnosed with malnutrition; and were 2.6 times more likely to be readmitted in 6 months.ConclusionA model that predicts UCE offers a novel method to identify patients with low muscularity and malnutrition on admission without the use of invasive tests.