Predictive and concurrent validity of the Malnutrition Universal Screening Tool using mid‐upper arm circumference instead of body mass index. Issue 6 (8th May 2019)

• Record Type: Journal Article
• Authors: Gottschall, C.; Tarnowski, M.; Machado, P.; Raupp, D.; Marcadenti, A.; Rabito, E. I.; Silva, F. M.
• Is Part Of: Journal of human nutrition and dietetics. Volume 32:Issue 6(2019)
• Page Start: 775
• Page End: 780
• Publication Date: 2019-05-08
• Subjects: hospital -- mid‐upper arm circumference -- mortality -- nutritional screening; Dietetics -- Periodicals; Nutrition -- Periodicals; 613.205
• DOI: 10.1111/jhn.12665
• Languages: English
• ISSNs: 0952-3871

Abstract

Abstract: Background: Considering the difficulty in obtaining weight and height measurements of patients at hospital admission, the Malnutrition Universal Screening Tool (MUST) proposes the use of mid‐upper arm circumference (MUAC) instead of body mass index (BMI) as an alternative for screening of malnutrition risk. The present study aimed to evaluate the performance of MUST with MUAC in place of BMI to identify nutritional risk and predict prolonged hospitalisation and mortality in hospitalised patients. Methods: The prospective cohort study involved ambulant patients aged ≥18 years who were admitted to the emergency department of a public hospital. A questionnaire concerning clinical and socio‐demographic data was applied and anthropometric measurements were performed (weight, height, BMI and MUAC). Nutritional risk screening was performed using the original MUST (BMI) and MUST‐MUAC tools. The outcomes were length of hospital stay and death. Results: Seven hundred and fifty‐two patients were included and followed‐up for 13.5 (interquartile range 3.00–19.00) days. The frequency of patients at nutritional risk was higher according to MUST‐MUAC (48.9%) compared to the original MUST (37.1%). MUST‐MUAC showed concurrent validity, demonstrating good agreement with the original MUST ( k = 0.690), high sensitivity (95.3%) and accuracy (area under the curve = 0.868; 95% confidence interval = 0.841–0.895) with respect to identifying nutritional risk. The presence of nutritional risk detected by the MUST‐MUAC increased the chance of prolonged hospital stay by 1.9 (95% CI. 1.4–2.7)‐fold and mortality by 3.2 (95% CI. 1.1–9.4)‐fold. Conclusions: MUST‐MUAC showed satisfactory concurrent and predictive validity. Considering that MUAC measurement is easier to perform than BMI, the MUST‐MUAC should be used for screening of nutritional risk in hospitalised patients.