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Introduction: Nutritional screening is a fundamental aspect of the initial evaluation of the hospitalised patient. Body Mass Index (BMI) in association with other parameters is a good marker of malnutrition (<18.5 kg/m2), but it presents the handicap that the great majority of patients cannot be weighed and measured. For this reason it is necessary to find other indicators that can be measured in these patients., Objectives: 1) Analyse the relationship between BMI and Mid-Upper Arm Circumference (MUAC); 2) establish a cut-off point of MUAC equivalent to BMI <18.5 kg/m2., Materials and Methods: The anthropometric data of patients hospitalised over the period 2004-2013 were retrospectively revised. The following variables were collected: weight, height, BMI, MUAC, sex and age., Results: 1373 patients were evaluated, who presented a mean weight of: 65.04±15.51 kg; height: 1.66±0.09 m; BMI: 23.48±5.03 kg/m2; MUAC: 26.95±4.50 cm; age: 56.24±16.77. MUAC correlates suitably to BMI by means of the following equation (simple linear regression): BMI = - 0.042 + 0.873 x MUAC (cm) (R2 = 0.609), with a Pearson r value of 0.78 (p<0.001). The area under the curve of MUAC for the diagnosis of malnutrition was 0.92 (95% CI: 0.90-0.94; p<0.001). The MUAC value ≤22.5 cm presented a sensitivity of 67.7%, specificity of 94.5%, and a correct classification of 90%. No significant statistical differences were found in the cut-off point of MUAC for the diagnosis of malnutrition based on sex (p = 0.115) and age (p = 0.694)., Conclusions: 1) MUAC correlates positively and significantly with BMI. 2) MUAC ≤ 22.5 cm correlates properly with a BMI of <18.5 kg/m2, independent of the age or sex of the patient, although there are other alternatives. MUAC constitutes a useful tool as a marker of malnutrition, fundamentally in patients for whom weight and height cannot be determined.

Background: Malnutrition is highly prevalent in hospitalized patients and results in a worsened clinical course as well as an increased length of stay, mortality, and costs. Therefore, simple nutrition screening systems, such as CIPA (control of food intake, protein, anthropometry), may be implemented to facilitate the patient's recovery process. The aim of this study is to evaluate the effectiveness and cost-effectiveness of implementing such screening tool in a tertiary hospital, consistent with the lack of similar, published studies on any hospital nutrition screening system.Methods: The present study is carried out as an open, controlled, randomized study on patients that were admitted to the Internal Medicine and the General and Digestive Surgery ward; the patients were randomized to either a control or an intervention group (n = 824, thereof 412 patients in each of the two study arms). The control group underwent usual inpatient clinical care, while the intervention group was evaluated with the CIPA screening tool for early detection of malnutrition and treated accordingly. CIPA nutrition screening was performed upon hospital admission and classified positive when at least one of the following parameters was met: 72 h food intake control < 50%, serum albumin < 3 g/dL, body mass index < 18.5 kg/m2 (or mid-upper arm circumference ≤ 22.5 cm). In this case, the doctor decided on whether or not providing nutrition support. The following variables will be evaluated: hospital length of stay (primary endpoint), mortality, 3-month readmission, and in-hospital complications. Likewise, the quality of life questionnaires EQ-5D-5 L are being collected for all patients at hospital admission, discharge, and 3 months post-discharge. Analysis of cost-effectiveness will be performed by measuring effectiveness in terms of quality-adjusted life years (QALYs). The cost per patient will be established by identifying health care resource utilization; cost-effectiveness will be determined through the incremental cost-effectiveness ratio (ICER). We will calculate the incremental cost per QALY gained with respect to the intervention.Discussion: This ongoing trial aims to evaluate the cost-effectiveness of implementing the malnutrition screening tool CIPA in a tertiary hospital.Trial Registration: Clinical Trial.gov ( NCT02721706 ). First receivevd: March 1, 2016 Last updated: April 8, 2017 Last verified: April 2017. [ABSTRACT FROM AUTHOR]