AHEAD OF PRINT BRIEF C MMU ICATION

Background – Malnutrition is associated with clinical factors, including longer hospital stay, increased morbidity and mortality and hospital costs. Objective – To investigate the prevalence of malnutrition using different nutritional indicators and to identify factors that contribute to malnutrition in hospitalized patients. Methods – We investigated anthropometric, laboratory standards, nutritional risk screening (NRS), subjective global assessment (SGA), mini nutritional assessment and habitual energy consumption (HEC). Chi-square, Fisher’s exact test, Mann-Whitney test and univariate and multiple Cox regression analysis were used, at 5% significance level. Results – It was found 21.01% of malnourished individuals by ASG; a total of 34.78% with nutritional risk according to NRS and 11.59% with low weight (BMI). There was no statistically significant difference in the prevalence of malnutrition by ASG (P=0.3344) and nutritional risk by NRS (P=0.2286), among the types of disorders. Patients with nutritional risk were of higher median age (64.5 vs 58.0 years; P=0.0246) and had lower median values of HEC (1362.1 kcal vs 1525 kcal, P=0.0030), of calf circumference (32.0 cm vs 33.5 cm, P=0.0405) of lymphocyte count (1176.5 cell/mm3 vs 1760.5 cell/ mm3, P=0.0095); and higher percentage of low body weight according to the BMI (22.9% vs 5.6%; P=0.0096). Lymphocyte count was associated with nutritional risk (P=0.0414; HR= 1.000; IC95%= 0.999; 1.000). Conclusion – NRS was more sensitive than other indicators in the diagnosis of malnutrition. Patients at risk were older and had lower HEC values, calf circumference, BMI and lymphocyte count. Low lymphocyte count was considered a factor associated with nutritional risk by the NRS. HEADINGS – Health status indicators. Malnutrition. Nutrition assessment. Nutritional status. Declared conflict of interest of all authors: none Disclosure of funding: no funding received 1 PUC, Programa de Pós-Graduação em Ciências da Saúde, Campinas, SP, Brasil. 2 PUC, Faculdade de Nutrição, Campinas, SP, Brasil. 3 PUC, Faculdade de Medicina, Campinas, SP, Brasil. Corresponding author: Vânia Aparecida Leandro Merhi. E-mail: valm@puc-campinas.edu. br of clinical and nutritional data in medical records and assessment of nutritional status during the first 24 hours of hospitalization. Patients with incomplete entries for such information in the medical records and those hospitalized only for diagnostic investigation and exams were excluded. This study is part of a larger project that is investigating the presence of malnutrition in patients hospitalized for different kinds of diseases and indicators, previously approved by the institution’s ethics and research committee (opinion no. 2,312,714). We investigated variables such as age, sex, type of disease, hospitalization time, anthropometric and laboratory standards, nutritional screening tools, energy consumption and the kind of diet prescribed during hospitalization. Anthropometric and laboratory indicators According to standardized procedures and cutoff points defined in the literature, the body mass index (BMI) grading was used both for adults and the elderly(7,8). According to Frisancho (1990)(9) and Burr & Phillips (1984)(10), arm circumference (AC), triceps skinfold (TSF) and arm muscle circumference (AMC) were classified by percentiles grades. Calf circumference (CC) was classified according to WHO definition(11). Laboratory tests for lymphocyte count (LC) (cell/mm3), white blood cells (cell/mm3), erythrocytes (cm3), hematocrit (%), hemoglobin (g/dL) and MCV (fL) were classified according to standardized cut-off points(12). AG-2019-105 dx.doi. org/10.1590/S0004-2803.201900000-74 Leandro-Merhi VA, Costa CL, Saragiotto L, Aquino JLB. Nutritional indicators of malnutrition in hospitalized patients 448 • Arq Gastroenterol • 2019. v. 56 no 4 out/dez Nutritional screening tools (nutritional risk screening-NRS, subjective global assessment-SGA and mini nutritional assessment -MNA) For nutritional risk detection, NRS was applied(13,14). This method takes into account BMI, weight loss, decreased food intake and disease severity, classifying the risk by numerical score ≥3 (at risk) and <3 (no risk)(13,14). Based on weight loss, food consumption and clinical and physical signs of malnutrition, SGA subjectively assessed the patient’s nutritional status, being classified as: well-nourished-WN, slightly malnourished-SM, moderately malnourished-MM and gravely malnourished-GM(15). In this study, patients classified as SM, MM and GM, were considered as malnourished. MNA classifies the elderly as malnourished, risk of malnutrition and eutrophic, considering dietary and weight changes, physical evaluation, functional capacity, AC, CC, nutritional problems and disease(16). Percentage of adequacy of habitual energy consumption in relation to individual energy needs (% HEC/EN) The % HEC/EN was classified as <75% and ≥75%(2,17,18). This assessment was obtained through the investigation of habitual energy consumption (HEC). The energy requirements were estimated from the Harris & Benedict equation(19). Statistical analysis A descriptive analysis was performed with frequencies for categorical variables and position and dispersion measurements for continuous variables. To compare proportions, the chi-square or Fisher’s exact test was used when necessary. For the comparison of continuous or orderly measurements between two groups, the Mann-Whitney test was applied. Subsequently, univariate and multiple Cox regression analysis was used to identify the risk factors associated with SGA malnutrition and NRS nutritional risk. The variable selection process was performed stepwise. The level of significance adopted for the statistical tests was 5%(20-22). Ethical approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national Research Committee (CNS resolution no. 466/12).