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THE NUTRITIONAL STATUS OF HOSPITALIZED CHILDREN AND ADOLESCENTS: A COMPARISON BETWEEN TWO NUTRITIONAL ASSESSMENT TOOLS WITH ANTHROPOMETRIC PARAMETERS

OBJECTIVE: Verify the association between anthropometric indicators and the Subjective Global Assessment of Nutritional Status (SGA) and the Screening of Risk for Nutritional Status and Growth (STRONGkids) scales. METHODS: A cross-sectional study with patients from 0 to 18 years admitted in the Hosp...

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Detalles Bibliográficos
Autores principales: de Oliveira, Thaynara Cristina, de Albuquerque, Izabela Zibetti, Stringhini, Maria Luiza Ferreira, Mortoza, Andrea Sugai, de Morais, Bruna Alves
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sociedade de Pediatria de São Paulo 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5606174/
https://www.ncbi.nlm.nih.gov/pubmed/28977291
http://dx.doi.org/10.1590/1984-0462/;2017;35;3;00006
Descripción
Sumario:OBJECTIVE: Verify the association between anthropometric indicators and the Subjective Global Assessment of Nutritional Status (SGA) and the Screening of Risk for Nutritional Status and Growth (STRONGkids) scales. METHODS: A cross-sectional study with patients from 0 to 18 years admitted in the Hospital das Clínicas, Goiânia (GO), between August and November 2015. Children and adolescents admitted in up to 48 hours were included. Patients who required specific instruments for assessing their nutritional status and those hospitalized in Intensive Care were excluded. Identification and anthropometric data was collected and applied to the SGA and STRONGkids. We performed an analysis comparing proportions and did an agreement assessment, where p<0.05 was significant. RESULTS: 71 patients were evaluated, of whom 9.6% had low or very low birth weight/age, 9.7% had thinness or accentuated thinness according to the weight/height index, 16.9% had a height impairment, 7% were thin according to the body mass index/age, and 32.4% were malnourished with regard to arm muscle circumference. The STRONGkids detected that 69% of the sample had a moderate or high nutritional risk. According to the SGA, malnutrition prevalence was 38.1%. There was an association between the SGA and body mass index/age (p=0.022), height/age (p<0.001) and arm muscle circumference (p=0.014). There was no association between the STRONGkids and anthropometric indicators. A correlation was found between: high nutritional risk versus severe malnutrition and low nutritional risk x the well-nourished (p<0.001), but the agreement was weak (k=0.255). CONCLUSIONS: It is recommended to use the STRONGkids as a screening instrument because it has a higher sensitivity for diagnosing patients with a nutritional risk. The SGA should be applied to nutritional assessment due to its association with anthropometry.