Evaluation of the risk of malnutrition in hospitalized children by PYMS, STAMP, and STRONGkids tools and comparison with their anthropometric indices: a cross-sectional study

Abstract

Background Malnutrition is a determining factor of pediatric mortality and morbidity, especially in low and middle-income countries. Hospitalized children are at a higher risk of malnutrition. Several malnutrition screening tools have been used, among which STAMP, PYMS, and STRONGkids are valid tools with high sensitivity and specificity. The aim of this study was to compare these screening tools to find the best ones in identifying the risk of malnutrition in hospitalized children. Methods This is a cross-sectional study performed on hospitalized children aged 1 to 16 years. The questionnaires of PYMS, STAMP, STRONGkids malnutrition risk assessment tools were filled. The weight for height and BMI for age Z-scores were calculated. The data were analyzed by SPSS. Sensitivity, specificity, positive predictive value, and negative predictive values of the risk scores based on weight for height and BMI for age Z-scores were calculated. Results Ninety-three patients with a mean age of 5.53 ± 3.9 years were included. The frequency of malnutrition was reported as 26% and 39% according to weight for height and BMI for age Z-scores, respectively. A significant relationship was found between PYMS and Weight for height Z-score (P-value < 0.001), and BMI for age Z-score (P-value < 0.001). Moreover, STRONGkids was found to be associated with weight for height Z-score (P-value: 0.017). Conclusion The PYMS is a practical and beneficial tool in early identifying the risk of severe malnutrition in hospitalized patients. It is a suitable method for patients in our settings.

The Role of the Pediatric Yorkhill Malnutrition Score (PYMS), Neutrophil-to-Lymphocyte and Platelet-to-Lymphocyte Ratios in Malnutrition Prediction of Hospitalized Children

“…Moreover, in our study, half of the population (50.5%) was boys, which is comparable with yielded percentages of other pediatric malnutrition studies with an inclusion rate of boys 56.9–58% [ 25 ]. Furthermore, the calculated mean BMI of this study (18 kg/m 2 ) is slightly higher than that of other published studies [ 25 , 26 ]. Regarding the hospitalization duration, the mean 4.2 days of our data parallels the length of stay reported in equivalent studies elsewhere [ 25 , 26 , 27 ].…”

“…Furthermore, the calculated mean BMI of this study (18 kg/m 2 ) is slightly higher than that of other published studies [ 25 , 26 ]. Regarding the hospitalization duration, the mean 4.2 days of our data parallels the length of stay reported in equivalent studies elsewhere [ 25 , 26 , 27 ].…”

“…Regarding the diagnoses’ spectrum, we found that infectious diseases were the most predominant ones (cumulatively 55.1%), which was followed by traumatic head injury (8.4%) and appendicitis (6.3%). Likewise, Malekiantaghi et al [ 26 ] included in their malnutrition cohort hospitalized children with 43% of the sample consisting of infectious diagnoses and 41% consisting of surgical ones. The frequency of the diagnoses was investigated by Katsagoni et al [ 25 ] in an adequate sample of 1506 children investigating malnutrition in hospitalized patients: gastrointestinal disease (26%), minor surgeries (23.8%), neurological disorders (12.2%), and respiratory disorders (9.5%).…”

Avaliação nutricional de crianças e adolescentes internados em um hospital filantrópico no município de Aracaju

“…Outro ponto substancial, foi o número de pacientes com magreza e magreza acentuada em maiores de dois anos pelo score do IMC/I, o qual é um ótimo avaliador do estado nutricional de crianças e adolescentes. Consoante com tal informação, um estudo transversal, com crianças de 1 a 16 anos que foram internadas por mais de 48 h nas enfermarias de infecção, geral e cirurgia de um hospital pediátrico terciário, Bahrami Children Hospital, Teerã, (Irã), também obteve um número significativo de crianças desnutridas (Malekiantaghi et al, 2022).…”

“…Quanto a avaliação do risco nutricional, a aplicação da STRONGkids considerou risco moderado e alto em 64,25% da amostra para desnutrição. Houve conformidade com a pesquisa realizada por (Malekiantaghi et al, 2022), na qual também foi demonstrada a sensibilidade da STRONGKids em detectar o risco nutricional. Vale destacar, que a STRONGkids considera que todos os pacientes possuem risco nutricional, pois, segundo as instruções dessa ferramenta, um escore nulo já define um risco nutricional baixo, não havendo a classificação de pacientes sem risco nutricional.…”