Pereira Danielly S, da Silva Vitória M, Luz Gabriela D, Silva Flávia M, Dalle Molle Roberta
Programa de Pós-Graduação em Ciências da Nutrição, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, Rio Grande do Sul, Brazil.
Curso de Graduação em Nutrição, Centro Universitário Cesuca, Cachoeirinha, Rio Grande do Sul, Brazil.
JPEN J Parenter Enteral Nutr. 2023 Feb;47(2):184-206. doi: 10.1002/jpen.2462. Epub 2022 Dec 5.
Nutrition screening (NS) allows health professionals to identify patients at nutritional risk (NR), enabling early nutrition intervention. This study aimed to systematically review the criterion validity of NS tools for hospitalized non-critical care pediatric patients and to estimate the prevalence of NR in this population. This research was performed using PubMed, Embase, and Scopus databases until June 2021. The reviewers extracted the studies' general information, the population characteristics, the NR prevalence, and the NS tools' concurrent and predictive validity data. Quality evaluation was performed using the Newcastle-Ottawa Scale, adapted Newcastle-Ottawa Scale, and Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). The primary studies were qualitatively analyzed, and descriptive statistics were calculated to describe the NR prevalence. Of the total 3944 studies found, 49 met the inclusion criteria. Ten different pediatric NS tools were identified; the most frequently used were Screening Tool for Risk on Nutritional Status and Growth (STRONGkids), Screening Tool for the Assessment of Malnutrition in Pediatrics (STAMP), and Pediatric Yorkhill Malnutrition Score (PYMS). The mean NR prevalence was 59.85% (range, 14.6%-96.9%). Among all NS tools analyzed, STRONGkids and PYMS showed the best diagnostic performance. STRONGkids had the most studies of predictive validity showing that the NR predicted a higher hospital length of stay (odds ratio [OR], 1.96-8.02), health complications during hospitalization (OR, 3.4), and the necessity for nutrition intervention (OR, 18.93). Considering the diagnostic accuracy, robust and replicated findings of predictive validity, and studies' quality, STRONGkids performed best in identifying NR in the pediatric population among the tools identified.
营养筛查(NS)可使医疗专业人员识别有营养风险(NR)的患者,从而实现早期营养干预。本研究旨在系统评价NS工具对非重症监护住院儿科患者的标准效度,并估计该人群中NR的患病率。本研究使用PubMed、Embase和Scopus数据库进行,检索截至2021年6月的文献。评审人员提取了研究的一般信息、人群特征、NR患病率以及NS工具的同时效度和预测效度数据。使用纽卡斯尔-渥太华量表、改编的纽卡斯尔-渥太华量表和诊断准确性研究质量评估(QUADAS-2)进行质量评估。对主要研究进行定性分析,并计算描述性统计量以描述NR患病率。在总共找到的3944项研究中,49项符合纳入标准。确定了10种不同的儿科NS工具;最常用的是营养状况和生长风险筛查工具(STRONGkids)、儿科营养不良评估筛查工具(STAMP)和儿科约克希尔营养不良评分(PYMS)。NR的平均患病率为59.85%(范围为14.6%-96.9%)。在所有分析的NS工具中,STRONGkids和PYMS表现出最佳的诊断性能。STRONGkids关于预测效度的研究最多,表明NR可预测更长的住院时间(比值比[OR],1.96-8.02)、住院期间的健康并发症(OR,3.4)以及营养干预的必要性(OR,18.93)。考虑到诊断准确性、预测效度的可靠且重复的结果以及研究质量,在已识别的工具中,STRONGkids在识别儿科人群中的NR方面表现最佳。