Juliana Rolim Vieira Maciel , Eduardo Yoshio Nakano , Kênia Mara Baiocchi de Carvalho , Eliane Said Dutra
{"title":"STRONGkids验证:工具准确性","authors":"Juliana Rolim Vieira Maciel , Eduardo Yoshio Nakano , Kênia Mara Baiocchi de Carvalho , Eliane Said Dutra","doi":"10.1016/j.jpedp.2019.05.006","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><p>Validate the accuracy of the Screening Tool for Risk on Nutritional status and Growth (STRONGkids) and estimate the prevalence of malnutrition and nutritional risk in hospitalized children.</p></div><div><h3>Methods</h3><p>Cross‐sectional study of a representative sample of children admitted to ten public pediatric emergency rooms. The sample was randomly estimated in stages, including children older than 30 days and younger than 10 years of age, of both sexes, excluding syndromic children and those in whom it was impossible to directly measure anthropometry. Weight, height, and arm circumference were measured, as well as the <em>Z</em>‐scores of the anthropometric indices weight‐for‐age, height‐for‐age, weight‐for‐height, body mass index for age, and arm circumference for age, classified according to the reference curves of the World Health Organization. After the tool was applied, its accuracy tests were performed in comparison with the anthropometric data, with the evaluation of sensitivity, specificity, and positive and negative predictive values.</p></div><div><h3>Results</h3><p>A total of 271 children were evaluated, 56.46% males and 41.70% younger than 2 years of age. The prevalence rates of malnutrition, nutritional risk assessed by anthropometric measurements, and nutritional risk assessed by the tool were 12.18%, 33.95%, and 78.60%, respectively. Accuracy showed sensitivity of 84.8%, specificity of 26.7%, positive predictive value of 49.8%, and negative predictive value of 67.2%, when the patients at nutritional risk were identified by anthropometry.</p></div><div><h3>Conclusion</h3><p>Validation of the accuracy of STRONGkids was performed, showing high sensitivity, allowing the early identification of nutritional risk in similar populations.</p></div>","PeriodicalId":100742,"journal":{"name":"Jornal de Pediatria (Vers?o em Português)","volume":"96 3","pages":"Pages 371-378"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.jpedp.2019.05.006","citationCount":"0","resultStr":"{\"title\":\"STRONGkids validation: tool accuracy\",\"authors\":\"Juliana Rolim Vieira Maciel , Eduardo Yoshio Nakano , Kênia Mara Baiocchi de Carvalho , Eliane Said Dutra\",\"doi\":\"10.1016/j.jpedp.2019.05.006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><p>Validate the accuracy of the Screening Tool for Risk on Nutritional status and Growth (STRONGkids) and estimate the prevalence of malnutrition and nutritional risk in hospitalized children.</p></div><div><h3>Methods</h3><p>Cross‐sectional study of a representative sample of children admitted to ten public pediatric emergency rooms. The sample was randomly estimated in stages, including children older than 30 days and younger than 10 years of age, of both sexes, excluding syndromic children and those in whom it was impossible to directly measure anthropometry. Weight, height, and arm circumference were measured, as well as the <em>Z</em>‐scores of the anthropometric indices weight‐for‐age, height‐for‐age, weight‐for‐height, body mass index for age, and arm circumference for age, classified according to the reference curves of the World Health Organization. After the tool was applied, its accuracy tests were performed in comparison with the anthropometric data, with the evaluation of sensitivity, specificity, and positive and negative predictive values.</p></div><div><h3>Results</h3><p>A total of 271 children were evaluated, 56.46% males and 41.70% younger than 2 years of age. The prevalence rates of malnutrition, nutritional risk assessed by anthropometric measurements, and nutritional risk assessed by the tool were 12.18%, 33.95%, and 78.60%, respectively. Accuracy showed sensitivity of 84.8%, specificity of 26.7%, positive predictive value of 49.8%, and negative predictive value of 67.2%, when the patients at nutritional risk were identified by anthropometry.</p></div><div><h3>Conclusion</h3><p>Validation of the accuracy of STRONGkids was performed, showing high sensitivity, allowing the early identification of nutritional risk in similar populations.</p></div>\",\"PeriodicalId\":100742,\"journal\":{\"name\":\"Jornal de Pediatria (Vers?o em Português)\",\"volume\":\"96 3\",\"pages\":\"Pages 371-378\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.jpedp.2019.05.006\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jornal de Pediatria (Vers?o em Português)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2255553619300874\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jornal de Pediatria (Vers?o em Português)","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2255553619300874","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Validate the accuracy of the Screening Tool for Risk on Nutritional status and Growth (STRONGkids) and estimate the prevalence of malnutrition and nutritional risk in hospitalized children.
Methods
Cross‐sectional study of a representative sample of children admitted to ten public pediatric emergency rooms. The sample was randomly estimated in stages, including children older than 30 days and younger than 10 years of age, of both sexes, excluding syndromic children and those in whom it was impossible to directly measure anthropometry. Weight, height, and arm circumference were measured, as well as the Z‐scores of the anthropometric indices weight‐for‐age, height‐for‐age, weight‐for‐height, body mass index for age, and arm circumference for age, classified according to the reference curves of the World Health Organization. After the tool was applied, its accuracy tests were performed in comparison with the anthropometric data, with the evaluation of sensitivity, specificity, and positive and negative predictive values.
Results
A total of 271 children were evaluated, 56.46% males and 41.70% younger than 2 years of age. The prevalence rates of malnutrition, nutritional risk assessed by anthropometric measurements, and nutritional risk assessed by the tool were 12.18%, 33.95%, and 78.60%, respectively. Accuracy showed sensitivity of 84.8%, specificity of 26.7%, positive predictive value of 49.8%, and negative predictive value of 67.2%, when the patients at nutritional risk were identified by anthropometry.
Conclusion
Validation of the accuracy of STRONGkids was performed, showing high sensitivity, allowing the early identification of nutritional risk in similar populations.