author_facet Carter, Laura E.
Shoyele, Grace
Southon, Sarah
Farmer, Anna
Persad, Rabin
Mazurak, Vera C.
BrunetWood, M. Kim
Carter, Laura E.
Shoyele, Grace
Southon, Sarah
Farmer, Anna
Persad, Rabin
Mazurak, Vera C.
BrunetWood, M. Kim
author Carter, Laura E.
Shoyele, Grace
Southon, Sarah
Farmer, Anna
Persad, Rabin
Mazurak, Vera C.
BrunetWood, M. Kim
spellingShingle Carter, Laura E.
Shoyele, Grace
Southon, Sarah
Farmer, Anna
Persad, Rabin
Mazurak, Vera C.
BrunetWood, M. Kim
Nutrition in Clinical Practice
Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best?
Nutrition and Dietetics
Medicine (miscellaneous)
author_sort carter, laura e.
spelling Carter, Laura E. Shoyele, Grace Southon, Sarah Farmer, Anna Persad, Rabin Mazurak, Vera C. BrunetWood, M. Kim 0884-5336 1941-2452 Wiley Nutrition and Dietetics Medicine (miscellaneous) http://dx.doi.org/10.1002/ncp.10367 <jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Identifying children at malnutrition risk on admission to hospital is considered best practice; however, nutrition screening in pediatric populations is not common. The aim of this study was to determine which screening tool is able to identify children with malnutrition on admission to hospital.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>A nurse administered 2 pediatric nutrition screening tools, Screening Tool for Risk on Nutritional Status and Growth (STRONGkids) and Pediatric Nutrition Screening Tool (PNST) to patients admitted to medicine and surgery units (n = 165). The Subjective Global Nutritional Assessment (SGNA) was then completed by a dietitian, blinded to the results of the screens. Sensitivity, specificity, and κ were calculated for both screening tools against the SGNA. A receiver operating characteristic (ROC) curve assessed alternate cutoffs for each tool. Length of hospital stay (LOS) was used to assess prospective validity.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Using the recommended cutoffs, the sensitivity of STRONGkids was 89%, specificity 35%, and κ 0.483. The sensitivity of PNST was 58%, specificity 88%, and κ 0.601. Using adjusted cutoffs, PNST's sensitivity improved to 87%, specificity 71%, and κ 0.681, and STRONGkids specificity improved to 61%, sensitivity 80%, and κ 0.5. Children identified at nutrition risk had significantly longer LOS (<jats:italic>P</jats:italic> &lt; 0.05).</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>This study showed neither tool was appropriate for clinical use based on published cutoffs. By adjusting the cutoffs using ROC curve analysis, both tools improved overall agreement with the SGNA without significantly impacting the prospective validity. PNST with adjusted cutoffs is the most appropriate for clinical use in this population.</jats:p></jats:sec> Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best? Nutrition in Clinical Practice
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title Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best?
title_unstemmed Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best?
title_full Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best?
title_fullStr Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best?
title_full_unstemmed Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best?
title_short Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best?
title_sort screening for pediatric malnutrition at hospital admission: which screening tool is best?
topic Nutrition and Dietetics
Medicine (miscellaneous)
url http://dx.doi.org/10.1002/ncp.10367
publishDate 2020
physical 951-958
description <jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Identifying children at malnutrition risk on admission to hospital is considered best practice; however, nutrition screening in pediatric populations is not common. The aim of this study was to determine which screening tool is able to identify children with malnutrition on admission to hospital.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>A nurse administered 2 pediatric nutrition screening tools, Screening Tool for Risk on Nutritional Status and Growth (STRONGkids) and Pediatric Nutrition Screening Tool (PNST) to patients admitted to medicine and surgery units (n = 165). The Subjective Global Nutritional Assessment (SGNA) was then completed by a dietitian, blinded to the results of the screens. Sensitivity, specificity, and κ were calculated for both screening tools against the SGNA. A receiver operating characteristic (ROC) curve assessed alternate cutoffs for each tool. Length of hospital stay (LOS) was used to assess prospective validity.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Using the recommended cutoffs, the sensitivity of STRONGkids was 89%, specificity 35%, and κ 0.483. The sensitivity of PNST was 58%, specificity 88%, and κ 0.601. Using adjusted cutoffs, PNST's sensitivity improved to 87%, specificity 71%, and κ 0.681, and STRONGkids specificity improved to 61%, sensitivity 80%, and κ 0.5. Children identified at nutrition risk had significantly longer LOS (<jats:italic>P</jats:italic> &lt; 0.05).</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>This study showed neither tool was appropriate for clinical use based on published cutoffs. By adjusting the cutoffs using ROC curve analysis, both tools improved overall agreement with the SGNA without significantly impacting the prospective validity. PNST with adjusted cutoffs is the most appropriate for clinical use in this population.</jats:p></jats:sec>
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author Carter, Laura E., Shoyele, Grace, Southon, Sarah, Farmer, Anna, Persad, Rabin, Mazurak, Vera C., BrunetWood, M. Kim
author_facet Carter, Laura E., Shoyele, Grace, Southon, Sarah, Farmer, Anna, Persad, Rabin, Mazurak, Vera C., BrunetWood, M. Kim, Carter, Laura E., Shoyele, Grace, Southon, Sarah, Farmer, Anna, Persad, Rabin, Mazurak, Vera C., BrunetWood, M. Kim
author_sort carter, laura e.
container_issue 5
container_start_page 951
container_title Nutrition in Clinical Practice
container_volume 35
description <jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Identifying children at malnutrition risk on admission to hospital is considered best practice; however, nutrition screening in pediatric populations is not common. The aim of this study was to determine which screening tool is able to identify children with malnutrition on admission to hospital.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>A nurse administered 2 pediatric nutrition screening tools, Screening Tool for Risk on Nutritional Status and Growth (STRONGkids) and Pediatric Nutrition Screening Tool (PNST) to patients admitted to medicine and surgery units (n = 165). The Subjective Global Nutritional Assessment (SGNA) was then completed by a dietitian, blinded to the results of the screens. Sensitivity, specificity, and κ were calculated for both screening tools against the SGNA. A receiver operating characteristic (ROC) curve assessed alternate cutoffs for each tool. Length of hospital stay (LOS) was used to assess prospective validity.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Using the recommended cutoffs, the sensitivity of STRONGkids was 89%, specificity 35%, and κ 0.483. The sensitivity of PNST was 58%, specificity 88%, and κ 0.601. Using adjusted cutoffs, PNST's sensitivity improved to 87%, specificity 71%, and κ 0.681, and STRONGkids specificity improved to 61%, sensitivity 80%, and κ 0.5. Children identified at nutrition risk had significantly longer LOS (<jats:italic>P</jats:italic> &lt; 0.05).</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>This study showed neither tool was appropriate for clinical use based on published cutoffs. By adjusting the cutoffs using ROC curve analysis, both tools improved overall agreement with the SGNA without significantly impacting the prospective validity. PNST with adjusted cutoffs is the most appropriate for clinical use in this population.</jats:p></jats:sec>
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spelling Carter, Laura E. Shoyele, Grace Southon, Sarah Farmer, Anna Persad, Rabin Mazurak, Vera C. BrunetWood, M. Kim 0884-5336 1941-2452 Wiley Nutrition and Dietetics Medicine (miscellaneous) http://dx.doi.org/10.1002/ncp.10367 <jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Identifying children at malnutrition risk on admission to hospital is considered best practice; however, nutrition screening in pediatric populations is not common. The aim of this study was to determine which screening tool is able to identify children with malnutrition on admission to hospital.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>A nurse administered 2 pediatric nutrition screening tools, Screening Tool for Risk on Nutritional Status and Growth (STRONGkids) and Pediatric Nutrition Screening Tool (PNST) to patients admitted to medicine and surgery units (n = 165). The Subjective Global Nutritional Assessment (SGNA) was then completed by a dietitian, blinded to the results of the screens. Sensitivity, specificity, and κ were calculated for both screening tools against the SGNA. A receiver operating characteristic (ROC) curve assessed alternate cutoffs for each tool. Length of hospital stay (LOS) was used to assess prospective validity.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Using the recommended cutoffs, the sensitivity of STRONGkids was 89%, specificity 35%, and κ 0.483. The sensitivity of PNST was 58%, specificity 88%, and κ 0.601. Using adjusted cutoffs, PNST's sensitivity improved to 87%, specificity 71%, and κ 0.681, and STRONGkids specificity improved to 61%, sensitivity 80%, and κ 0.5. Children identified at nutrition risk had significantly longer LOS (<jats:italic>P</jats:italic> &lt; 0.05).</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>This study showed neither tool was appropriate for clinical use based on published cutoffs. By adjusting the cutoffs using ROC curve analysis, both tools improved overall agreement with the SGNA without significantly impacting the prospective validity. PNST with adjusted cutoffs is the most appropriate for clinical use in this population.</jats:p></jats:sec> Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best? Nutrition in Clinical Practice
spellingShingle Carter, Laura E., Shoyele, Grace, Southon, Sarah, Farmer, Anna, Persad, Rabin, Mazurak, Vera C., BrunetWood, M. Kim, Nutrition in Clinical Practice, Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best?, Nutrition and Dietetics, Medicine (miscellaneous)
title Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best?
title_full Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best?
title_fullStr Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best?
title_full_unstemmed Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best?
title_short Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best?
title_sort screening for pediatric malnutrition at hospital admission: which screening tool is best?
title_unstemmed Screening for Pediatric Malnutrition at Hospital Admission: Which Screening Tool Is Best?
topic Nutrition and Dietetics, Medicine (miscellaneous)
url http://dx.doi.org/10.1002/ncp.10367