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Testing the Accuracy of a Bedside Screening Tool Framework to Clinical Records for Identification of Patients at Risk of Malnutrition in a Rural Setting: An Exploratory Study

This study aimed to explore the diagnostic accuracy of the Patient-Generated Subjective Global Assessment (PG-SGA) malnutrition risk screening tool when used to score patients based on their electronic medical records (EMR), compared to bedside screening interviews. In-patients at a rural health ser...

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Autores principales: Alston, Laura, Green, Megan, Nichols, Melanie, Partridge, Stephanie R., Buccheri, Alison, Bolton, Kristy A., Versace, Vincent L., Field, Michael, Launder, Ambrose J., Lily, Amy, Allender, Steven, Orellana, Liliana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8746937/
https://www.ncbi.nlm.nih.gov/pubmed/35011080
http://dx.doi.org/10.3390/nu14010205
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author Alston, Laura
Green, Megan
Nichols, Melanie
Partridge, Stephanie R.
Buccheri, Alison
Bolton, Kristy A.
Versace, Vincent L.
Field, Michael
Launder, Ambrose J.
Lily, Amy
Allender, Steven
Orellana, Liliana
author_facet Alston, Laura
Green, Megan
Nichols, Melanie
Partridge, Stephanie R.
Buccheri, Alison
Bolton, Kristy A.
Versace, Vincent L.
Field, Michael
Launder, Ambrose J.
Lily, Amy
Allender, Steven
Orellana, Liliana
author_sort Alston, Laura
collection PubMed
description This study aimed to explore the diagnostic accuracy of the Patient-Generated Subjective Global Assessment (PG-SGA) malnutrition risk screening tool when used to score patients based on their electronic medical records (EMR), compared to bedside screening interviews. In-patients at a rural health service were screened at the bedside (n = 50) using the PG-SGA, generating a bedside score. Clinical notes within EMRs were then independently screened by blinded researchers. The accuracy of the EMR score was assessed against the bedside score using area under the receiver operating curve (AUC), sensitivity, and specificity. Participants were 62% female and 32% had conditions associated with malnutrition, with a mean age of 70.6 years (SD 14.9). The EMR score had moderate diagnostic accuracy relative to PG-SGA bedside screen, AUC 0.74 (95% CI: 0.59–0.89). The accuracy, specificity and sensitivity of the EMR score was highest for patients with a score of 7, indicating EMR screen is more likely to detect patients at risk of malnutrition. This exploratory study showed that applying the PG-SGA screening tool to EMRs had enough sensitivity and specificity for identifying patients at risk of malnutrition to warrant further exploration in low-resource settings.
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spelling pubmed-87469372022-01-11 Testing the Accuracy of a Bedside Screening Tool Framework to Clinical Records for Identification of Patients at Risk of Malnutrition in a Rural Setting: An Exploratory Study Alston, Laura Green, Megan Nichols, Melanie Partridge, Stephanie R. Buccheri, Alison Bolton, Kristy A. Versace, Vincent L. Field, Michael Launder, Ambrose J. Lily, Amy Allender, Steven Orellana, Liliana Nutrients Article This study aimed to explore the diagnostic accuracy of the Patient-Generated Subjective Global Assessment (PG-SGA) malnutrition risk screening tool when used to score patients based on their electronic medical records (EMR), compared to bedside screening interviews. In-patients at a rural health service were screened at the bedside (n = 50) using the PG-SGA, generating a bedside score. Clinical notes within EMRs were then independently screened by blinded researchers. The accuracy of the EMR score was assessed against the bedside score using area under the receiver operating curve (AUC), sensitivity, and specificity. Participants were 62% female and 32% had conditions associated with malnutrition, with a mean age of 70.6 years (SD 14.9). The EMR score had moderate diagnostic accuracy relative to PG-SGA bedside screen, AUC 0.74 (95% CI: 0.59–0.89). The accuracy, specificity and sensitivity of the EMR score was highest for patients with a score of 7, indicating EMR screen is more likely to detect patients at risk of malnutrition. This exploratory study showed that applying the PG-SGA screening tool to EMRs had enough sensitivity and specificity for identifying patients at risk of malnutrition to warrant further exploration in low-resource settings. MDPI 2022-01-02 /pmc/articles/PMC8746937/ /pubmed/35011080 http://dx.doi.org/10.3390/nu14010205 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Alston, Laura
Green, Megan
Nichols, Melanie
Partridge, Stephanie R.
Buccheri, Alison
Bolton, Kristy A.
Versace, Vincent L.
Field, Michael
Launder, Ambrose J.
Lily, Amy
Allender, Steven
Orellana, Liliana
Testing the Accuracy of a Bedside Screening Tool Framework to Clinical Records for Identification of Patients at Risk of Malnutrition in a Rural Setting: An Exploratory Study
title Testing the Accuracy of a Bedside Screening Tool Framework to Clinical Records for Identification of Patients at Risk of Malnutrition in a Rural Setting: An Exploratory Study
title_full Testing the Accuracy of a Bedside Screening Tool Framework to Clinical Records for Identification of Patients at Risk of Malnutrition in a Rural Setting: An Exploratory Study
title_fullStr Testing the Accuracy of a Bedside Screening Tool Framework to Clinical Records for Identification of Patients at Risk of Malnutrition in a Rural Setting: An Exploratory Study
title_full_unstemmed Testing the Accuracy of a Bedside Screening Tool Framework to Clinical Records for Identification of Patients at Risk of Malnutrition in a Rural Setting: An Exploratory Study
title_short Testing the Accuracy of a Bedside Screening Tool Framework to Clinical Records for Identification of Patients at Risk of Malnutrition in a Rural Setting: An Exploratory Study
title_sort testing the accuracy of a bedside screening tool framework to clinical records for identification of patients at risk of malnutrition in a rural setting: an exploratory study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8746937/
https://www.ncbi.nlm.nih.gov/pubmed/35011080
http://dx.doi.org/10.3390/nu14010205
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