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ORIGINAL ARTICLE
Open Access

Empirically Derived Dehydration Scoring and Decision Tree Models for Children With Diarrhea: Assessment and Internal Validation in a Prospective Cohort Study in Dhaka, Bangladesh

Adam C Levine, Justin Glavis-Bloom, Payal Modi, Sabiha Nasrin, Soham Rege, Chieh Chu, Christopher H Schmid and Nur H Alam
Global Health: Science and Practice September 2015, 3(3):405-418; https://doi.org/10.9745/GHSP-D-15-00097
Adam C Levine
aThe Warren Alpert Medical School of Brown University, Providence, RI, USA
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  • For correspondence: adam_levine@brown.edu
Justin Glavis-Bloom
aThe Warren Alpert Medical School of Brown University, Providence, RI, USA
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Payal Modi
aThe Warren Alpert Medical School of Brown University, Providence, RI, USA
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Sabiha Nasrin
bInternational Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
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Soham Rege
aThe Warren Alpert Medical School of Brown University, Providence, RI, USA
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Chieh Chu
cBrown University School of Public Health, Department of Biostatistics, Providence, RI, USA
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Christopher H Schmid
cBrown University School of Public Health, Department of Biostatistics, Providence, RI, USA
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Nur H Alam
bInternational Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
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The DHAKA Dehydration Score and the DHAKA Dehydration Tree are the first empirically derived and internally validated diagnostic models for assessing dehydration in children with acute diarrhea for use by general practice nurses in a resource-limited setting. Frontline providers can use these new tools to better classify and manage dehydration in children.

Abstract

Introduction: Diarrhea remains one of the most common and most deadly conditions affecting children worldwide. Accurately assessing dehydration status is critical to determining treatment course, yet no clinical diagnostic models for dehydration have been empirically derived and validated for use in resource-limited settings.

Methods: In the Dehydration: Assessing Kids Accurately (DHAKA) prospective cohort study, a random sample of children under 5 with acute diarrhea was enrolled between February and June 2014 in Bangladesh. Local nurses assessed children for clinical signs of dehydration on arrival, and then serial weights were obtained as subjects were rehydrated. For each child, the percent weight change with rehydration was used to classify subjects with severe dehydration (>9% weight change), some dehydration (3–9%), or no dehydration (<3%). Clinical variables were then entered into logistic regression and recursive partitioning models to develop the DHAKA Dehydration Score and DHAKA Dehydration Tree, respectively. Models were assessed for their accuracy using the area under their receiver operating characteristic curve (AUC) and for their reliability through repeat clinical exams. Bootstrapping was used to internally validate the models.

Results: A total of 850 children were enrolled, with 771 included in the final analysis. Of the 771 children included in the analysis, 11% were classified with severe dehydration, 45% with some dehydration, and 44% with no dehydration. Both the DHAKA Dehydration Score and DHAKA Dehydration Tree had significant AUCs of 0.79 (95% CI = 0.74, 0.84) and 0.76 (95% CI = 0.71, 0.80), respectively, for the diagnosis of severe dehydration. Additionally, the DHAKA Dehydration Score and DHAKA Dehydration Tree had significant positive likelihood ratios of 2.0 (95% CI = 1.8, 2.3) and 2.5 (95% CI = 2.1, 2.8), respectively, and significant negative likelihood ratios of 0.23 (95% CI = 0.13, 0.40) and 0.28 (95% CI = 0.18, 0.44), respectively, for the diagnosis of severe dehydration. Both models demonstrated 90% agreement between independent raters and good reproducibility using bootstrapping.

Conclusion: This study is the first to empirically derive and internally validate accurate and reliable clinical diagnostic models for dehydration in a resource-limited setting. After external validation, frontline providers may use these new tools to better manage acute diarrhea in children.

  • Received: 2015 Mar 24.
  • Accepted: 2015 Jul 10.
  • Published: 2015 Sep 10.
  • © Levine et al.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly cited. To view a copy of the license, visit http://creativecommons.org/licenses/by/3.0/. When linking to this article, please use the following permanent link: http://dx.doi.org/10.9745/GHSP-D-15-00097.

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Global Health: Science and Practice: 3 (3)
Global Health: Science and Practice
Vol. 3, No. 3
September 10, 2015
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Empirically Derived Dehydration Scoring and Decision Tree Models for Children With Diarrhea: Assessment and Internal Validation in a Prospective Cohort Study in Dhaka, Bangladesh
Adam C Levine, Justin Glavis-Bloom, Payal Modi, Sabiha Nasrin, Soham Rege, Chieh Chu, Christopher H Schmid, Nur H Alam
Global Health: Science and Practice Sep 2015, 3 (3) 405-418; DOI: 10.9745/GHSP-D-15-00097

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Empirically Derived Dehydration Scoring and Decision Tree Models for Children With Diarrhea: Assessment and Internal Validation in a Prospective Cohort Study in Dhaka, Bangladesh
Adam C Levine, Justin Glavis-Bloom, Payal Modi, Sabiha Nasrin, Soham Rege, Chieh Chu, Christopher H Schmid, Nur H Alam
Global Health: Science and Practice Sep 2015, 3 (3) 405-418; DOI: 10.9745/GHSP-D-15-00097
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