Clinical predictors for etiology of acute diarrhea in children in resource-limited settings.
Background Diarrhea is one of the leading causes of childhood morbidity and mortality in lower- and middle-income countries. In such settings, access to laboratory diagnostics are often limited, and decisions for use of antimicrobials often empiric. Clinical predictors are a potential non-laboratory...
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ftdoajarticles:oai:doaj.org/article:4be98fa8640b4150891d1d6681e3c0e4 2023-05-15T15:11:36+02:00 Clinical predictors for etiology of acute diarrhea in children in resource-limited settings. Ben J Brintz Joel I Howard Benjamin Haaland James A Platts-Mills Tom Greene Adam C Levine Eric J Nelson Andrew T Pavia Karen L Kotloff Daniel T Leung 2020-10-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0008677 https://doaj.org/article/4be98fa8640b4150891d1d6681e3c0e4 EN eng Public Library of Science (PLoS) https://doi.org/10.1371/journal.pntd.0008677 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0008677 https://doaj.org/article/4be98fa8640b4150891d1d6681e3c0e4 PLoS Neglected Tropical Diseases, Vol 14, Iss 10, p e0008677 (2020) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2020 ftdoajarticles https://doi.org/10.1371/journal.pntd.0008677 2022-12-31T11:50:06Z Background Diarrhea is one of the leading causes of childhood morbidity and mortality in lower- and middle-income countries. In such settings, access to laboratory diagnostics are often limited, and decisions for use of antimicrobials often empiric. Clinical predictors are a potential non-laboratory method to more accurately assess diarrheal etiology, the knowledge of which could improve management of pediatric diarrhea. Methods We used clinical and quantitative molecular etiologic data from the Global Enteric Multicenter Study (GEMS), a prospective, case-control study, to develop predictive models for the etiology of diarrhea. Using random forests, we screened the available variables and then assessed the performance of predictions from random forest regression models and logistic regression models using 5-fold cross-validation. Results We identified 1049 cases where a virus was the only etiology, and developed predictive models against 2317 cases where the etiology was known but non-viral (bacterial, protozoal, or mixed). Variables predictive of a viral etiology included lower age, a dry and cold season, increased height-for-age z-score (HAZ), lack of bloody diarrhea, and presence of vomiting. Cross-validation suggests an AUC of 0.825 can be achieved with a parsimonious model of 5 variables, achieving a specificity of 0.85, a sensitivity of 0.59, a NPV of 0.82 and a PPV of 0.64. Conclusion Predictors of the etiology of pediatric diarrhea can be used by providers in low-resource settings to inform clinical decision-making. The use of non-laboratory methods to diagnose viral causes of diarrhea could be a step towards reducing inappropriate antibiotic prescription worldwide. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 14 10 e0008677 |
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Directory of Open Access Journals: DOAJ Articles |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Ben J Brintz Joel I Howard Benjamin Haaland James A Platts-Mills Tom Greene Adam C Levine Eric J Nelson Andrew T Pavia Karen L Kotloff Daniel T Leung Clinical predictors for etiology of acute diarrhea in children in resource-limited settings. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
Background Diarrhea is one of the leading causes of childhood morbidity and mortality in lower- and middle-income countries. In such settings, access to laboratory diagnostics are often limited, and decisions for use of antimicrobials often empiric. Clinical predictors are a potential non-laboratory method to more accurately assess diarrheal etiology, the knowledge of which could improve management of pediatric diarrhea. Methods We used clinical and quantitative molecular etiologic data from the Global Enteric Multicenter Study (GEMS), a prospective, case-control study, to develop predictive models for the etiology of diarrhea. Using random forests, we screened the available variables and then assessed the performance of predictions from random forest regression models and logistic regression models using 5-fold cross-validation. Results We identified 1049 cases where a virus was the only etiology, and developed predictive models against 2317 cases where the etiology was known but non-viral (bacterial, protozoal, or mixed). Variables predictive of a viral etiology included lower age, a dry and cold season, increased height-for-age z-score (HAZ), lack of bloody diarrhea, and presence of vomiting. Cross-validation suggests an AUC of 0.825 can be achieved with a parsimonious model of 5 variables, achieving a specificity of 0.85, a sensitivity of 0.59, a NPV of 0.82 and a PPV of 0.64. Conclusion Predictors of the etiology of pediatric diarrhea can be used by providers in low-resource settings to inform clinical decision-making. The use of non-laboratory methods to diagnose viral causes of diarrhea could be a step towards reducing inappropriate antibiotic prescription worldwide. |
format |
Article in Journal/Newspaper |
author |
Ben J Brintz Joel I Howard Benjamin Haaland James A Platts-Mills Tom Greene Adam C Levine Eric J Nelson Andrew T Pavia Karen L Kotloff Daniel T Leung |
author_facet |
Ben J Brintz Joel I Howard Benjamin Haaland James A Platts-Mills Tom Greene Adam C Levine Eric J Nelson Andrew T Pavia Karen L Kotloff Daniel T Leung |
author_sort |
Ben J Brintz |
title |
Clinical predictors for etiology of acute diarrhea in children in resource-limited settings. |
title_short |
Clinical predictors for etiology of acute diarrhea in children in resource-limited settings. |
title_full |
Clinical predictors for etiology of acute diarrhea in children in resource-limited settings. |
title_fullStr |
Clinical predictors for etiology of acute diarrhea in children in resource-limited settings. |
title_full_unstemmed |
Clinical predictors for etiology of acute diarrhea in children in resource-limited settings. |
title_sort |
clinical predictors for etiology of acute diarrhea in children in resource-limited settings. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2020 |
url |
https://doi.org/10.1371/journal.pntd.0008677 https://doaj.org/article/4be98fa8640b4150891d1d6681e3c0e4 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 14, Iss 10, p e0008677 (2020) |
op_relation |
https://doi.org/10.1371/journal.pntd.0008677 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0008677 https://doaj.org/article/4be98fa8640b4150891d1d6681e3c0e4 |
op_doi |
https://doi.org/10.1371/journal.pntd.0008677 |
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PLOS Neglected Tropical Diseases |
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14 |
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10 |
container_start_page |
e0008677 |
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