Clinical predictors for etiology of acute diarrhea in children in resource-limited settings.

<h4>Background</h4>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 pote...

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Main Authors: Ben J Brintz (Author), Joel I Howard (Author), Benjamin Haaland (Author), James A Platts-Mills (Author), Tom Greene (Author), Adam C Levine (Author), Eric J Nelson (Author), Andrew T Pavia (Author), Karen L Kotloff (Author), Daniel T Leung (Author)
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Published: Public Library of Science (PLoS), 2020-10-01T00:00:00Z.
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042 |a dc 
100 1 0 |a Ben J Brintz  |e author 
700 1 0 |a Joel I Howard  |e author 
700 1 0 |a Benjamin Haaland  |e author 
700 1 0 |a James A Platts-Mills  |e author 
700 1 0 |a Tom Greene  |e author 
700 1 0 |a Adam C Levine  |e author 
700 1 0 |a Eric J Nelson  |e author 
700 1 0 |a Andrew T Pavia  |e author 
700 1 0 |a Karen L Kotloff  |e author 
700 1 0 |a Daniel T Leung  |e author 
245 0 0 |a Clinical predictors for etiology of acute diarrhea in children in resource-limited settings. 
260 |b Public Library of Science (PLoS),   |c 2020-10-01T00:00:00Z. 
500 |a 1935-2727 
500 |a 1935-2735 
500 |a 10.1371/journal.pntd.0008677 
520 |a <h4>Background</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusion</h4>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. 
546 |a EN 
690 |a Arctic medicine. Tropical medicine 
690 |a RC955-962 
690 |a Public aspects of medicine 
690 |a RA1-1270 
655 7 |a article  |2 local 
786 0 |n PLoS Neglected Tropical Diseases, Vol 14, Iss 10, p e0008677 (2020) 
787 0 |n https://doi.org/10.1371/journal.pntd.0008677 
787 0 |n https://doaj.org/toc/1935-2727 
787 0 |n https://doaj.org/toc/1935-2735 
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