1. External validation of a mobile clinical decision support system for diarrhea etiology prediction in children: A multicenter study in Bangladesh and Mali.
- Author
-
Garbern SC, Nelson EJ, Nasrin S, Keita AM, Brintz BJ, Gainey M, Badji H, Nasrin D, Howard J, Taniuchi M, Platts-Mills JA, Kotloff KL, Haque R, Levine AC, Sow SO, Alam NH, and Leung DT
- Subjects
- Anti-Bacterial Agents, Bangladesh epidemiology, Child, Diarrhea diagnosis, Diarrhea epidemiology, Humans, Mali, Decision Support Systems, Clinical
- Abstract
Background: Diarrheal illness is a leading cause of antibiotic use for children in low- and middle-income countries. Determination of diarrhea etiology at the point-of-care without reliance on laboratory testing has the potential to reduce inappropriate antibiotic use., Methods: This prospective observational study aimed to develop and externally validate the accuracy of a mobile software application ('App') for the prediction of viral-only etiology of acute diarrhea in children 0-59 months in Bangladesh and Mali. The App used a previously derived and internally validated model consisting of patient-specific ('present patient') clinical variables (age, blood in stool, vomiting, breastfeeding status, and mid-upper arm circumference) as well as location-specific viral diarrhea seasonality curves. The performance of additional models using the 'present patient' data combined with other external data sources including location-specific climate, data, recent patient data, and historical population-based prevalence were also evaluated in secondary analysis. Diarrhea etiology was determined with TaqMan Array Card using episode-specific attributable fraction (AFe) >0.5., Results: Of 302 children with acute diarrhea enrolled, 199 had etiologies above the AFe threshold. Viral-only pathogens were detected in 22% of patients in Mali and 63% in Bangladesh. Rotavirus was the most common pathogen detected (16% Mali; 60% Bangladesh). The present patient+ viral seasonality model had an AUC of 0.754 (0.665-0.843) for the sites combined, with calibration-in-the-large α = -0.393 (-0.455--0.331) and calibration slope β = 1.287 (1.207-1.367). By site, the present patient+ recent patient model performed best in Mali with an AUC of 0.783 (0.705-0.86); the present patient+ viral seasonality model performed best in Bangladesh with AUC 0.710 (0.595-0.825)., Conclusions: The App accurately identified children with high likelihood of viral-only diarrhea etiology. Further studies to evaluate the App's potential use in diagnostic and antimicrobial stewardship are underway., Funding: Funding for this study was provided through grants from the Bill and Melinda GatesFoundation (OPP1198876) and the National Institute of Allergy and Infectious Diseases (R01AI135114). Several investigators were also partially supported by a grant from the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK116163). This investigation was also supported by the University of Utah Population Health Research (PHR) Foundation, with funding in part from the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number UL1TR002538. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funders had no role in the study design, data collection, data analysis, interpretation of data, or in the writing or decision to submit the manuscript for publication., Competing Interests: SG received consultancy fees from the University of Utah, in relation to project "Development of clinical decision tools for management of diarrhea of children in high and low resource settings" (R01AI135114, PI: Leung), and from Department of Defense Naval Medical Logistics Command, for the Austere Environments Consortium for Enhanced Sepsis Outcomes: An Observational Study of Sepsis (N62645-14-2-0001). The author has no other competing interests to declare, EN is associated with a patent on data collection components in the 'Outbreak Responder' (Patent Publication Number 2020/0082921), of which the original 'Rehydration Calculator' was a component. These components are not included in the software referenced and published herein. Has no financial interest in the 'Rehydration Calculator' herein or the original 'Outbreak Responder' software, SN, AK, BB, MG, HB, JH, MT, JP, KK, RH, SS, NA, DL No competing interests declared, DN received travel funding for training and monitoring data collection in Mali. The author has no other competing interests to declare, AL received consultancy fees from the University of Utah, in relation to project "Development of clinical decision tools for management of diarrhea of children in high and low resource settings" (R01AI135114, PI: Leung). The author has no other competing interests to declare, (© 2022, Garbern et al.)
- Published
- 2022
- Full Text
- View/download PDF