External validation of a mobile clinical decision support system for diarrhea etiology prediction in children: a multicenter study in Bangladesh and Mali
- Brown University, United States
- University of Florida, United States
- International Centre for Diarrhoeal Disease Research, Bangladesh
- Centre for Vaccine Development, Mali
- University of Utah, United States
- Rhode Island Hospital, United States
- Center for Vaccine Development, Mali
- University of Maryland School of Medicine, United States
- University of Kentucky, United States
- University of Virginia, United States
- University of Maryland, United States
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).
Conclusion: 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 Gates Foundation (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.
Data availability
The de-identified dataset is included as Supplementary File 5 and has been deposited on Dryad. The modeling code and additional files needed to run the code are deposited on GitHub at https://github.com/LeungLab/DiaPR_Phase1
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Data from: Diarrhea Etiology Prediction Validation Dataset - Bangladesh and MaliDryad Digital Repository doi:10.5061/dryad.0rxwdbs19.
Article and author information
Author details
Stephanie Chow Garbern
Funding
Bill and Melinda Gates Foundation (OPP1198876)
- Daniel T Leung
National Institute of Allergy and Infectious Diseases (R01AI135114)
- Daniel T Leung
National Institute of Diabetes and Digestive and Kidney Diseases (R01DK116163)
- Monique Gainey
National Center for Advancing Translational Sciences (UL1TR002538)
- Ben J Brintz
National Institutes of Health (R21TW010182)
- Eric J Nelson
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Joshua T Schiffer, Fred Hutchinson Cancer Research Center, United States
Ethics
Human subjects: Informed consent was obtained from all study participants as described in Materials and Methods. Ethical approval was obtained from the icddr,b Ethical Review Committee (PR-19095), the University of Sciences, Techniques, and Technologies of Bamako Ethics Committee (2019-153), and the University of Utah Institutional Review Board (IRB_00121790).
Version history
- Received: July 18, 2021
- Preprint posted: August 1, 2021 (view preprint)
- Accepted: February 5, 2022
- Accepted Manuscript published: February 9, 2022 (version 1)
- Version of Record published: March 8, 2022 (version 2)
Copyright
© 2022, Garbern et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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External validation of a mobile clinical decision support system for diarrhea etiology prediction in children: a multicenter study in Bangladesh and Mali
eLife 11:e72294.
https://doi.org/10.7554/eLife.72294
Further reading
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- Epidemiology and Global Health
Background:
Circulating omega-3 and omega-6 polyunsaturated fatty acids (PUFAs) have been associated with various chronic diseases and mortality, but results are conflicting. Few studies examined the role of omega-6/omega-3 ratio in mortality.
Methods:
We investigated plasma omega-3 and omega-6 PUFAs and their ratio in relation to all-cause and cause-specific mortality in a large prospective cohort, the UK Biobank. Of 85,425 participants who had complete information on circulating PUFAs, 6461 died during follow-up, including 2794 from cancer and 1668 from cardiovascular disease (CVD). Associations were estimated by multivariable Cox proportional hazards regression with adjustment for relevant risk factors.
Results:
Risk for all three mortality outcomes increased as the ratio of omega-6/omega-3 PUFAs increased (all Ptrend <0.05). Comparing the highest to the lowest quintiles, individuals had 26% (95% CI, 15–38%) higher total mortality, 14% (95% CI, 0–31%) higher cancer mortality, and 31% (95% CI, 10–55%) higher CVD mortality. Moreover, omega-3 and omega-6 PUFAs in plasma were all inversely associated with all-cause, cancer, and CVD mortality, with omega-3 showing stronger effects.
Conclusions:
Using a population-based cohort in UK Biobank, our study revealed a strong association between the ratio of circulating omega-6/omega-3 PUFAs and the risk of all-cause, cancer, and CVD mortality.
Funding:
Research reported in this publication was supported by the National Institute of General Medical Sciences of the National Institute of Health under the award number R35GM143060 (KY). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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- Ecology
- Epidemiology and Global Health
Non-pharmaceutical interventions implemented to block SARS-CoV-2 transmission in early 2020 led to global reductions in the incidence of invasive pneumococcal disease (IPD). By contrast, most European countries reported an increase in antibiotic resistance among invasive Streptococcus pneumoniae isolates from 2019 to 2020, while an increasing number of studies reported stable pneumococcal carriage prevalence over the same period. To disentangle the impacts of the COVID-19 pandemic on pneumococcal epidemiology in the community setting, we propose a mathematical model formalizing simultaneous transmission of SARS-CoV-2 and antibiotic-sensitive and -resistant strains of S. pneumoniae. To test hypotheses underlying these trends five mechanisms were built into the model and examined: (1) a population-wide reduction of antibiotic prescriptions in the community, (2) lockdown effect on pneumococcal transmission, (3) a reduced risk of developing an IPD due to the absence of common respiratory viruses, (4) community azithromycin use in COVID-19 infected individuals, (5) and a longer carriage duration of antibiotic-resistant pneumococcal strains. Among 31 possible pandemic scenarios involving mechanisms individually or in combination, model simulations surprisingly identified only two scenarios that reproduced the reported trends in the general population. They included factors (1), (3), and (4). These scenarios replicated a nearly 50% reduction in annual IPD, and an increase in antibiotic resistance from 20% to 22%, all while maintaining a relatively stable pneumococcal carriage. Exploring further, higher SARS-CoV-2 R0 values and synergistic within-host virus-bacteria interaction mechanisms could have additionally contributed to the observed antibiotic resistance increase. Our work demonstrates the utility of the mathematical modeling approach in unraveling the complex effects of the COVID-19 pandemic responses on AMR dynamics.
