Observational studyeLife2022
External validation of a mobile clinical decision support system for diarrhea etiology prediction in children: A multicenter study in Bangladesh and Mali.
Observational study in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Designing Clinical Decision Support Systems (CDSS)-A User-Centered Lens of the Design Characteristics, Challenges, and Implications: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Improving Antibiotic Stewardship for Diarrheal Disease With Probability-Based Electronic Clinical Decision Support: A Randomized Crossover Trial.JAMA pediatrics · 2022Trial
- Performance of fecal inflammatory biomarkers to identify watery shigellosis: Findings from the Enterics for Global Health (EFGH) Shigella surveillance study.PLoS neglected tropical diseases · 2026Article
- Development and External Validation of a Prognostic Prediction Model for Hospitalization in SARS-CoV-2-Infected Ambulatory Patients.Open forum infectious diseases · 2026Article
- Application of Artificial Intelligence in analysing meteorological data for health research: A rapid review.Air quality, atmosphere, & health · 2026Review
- Derivation and Internal Validation of a Clinical Prediction Model for Diagnosis of Spotted Fever Group Rickettsioses in Northern Tanzania.Open forum infectious diseases · 2025Article
- Assessment and comparison of model estimated and directly observed weather data for prediction of diarrhoea aetiology.Epidemiology and infection · 2024Article
- Identification, mapping, and self-reported practice patterns of village doctors in Sitakunda subdistrict, Bangladesh.Journal of global health · 2024Article
- Integration of population-level data sources into an individual-level clinical prediction model for dengue virus test positivity.Science advances · 2024Article
- Qualitative Assessment of a Smartphone-Based Mobile Health Tool to Guide Diarrhea Management in Bangladesh.The American journal of tropical medicine and hygiene · 2024Article
- Predictive modeling for infectious diarrheal disease in pediatric populations: A systematic review.Learning health systems · 2024Article
- Expanding access to veterinary clinical decision support in resource-limited settings: a scoping review of clinical decision support tools in medicine and antimicrobial stewardship.Frontiers in veterinary science · 2024Article
- Assessment of Model Estimated and Directly Observed Weather Data for Etiological Prediction of Diarrhea.medRxiv : the preprint server for health sciences · 2023Article
- Effects of prebiotics on the gut microbiotaFrontiers in microbiology · 2023Article
- Designing a Novel Clinician Decision Support Tool for the Management of Acute Diarrhea in Bangladesh: Formative Qualitative Study.JMIR human factors · 2022Article
- Use of Framework Matrix and Thematic Coding Methods in Qualitative Analysis for mHealth: NIRUDAK Study Data.International journal of qualitative methodsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
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 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.
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