External Validation of a Mobile Clinical Decision Support System
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medRxiv preprint doi: https://doi.org/10.1101/2021.07.31.21261145; this version posted August 1, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 1 Title: 2 External Validation of a Mobile Clinical Decision Support System for Diarrhea Etiology 3 Prediction in Children: A Multicenter Study in Bangladesh and Mali 4 5 Authors: 6 Stephanie C Garbern, MD, MPH*1; Eric J Nelson, MD, PhD*2; Sabiha Nasrin, MBBS, MPH3; 7 Adama Mamby Keita, MD, MSc4; Ben J Brintz, PhD5; Monique Gainey, MS, MPH6; Henry Badji, 8 MSc4; Dilruba Nasrin, MBBS, PhD7; Joel Howard, MD8; Mami Taniuchi, PhD9; James A. Platts- 9 Mills, MD9 ; Karen L Kotloff, MD10; Rashidul Haque, MBBS, PhD3; Adam C Levine, MD, MPH1; 10 Samba O Sow, MD, MSc, FASTMH4; Nur H Alam, MBBS, MD3; Daniel T Leung, MD, MSc, 11 FASTMH11. 12 13 * co-first authors 14 15 Affiliations: 16 1 Department of Emergency Medicine, Alpert Medical School, Brown University, Providence, RI, 17 USA 18 2 Departments of Pediatrics and Environmental and Global Health, Emerging Pathogens 19 Institute, University of Florida, Gainesville, FL, USA. 20 3 International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, 21 Bangladesh 22 4 Center for Vaccine Development - Mali, Bamako, Mali 23 5 Division of Epidemiology, University of Utah, Salt Lake City, UT, USA 24 6 Rhode Island Hospital, Providence, RI, USA 25 7 Center for Vaccine Development and Global Health, University of Maryland School of 26 Medicine, Baltimore, MD, USA 27 8 Department, University of Kentucky, Lexington, KY, USA 28 9 Division of Infectious Diseases and International Health, University of Virginia, USA 29 10 *Department, University of Maryland, Baltimore, MD, USA 30 11 Division of Infectious Diseases, University of Utah School of Medicine, Salt Lake City, Utah, 31 USA 32 33 Correspondence: 34 Stephanie C. Garbern, MD, MPH 35 Department of Emergency Medicine 36 Alpert Medical School of Brown University 37 55 Claverick Street, 2nd Floor 38 Providence, RI 02903 USA 39 40 Daniel T. Leung, MD, MSc, FASTMH 41 Division of Infectious Diseases 42 University of Utah School of Medicine 43 30 N 1900 E, ROOM 4B319 44 Salt Lake City, Utah 84132, USA NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. 1 medRxiv preprint doi: https://doi.org/10.1101/2021.07.31.21261145; this version posted August 1, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 45 46 Key words: diarrhea, diarrhoea, antibiotic stewardship, antimicrobial resistance, AMR, 47 enteropathogens, enteric infections, Bangladesh, Mali, mobile health, smartphone, clinical 48 prediction model, clinical decision support 49 50 Declarations: 51 52 Funding: Funding for this study was provided through grants from the Bill and Melinda Gates 53 Foundation (OPP1198876) and the National Institute of Allergy and Infectious Diseases 54 (R01AI135114). Several investigators were also partially supported by a grant from the National 55 Institute of Diabetes and Digestive and Kidney Diseases (R01DK116163). This investigation 56 was also supported by the University of Utah Population Health Research (PHR) Foundation, 57 with funding in part from the National Center for Advancing Translational Sciences of the 58 National Institutes of Health under Award Number UL1TR002538. The content is solely the 59 responsibility of the authors and does not necessarily represent the official views of the National 60 Institutes of Health. The funders had no role in the study design, data collection, data analysis, 61 interpretation of data, or in the writing or decision to submit the manuscript for publication. 62 63 Conflict of Interest: The authors declare that they have no competing interests. The content of 64 this manuscript is solely the responsibility of the authors and does not necessarily represent the 65 views of NIH or any governmental bodies or academic organizations. 66 67 Ethical Approval and Consent to Participate: Ethical approval was obtained from the icddr,b 68 Ethical Review Committee and Rhode Island Hospital Institutional Review Board. 69 70 Consent for Publication: Not applicable. 71 72 Availability of Data and Material: The de-identified dataset is available in Supplemental File 8. 73 74 Acknowledgements: The authors thank all study participants and the study staff of the icddr,b 75 Dhaka Hospital and the health centers of Commune V and VI in Mali for their help and support. 76 The authors also thank the development team at BeeHyv Software Solutions Pvt. Ltd. 77 (Wilmington, DE; Hyderabad, India) who were instrumental in building the digital clinical 78 decision support software used in this study. 79 2 medRxiv preprint doi: https://doi.org/10.1101/2021.07.31.21261145; this version posted August 1, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 80 Abstract 81 82 Background: Diarrheal illness is a leading cause of antibiotic use for children in low- and 83 middle-income countries. Determination of diarrhea etiology at the point-of-care without reliance 84 on laboratory testing has the potential to reduce inappropriate antibiotic use. 85 86 Methods: This prospective observational study aimed to develop and externally validate the 87 accuracy of a mobile software application (“App”) for the prediction of viral-only etiology of acute 88 diarrhea in children 0-59 months in Bangladesh and Mali. The App used previously derived and 89 internally validated models using combinations of “patient-intrinsic” information (age, blood in 90 stool, vomiting, breastfeeding status, and mid-upper arm circumference), pre-test odds using 91 location-specific historical prevalence and recent patients, climate, and viral seasonality. 92 Diarrhea etiology was determined with TaqMan Array Card using episode-specific attributable 93 fraction (AFe) >0.5. 94 95 Results: Of 302 children with acute diarrhea enrolled, 199 had etiologies above the AFe 96 threshold. Viral-only pathogens were detected in 22% of patients in Mali and 63% in 97 Bangladesh. Rotavirus was the most common pathogen detected (16% Mali; 60% Bangladesh). 98 The viral seasonality model had an AUC of 0.754 (0.665-0.843) for the sites combined, with 99 calibration-in-the-large α=-0.393 (-0.455 – -0.331) and calibration slope β=1.287 (1.207 – 100 1.367). By site, the pre-test odds model performed best in Mali with an AUC of 0.783 (0.705 - 101 0.86); the viral seasonality model performed best in Bangladesh with AUC 0.710 (0.595 - 102 0.825). 103 104 Conclusion: The App accurately identified children with high likelihood of viral-only diarrhea 105 etiology. Further studies to evaluate the App’s potential use in diagnostic and antimicrobial 106 stewardship are underway. 107 108 109 3 medRxiv preprint doi: https://doi.org/10.1101/2021.07.31.21261145; this version posted August 1, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 110 Introduction 111 112 Diarrheal diseases remain a leading cause of morbidity and mortality in children younger than 113 five years worldwide, with approximately one billion episodes and 500,000 deaths annually.1,2 114 While a significant problem in all countries, the greatest burden of pediatric diarrhea exists in 115 low- and middle-income countries (LMICs), primarily in South Asia and sub-Saharan Africa.2 116 Although the majority of diarrhea episodes are self-limiting and the mainstay of diarrhea 117 treatment is rehydration, clinicians must also make decisions regarding appropriate use of 118 diagnostics and for antibiotic prescribing. Guidelines from the World Health Organization (WHO) 119 recommend against antibiotic use for the treatment of pediatric diarrhea, except for specific 120 presentations of diarrhea such as suspicion of Vibrio cholerae (V. cholerae) with severe 121 dehydration, blood in stool, or concurrent illness such as severe malnutrition.3 For the majority 122 of diarrhea etiologies, antibiotics are not recommended, particularly for viral causes of diarrhea 123 in which antibiotics have no benefit.4 Viral pathogens such as rotavirus, sapovirus, and 124 adenovirus, are among the top causes of diarrhea in young children in LMICs, as shown in two 125 large multi-center studies from LMICs, the Global Enteric Multicenter Study (GEMS) and the 126 Malnutrition and Enteric Disease (MAL-ED) study.5,6 127 128 Laboratory testing by culture or molecular assays are often impractical when treating children 129 with diarrhea in the majority of LMIC clinical settings due to time and resource constraints.7 As a 130 result, clinicians often make decisions regarding antibiotic use based on non-evidence based 131 assumptions or broad syndromic guidelines.8 Unfortunately, physician judgment has been 132 shown to poorly predict etiology and need for antibiotics in diarrheal infections. For example, 133 patients presenting to Kenyan hospitals with diarrhea showed that syndrome-based guidelines 134 for Shigella infection led to the failure to diagnose shigellosis in nearly 90% of cases.9 Accurate 135 and cost-effective tools to better determine diarrhea etiology at the point-of-care without relying 136 on laboratory tests are greatly needed to reduce antibiotic overuse while conserving scarce 137 healthcare resources.