Etiologies of Bloody Diarrhea in Children Presenting With Acute Gastroenteritis to US Emergency Departments.

We used molecular testing to examine the causes of bloody diarrhea in a multicenter study of pediatric gastroenteritis. Pathogens typically associated with bloody diarrhea were detected in less than half of cases, and inappropriate antibiotic use was common, supporting the use of stool testing in patients with bloody diarrhea.

Model-based estimates of age-structured SARS-CoV-2 epidemiology in households.

Background: Understanding how infectious disease transmission varies from person to person, including associations with age and contact behavior, can help design effective control strategies. Within households, transmission may be highly variable because of differing transmission risks by age, household size, and individual contagiousness. Our aim was to disentangle those factors by fitting mathematical models to SARS-CoV-2 household survey and serologic data.

Potential for an Electronic Clinical Decision Support Tool to Support Appropriate Antibiotic Use for Pediatric Diarrhea Among Village Doctors in Bangladesh.

Village doctors in Bangladesh expressed broad interest in clinical decision support tools for pediatric diarrheal disease management and described their willingness to alter their antibiotic dispensing practices if guided by one. Future research should evaluate the tool’s impact on appropriate antibiotic use and patient outcomes.

Assessment and comparison of model estimated and directly observed weather data for prediction of diarrhoea aetiology.

Recent advances in clinical prediction for diarrhoeal aetiology in low- and middle-income countries have revealed that the addition of weather data to clinical data improves predictive performance. However, the optimal source of weather data remains unclear. We aim to compare the use of model estimated satellite- and ground-based observational data with weather station directly observed data for the prediction of aetiology of diarrhoea.

Identification, mapping, and self-reported practice patterns of village doctors in Sitakunda subdistrict, Bangladesh.

Background: Informally trained health care providers, such as village doctors in Bangladesh, are crucial in providing health care services to the rural poor in low- and middle-income countries. Despite being one of the primary vendors of antibiotics in rural Bangladesh, village doctors often have limited knowledge about appropriate antibiotic use, leading to varied and potentially inappropriate dispensing and treatment practices. In this study, we aimed to identify, map, and survey village doctors in the Sitakunda subdistrict of Bangladesh to understand their distribution, practice characteristics, clinical behaviours, access to technologies, and use of these technologies for clinical decision-making.

Etiologies of bloody diarrhea in children presenting with acute gastroenteritis to US emergency departments.

Among 111 children presenting with bloody diarrhea in a multicenter study of molecular testing in US emergency departments, we found viral pathogens in 18%, bacteria in 48%, protozoa in 2%, and no pathogens detected in 38%.

Drivers of inappropriate use of antimicrobials in South Asia: A systematic review of qualitative literature.

Antimicrobial resistance is a global public health crisis. Effective antimicrobial stewardship requires an understanding of the factors and context that contribute to inappropriate use of antimicrobials. The goal of this qualitative systematic review was to synthesize themes across levels of the social ecological framework that drive inappropriate use of antimicrobials in South Asia.

Assessment of Model Estimated and Directly Observed Weather Data for Etiological Prediction of Diarrhea.

Recent advances in clinical prediction for diarrheal etiology in low- and middle-income countries have revealed that addition of weather data improves predictive performance. However, the optimal source of weather data remains unclear. We aim to compare model estimated satellite- and ground-based observational data with weather station directly-observed data for diarrheal prediction.

Drivers of inappropriate use of antimicrobials in South Asia: A systematic review of qualitative literature.

Antimicrobial resistance is a global public health crisis. Effective antimicrobial stewardship requires an understanding of the factors and context that contribute to inappropriate use of antimicrobials. The goal of this qualitative systematic review was to synthesize themes across levels of the social ecological framework that drive inappropriate use of antimicrobials in South Asia.

Derivation and External Validation of a Clinical Prediction Model for Viral Diarrhea Etiology in Bangladesh.

Background: Antibiotics are commonly overused for diarrheal illness in many low- and middle-income countries, partly due to a lack of diagnostics to identify viral cases, in which antibiotics are not beneficial. This study aimed to develop clinical prediction models to predict risk of viral-only diarrhea across all ages, using routinely collected demographic and clinical variables.

Methods: We used a derivation dataset from 10 hospitals across Bangladesh and a separate validation dataset from the icddr,b Dhaka Hospital.

Clinical Prediction Rule to Guide Diagnostic Testing for and Improve Antibiotic Stewardship for Pediatric Diarrhea.

Background: Diarrheal diseases are a leading cause of death for children aged <5 years. Identification of etiology helps guide pathogen-specific therapy, but availability of diagnostic testing is often limited in low-resource settings. Our goal is to develop a clinical prediction rule (CPR) to guide clinicians in identifying when to use a point-of-care (POC) diagnostic for in children presenting with acute diarrhea.

Derivation and external validation of a clinical prognostic model identifying children at risk of death following presentation for diarrheal care.

Diarrhea continues to be a leading cause of death for children under-five. Amongst children treated for acute diarrhea, mortality risk remains elevated during and after acute medical management. Identification of those at highest risk would enable better targeting of interventions, but available prognostic tools lack validation.

Derivation and external validation of clinical prediction rules identifying children at risk of linear growth faltering.

Background: Nearly 150 million children under-5 years of age were stunted in 2020. We aimed to develop a clinical prediction rule (CPR) to identify children likely to experience additional stunting following acute diarrhea, to enable targeted approaches to prevent this irreversible outcome.

Methods: We used clinical and demographic data from the Global Enteric Multicenter Study (GEMS) to build predictive models of linear growth faltering (decrease of ≥0.

Improving Antibiotic Stewardship for Diarrheal Disease With Probability-Based Electronic Clinical Decision Support: A Randomized Crossover Trial.

Importance: Inappropriate use of antibiotics for diarrheal illness can result in adverse effects and increase in antimicrobial resistance.

Objective: To determine whether the diarrheal etiology prediction (DEP) algorithm, which uses patient-specific and location-specific features to estimate the probability that diarrhea etiology is exclusively viral, impacts antibiotic prescriptions in patients with acute diarrhea.

Design, Setting, And Participants: A randomized crossover study was conducted to evaluate the DEP incorporated into a smartphone-based electronic clinical decision-support (eCDS) tool.

Incidence Rate and Risk Factors Associated with Travelers' Diarrhea in International Travelers Departing from Utah, USA.

Despite knowledge on the causes and prevention strategies for travelers' diarrhea (TD), it continues to be one of the most common illnesses experienced by U.S. international travelers.

The Effects of Using a Clinical Prediction Rule to Prioritize Diagnostic Testing on Transmission and Hospital Burden: A Modeling Example of Early Severe Acute Respiratory Syndrome Coronavirus 2.

Background: Prompt identification of infections is critical for slowing the spread of infectious diseases. However, diagnostic testing shortages are common in emerging diseases, low resource settings, and during outbreaks. This forces difficult decisions regarding who receives a test, often without knowing the implications of those decisions on population-level transmission dynamics.

Robust Testing in Outpatient Settings to Explore COVID-19 Epidemiology: Disparities in Race/Ethnicity and Age, Salt Lake County, Utah, 2020.

Objective: US-based descriptions of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have focused on patients with severe disease. Our objective was to describe characteristics of a predominantly outpatient population tested for SARS-CoV-2 in an area receiving comprehensive testing.

Methods: We extracted data on demographic characteristics and clinical data for all patients (91% outpatient) tested for SARS-CoV-2 at University of Utah Health clinics in Salt Lake County, Utah, from March 10 through April 24, 2020.

Urinary polycyclic aromatic hydrocarbons concentrations and hepatitis B antibody serology in the United States (NHANES, 2003-2014).

Background: Polycyclic aromatic hydrocarbons (PAHs) are environmental contaminants that are hepatotoxic and immunotoxic. PAH exposure may modulate hepatitis B immunology.

Objective: We used data from 6 cycles of the National Health and Nutrition Examination Survey (2003-2014) to evaluate the associations between urinary PAH metabolites and hepatitis B serology.

A modular approach to integrating multiple data sources into real-time clinical prediction for pediatric diarrhea.

Traditional clinical prediction models focus on parameters of the individual patient. For infectious diseases, sources external to the patient, including characteristics of prior patients and seasonal factors, may improve predictive performance. We describe the development of a predictive model that integrates multiple sources of data in a principled statistical framework using a post-test odds formulation.

Modeling reductions in SARS-CoV-2 transmission and hospital burden achieved by prioritizing testing using a clinical prediction rule.

Prompt identification of cases is critical for slowing the spread of COVID-19. However, many areas have faced diagnostic testing shortages, requiring difficult decisions to be made regarding who receives a test, without knowing the implications of those decisions on population-level transmission dynamics. Clinical prediction rules (CPRs) are commonly used tools to guide clinical decisions.

A prospective cohort study of in utero and early childhood arsenic exposure and infectious disease in 4- to 5-year-old Bangladeshi children.

Background: Previous research found that infants who were exposed to high levels of arsenic in utero had an increased risk of infectious disease in the first year of life. This prospective study examined the association between arsenic exposures during gestation, and respiratory, diarrheal, and febrile morbidity in children 4-5 years of age.

Methods: A cohort of pregnant women was recruited in 2008-2011 in Bangladesh.

Evaluating the effects between metal mixtures and serum vaccine antibody concentrations in children: a prospective birth cohort study.

Background: Many populations are exposed to arsenic, lead, and manganese. These metals influence immune function. We evaluated the association between exposure to single and multiple metals, including arsenic, lead, and manganese, to humoral immunity as measured by antibody concentrations to diphtheria and tetanus toxoid among vaccinated Bangladeshi children.