Diarrhea is one of the leading causes of childhood morbidity and mortality in lower- and middle-income countries. In such settings, access to laboratory diagnostics are often limited, and decisions for use of antimicrobials often empiric. Clinical predictors are a potential non-laboratory method to more accurately assess diarrheal etiology, the knowledge of which could improve management of pediatric diarrhea. We used clinical and quantitative molecular etiologic data from the Global Enteric Multicenter Study (GEMS), a prospective, case-control study, to develop predictive models for the etiology of diarrhea. Using random forests, we screened the available variables and then assessed the performance of predictions from random forest regression models and logistic regression models using 5-fold cross-validation. We identified 1049 cases where a virus was the only etiology, and developed predictive models against 2317 cases where the etiology was known but non-viral (bacterial, protozoal, or mixed). Variables predictive of a viral etiology included lower age, a dry and cold season, increased height-for-age z-score (HAZ), lack of bloody diarrhea, and presence of vomiting. Cross-validation suggests an AUC of 0.825 can be achieved with a parsimonious model of 5 variables, achieving a specificity of 0.85, a sensitivity of 0.59, a NPV of 0.82 and a PPV of 0.64. Predictors of the etiology of pediatric diarrhea can be used by providers in low-resources setting to inform clinical decision-making. The use of non-laboratory methods to diagnose viral causes of diarrhea could be a step towards reducing inappropriate antibiotic prescription worldwide. Diarrhea is one of the leading causes of death in young children worldwide. In low-resource settings, diarrhea testing is not available or too expensive, and the decision to prescribe antibiotics is often made without testing. Using clinical information to predict which cases are caused by viruses, and thus wouldn’t need antibiotics, would help to improve appropriate use of antibiotics. We used data from a large study of childhood diarrhea, paired with advanced statistical methods including machine learning, to come up with the top clinical factors that could predict a viral cause of diarrhea. We compared 1049 cases where a virus was the only cause, with 2317 cases where the cause was known but not a virus. We found that a lower age, dry and cold season, nutritional status defined by increased height, lack of blood diarrhea, and vomiting, were the clinical factors most predictive of whether the diarrhea was caused by a virus. We found that, using just those 5 factors, we were able to predict a viral cause with good accuracy. Our findings can be used by doctors to guide the appropriate use of antibiotics for diarrhea in children.

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.

Purpose: To quantify the damage to the corneal endothelium from the flow of a balanced salt solution during phacoemulsification. Setting: John A. Moran Eye Center, University of Utah, Salt Lake City, Utah. Design: Experimental study. Methods: 12 New Zealand white rabbits received bilateral surgery. 6 eyes served as controls with no irrigation (incision only). In 18 eyes, the Intrepid Balanced tip of the Centurion Ozil (Alcon Laboratories, Inc.) handpiece was inserted into the anterior chamber for continuous irrigation at 50 mL/min with either 250 or 500 mL of balanced salt solution. After killing humanely and enucleation, the corneas were removed, stained with trypan blue–alizarin red, and photographed in a standardized manner (×400 photographs from 5 specific areas and 1 overview photograph from each corneal button). The ImageJ program was used to evaluate cell damage and loss in the photographs obtained from each cornea. Results: Analysis of the ×400 photographs showed no statistically significant differences between control, 250 mL, and 500 mL groups in the percentage of intact, damaged, or lost cells (P = .896, .851, and .972 respectively). For the overview photographs, the differences in areas of intact and damaged cells among the groups were statistically significant, likely because of the peripheral areas of damage related to touches between the phacoemulsification tip and the endothelium during irrigation. Conclusions: The volume of balanced salt solution flow alone did not seem to be a major contributing source of endothelial cell damage and loss, providing further insight into mechanisms of corneal endothelium damage during phacoemulsification.

Purpose: To compare corneal endothelial damage from longitudinal and torsional ultrasound during phacoemulsification. Setting: John A. Moran Eye Center, University of Utah, Salt Lake City, Utah, USA. Design: Experimental study. Methods: 9 New Zealand white rabbits underwent bilateral surgery. After incision, the Intrepid Balanced Tip of the Centurion Ozil handpiece was inserted into the anterior chamber, and the following settings were used: 50 mL/min flow, 70 mm Hg intraocular pressure, 600 mm Hg vacuum, and 60% longitudinal (1 eye) or torsional (contralateral eye) ultrasound for 30 seconds. Cumulative dissipated energy (CDE) was noted. After euthanasia and enucleation, the corneas were removed, stained with trypan blue/alizarin red, and photographed (400× photographs from 5 specific areas and 1 overview photograph from each corneal button). The ImageJ program was used to evaluate cell damage and loss in the photographs obtained from each cornea. Results: Cavitation bubbles around the phacoemulsification tip were generally observed in the longitudinal group. CDE was 17.4 ± 0.58 and 6.93 ± 0.15 in the longitudinal and torsional groups, respectively (P = .003). The percentage of intact cells was statistically higher in the torsional group (94.22% ± 5.99% vs 56.85% ± 22.29%), and the percentage of lost cells was statistically higher in the longitudinal group (42.10% ± 22.02% vs 4.97% ± 6.23%) (P = .003). This was observed in the analysis of the 400× photographs and the overview photographs. Conclusions: This study suggests that torsional ultrasound was associated with significantly less corneal endothelial cell damage than classical longitudinal tip motion, providing further insight on mechanisms of corneal endothelial damage during phacoemulsification.

Extended spectrum beta-lactamase producing Enterobacterales (ESBL-PE) present a risk to public health by limiting the efficacy of multiple classes of beta-lactam antibiotics against infection. International travellers may acquire these organisms and identifying individuals at high risk of acquisition could help inform clinical treatment or prevention strategies. We used data collected from a cohort of 528 international travellers enrolled in a multicentre US-based study to derive a clinical prediction rule (CPR) to identify travellers who developed ESBL-PE colonization, defined as those with new ESBL positivity in stool upon return to the United States. To select candidate features, we used data collected from pre-travel and post-travel questionnaires, alongside destination-specific data from external sources. We utilized LASSO regression for feature selection, followed by random forest or logistic regression modelling, to derive a CPR for ESBL acquisition. A CPR using machine learning and logistic regression on 10 features has an internally cross-validated area under the receiver operating characteristic curve (cvAUC) of 0.70 (95% confidence interval 0.69–0.71). We also demonstrate that a four-feature model performs similarly to the 10-feature model, with a cvAUC of 0.68 (95% confidence interval 0.67–0.69). This model uses traveller’s diarrhoea, and antibiotics as treatment, destination country waste management rankings and destination regional probabilities as predictors. We demonstrate that by integrating traveller characteristics with destination-specific data, we could derive a CPR to identify those at highest risk of acquiring ESBL-PE during international travel.

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. Our method enables electronic real-time updating and flexibility, such that components can be included or excluded according to data availability. We apply this method to the prediction of etiology of pediatric diarrhea, where 'pre-test’ epidemiologic data may be highly informative. Diarrhea has a high burden in low-resource settings, and antibiotics are often over-prescribed. We demonstrate that our integrative method outperforms traditional prediction in accurately identifying cases with a viral etiology, and show that its clinical application, especially when used with an additional diagnostic test, could result in a 61% reduction in inappropriately prescribed antibiotics.