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Objectives: Return visit (RV) to the emergency department (ED) is considered a benchmarking clinical indicator for health care quality. The purpose of this study was to develop a predictive model for early readmission risk in pediatric EDs comparing the performances of 2 learning machine algorithms., Methods: A retrospective study based on all children younger than 15 years spontaneously returning within 120 hours after discharge was conducted in an Italian university children's hospital between October 2012 and April 2013. Two predictive models, artificial neural network (ANN) and classification tree (CT), were used. Accuracy, specificity, and sensitivity were assessed., Results: A total of 28,341 patient records were evaluated. Among them, 626 patients returned to the ED within 120 hours after their initial visit. Comparing ANN and CT, our analysis has shown that CT is the best model to predict RVs. The CT model showed an overall accuracy of 81%, slightly lower than the one achieved by the ANN (91.3%), but CT outperformed ANN with regard to sensitivity (79.8% vs 6.9%, respectively). The specificity was similar for the 2 models (CT, 97% vs ANN, 98.3%). In addition, the time of arrival and discharge along with the priority code assigned in triage, age, and diagnosis play a pivotal role to identify patients at high risk of RVs., Conclusions: These models provide a promising predictive tool for supporting the ED staff in preventing unnecessary RVs.

Background: Schistosomiasis is a highly prevalent parasitic disease in Senegal. The early symptoms are hematuria and dysuria. Children's comprehension of the disease is fundamental to preventing the infection., Objectives: The aim of this study was to investigate the knowledge attitudes, and practices related to schistosomiasis among schoolchildren in 2 rural villages in Northern Senegal and to evaluate their impact on the disease., Methods: A cross-sectional study was conducted. Data about children's knowledge of schistosomiasis, behavior, and preventive measures were collected through a questionnaire., Findings: Questionnaire responses from 575 schoolchildren were analyzed. Correct answers about risky behavior for schistosomiasis were associated with early symptoms (P = 0.010). Wearing shoes and washing hands with soap were associated with not having hematuria and dysuria (P = 0.007 and 0.049, respectively). Playing in rivers was associated with the aforementioned symptoms (P < 0.001). Children who had good knowledge of schistosomiasis reportedly did not have symptoms (P = 0.002). A logistic regression model showed that female sex (odds ratio = 0.35; P = 0.01) and attending a primary school (odds ratio = 0.13; P < 0.001) were significant predictors of a lower risk of the early symptoms of urinary schistosomiasis., Conclusions: This study revealed that the level of knowledge among children in North Senegal about the causes, transmission, prevention, and treatment of schistosomiasis warrants implementing educational intervention., (Copyright © 2016 Icahn School of Medicine at Mount Sinai. Published by Elsevier Inc. All rights reserved.)