BACKGROUND: Universal screening is recommended to reduce the age of diagnosis for autism spectrum disorder (ASD). However, there are insufficient data on children who screen negative and no study of outcomes from truly universal screening. With this study, we filled these gaps by examining the accuracy of universal screening with systematic follow-up through 4 to 8 years. METHODS: Universal, primary care-based screening was conducted using the Modified Checklist for Autism in Toddlers with Follow-Up (M-CHAT/F) and supported by electronic administration and integration into electronic health records. All children with a well-child visit (1) between 16 and 26 months, (2) at a Children's Hospital of Philadelphia site after universal electronic screening was initiated, and (3) between January 2011 and July 2015 were included (N = 25 999). RESULTS: Nearly universal screening was achieved (91%), and ASD prevalence was 2.2%. Overall, the M-CHAT/F's sensitivity was 38.8%, and its positive predictive value (PPV) was 14.6%. Sensitivity was higher in older toddlers and with repeated screenings, whereas PPV was lower in girls. Finally, the M-CHAT/F's specificity and PPV were lower in children of color and those from lower-income households. CONCLUSIONS: Universal screening in primary care is possible when supported by electronic administration. In this "real-world" cohort that was systematically followed, the M-CHAT/F was less accurate in detecting ASD than in previous studies. Disparities in screening rates and accuracy were evident in traditionally underrepresented groups. Future research should focus on the development of new methods that detect a greater proportion of children with ASD and reduce disparities in the screening process. WHAT'S KNOWN ON THIS SUBJECT: Universal screening for autism spectrum disorder is recommended in primary care to facilitate early detection. However, the US Preventive Services Task Force concluded that there is currently insufficient data from primary care and with longitudinal follow-up to recommend universal screening. WHAT THIS STUDY ADDS: We examined the accuracy of autism screening in a diverse cohort screened nearly universally (91%) and followed-up systematically. The M-CHAT/F had lower sensitivity and positive predictive value than in previous studies; disparities were observed in screening rates and accuracy.

Background The coronavirus disease 2019 (COVID-19) pandemic caused dramatic changes in daily routines and health care utilization and delivery patterns in the United States. Understanding the influence of these changes and associated public health interventions on asthma care is important to determine effects on patient outcomes and identify measures that will ensure optimal future health care delivery. Objective We sought to identify changes in pediatric asthma-related health care utilization, respiratory viral testing, and air pollution during the COVID-19 pandemic. Methods For the time period January 17 to May 17, 2015 to 2020, asthma-related encounters and weekly summaries of respiratory viral testing data were extracted from Children's Hospital of Philadelphia electronic health records, and pollution data for 4 criteria air pollutants were extracted from AirNow. Changes in encounter characteristics, viral testing patterns, and air pollution before and after Mar 17, 2020, the date public health interventions to limit viral transmission were enacted in Philadelphia, were assessed and compared with data from 2015 to 2019 as a historical reference. Results After March 17, 2020, in-person asthma encounters decreased by 87% (outpatient) and 84% (emergency + inpatient). Video telemedicine, which was not previously available, became the most highly used asthma encounter modality (61% of all visits), and telephone encounters increased by 19%. Concurrently, asthma-related systemic steroid prescriptions and frequency of rhinovirus test positivity decreased, although air pollution levels did not substantially change, compared with historical trends. Conclusions The COVID-19 pandemic in Philadelphia was accompanied by changes in pediatric asthma health care delivery patterns, including reduced admissions and systemic steroid prescriptions. Reduced rhinovirus infections may have contributed to these patterns.

BACKGROUND Eosinophilic esophagitis (EoE) is an allergic inflammatory disease that is triggered by food allergens and characterized by progressive esophageal dysfunction. Recently, EoE has been identified in patients undergoing oral immunotherapy (OIT) for IgE-mediated food allergy, suggesting an association. OBJECTIVE We sought to ascertain whether significant associations exist between IgE-mediated food allergies and EoE. METHODS Utilizing analysis of EMR data and manual chart review, we examined our sub-specialty care network of 35,528 children and adolescents to identify and characterize patients with IgE-mediated, and EoE food allergy. The most common food allergens were defined, and the prevalence of EoE in patients with IgE-mediated food allergy was determined. Logistic regression was used to measure the extent to which IgE-mediated food allergy to specific foods is associated with EoE. RESULTS The most common causes of EoE were milk, grains, meats, peanut, tree nuts, egg, and soy, an allergen pattern that is distinct from that of IgE-mediated food allergy. The prevalence of EoE in patients with IgE-mediated food allergy was higher than that reported in the general population (4.7% vs 0.04%). The distribution of IgE-mediated food allergens in patients with EoE was similar to that of the general population, and IgE-mediated allergy to egg (2.27; 1.91–2.64), milk (4.19; 3.52–4.97), or shellfish (1.55; 1.24–1.92) was significantly associated with EoE diagnosis. CONCLUSIONS Our findings support a clinical association between these conditions that has implications for the management of children with food allergy, and particular relevance to patients undergoing OIT.

No abstract

Summary Despite the importance of adverse event (AE) reporting, AEs are under-reported on clinical trials. We hypothesized that electronic medical record (EMR) data can ascertain laboratory-based AEs more accurately than those ascertained manually. EMR data on 12 AEs for patients enrolled on two Children’s Oncology Group (COG) trials at one institution were extracted, processed and graded. When compared to gold standard chart data, COG AE report sensitivity and positive predictive values (PPV) were 0–21.1% and 20–100%, respectively. EMR sensitivity and PPV were >98.2% for all AEs. These results demonstrate that EMR-based AE ascertainment and grading substantially improves laboratory AE reporting accuracy.