<p>Several early-life environmental factors have been associated with altered risk for the development and/or severity of individual allergic conditions. These include exposures implicated in the modulation of the microbiome, such as infant delivery mode, diet, and exposure to antibiotics and antacids. The impact of these early-life factors on allergic multimorbidity remains unknown. To address this knowledge gap, we used electronic medical records for a birth cohort of 158,510 children to track development of atopic dermatitis (AD), IgE-mediated food allergy (IgE-FA), asthma, and allergic rhinitis (AR) in individual children over time. We measured hazard ratios (HRs), adjusted for birth year, race, ethnicity, sex, and insurance payer type, to assess how development of both individual and multiple allergic conditions is influenced by birth mode, feeding practice during the first year of life, or exposure to antibiotics and/or antacids during the first six months of life. We found that vaginal delivery (VD; HR 0.89, 0.83, 0.84, 0.79 for at least 1, 2, 3, 4 conditions, respectively; p≤0.001) and exclusive breastmilk (BM) feeding (HR 0.74, 0.75, 0.89, for at least 1, 2, 3 conditions, respectively; p≤0.001) are associated with reduced cumulative allergic burden, while antibiotic exposure (HR 1.40, 1.44, 1.48, 1.63 for at least 1, 2, 3, 4 conditions, respectively; p≤0.001) and antacid exposure (HR 1.26, 1.35, 1.32 for at least 1, 2, 3 conditions, respectively; p≤0.001) are associated with increased cumulative allergic burden during childhood. This work expands our understanding of how a child's early-life environment may influence their risk of allergy development and progression.</p>

<p><strong>BACKGROUND: </strong>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.</p>

<p><strong>METHODS: </strong>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 ( = 25 999).</p>

<p><strong>RESULTS: </strong>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.</p>

<p><strong>CONCLUSIONS: </strong>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.</p>

<p>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 &gt;98·2% for all AEs. These results demonstrate that EMR-based AE ascertainment and grading substantially improves laboratory AE reporting accuracy.</p>