with all other racial/ethnic groups included in the total). The gastroschisis case definition was based on the British Pediatric Association Classification of Diseases code (756.71) or the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code for gastroschisis (756.73, or before 10/1/2009, 756.79, with verification to confirm cases of gastroschisis, because the previous code was shared with omphalocele). Gastroschisis cases included live births, fetal deaths, † and elective terminations. § Data were pooled at CDC, and gastroschisis prevalence was calculated for each year, maternal age group, and race/ethnicity. Prevalence was calculated as number of gastroschisis cases among all birth outcomes divided by the total number of live births. The denominators of total number of live births in the same catchment area as the birth defects surveillance program were reported by states or obtained from public use data files. Poisson exact methods were used to calculate 95% CIs for each prevalence estimate. Prevalence ratios were calculated by dividing the prevalence during 2006-2012 by the prevalence during 1995-2005, and CIs for the prevalence ratios were calculated using Poisson regression.Because the comparison of prevalence between the two study periods involved an artificial breakpoint during the 18-year data span and only examined pooled prevalence within those periods, joinpoint regression analysis was used to identify statistically significant changes in the annual prevalence of gastroschisis over the course of the entire study period (1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012). Joinpoint regression initially models annual trend data by fitting a straight line (i.e., zero joinpoints). Then, joinpoints are added, one at a time, and a Monte Carlo permutation test is used to determine the optimal number of joinpoints. Each joinpoint in the final model corresponds to a significant change in the trend, and an AAPC and its 95% CI are calculated to describe how the rate changes within each time interval (3). The estimated overall percent change was calculated by first converting the AAPC to the projected single year change in prevalence and then exponentiating to the number of years studied minus one to estimate the total increase throughout the 18 years. This gives the magnitude of the increase, which

Importance: A surge in severe cases of COVID-19 (coronavirus disease 2019) in children would present unique challenges for hospitals and public health preparedness efforts in the United States. Objective: To provide evidence-based estimates of children infected with SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) and projected cumulative numbers of severely ill pediatric COVID-19 cases requiring hospitalization during the US 2020 pandemic. Design: Empirical case projection study. Main Outcomes and Measures: Adjusted pediatric severity proportions and adjusted pediatric criticality proportions were derived from clinical and spatiotemporal modeling studies of the COVID-19 epidemic in China for the period January-February 2020. Estimates of total children infected with SARS-CoV-2 in the United States through April 6, 2020, were calculated using US pediatric intensive care unit (PICU) cases and the adjusted pediatric criticality proportion. Projected numbers of severely and critically ill children with COVID-19 were derived by applying the adjusted severity and criticality proportions to US population data, under several scenarios of cumulative pediatric infection proportion (CPIP). Results: By April 6, 2020, there were 74 children who had been reported admitted to PICUs in 19 states, reflecting an estimated 176 190 children nationwide infected with SARS-CoV-2 (52 381 infants and toddlers younger than 2 years, 42 857 children aged 2-11 years, and 80 952 children aged 12-17 years). Under a CPIP scenario of 5%, there would be 3.7 million children infected with SARS-CoV-2, 9907 severely ill children requiring hospitalization, and 1086 critically ill children requiring PICU admission. Under a CPIP scenario of 50%, 10 865 children would require PICU admission, 99 073 would require hospitalization for severe pneumonia, and 37.0 million would be infected with SARS-CoV-2. Conclusions and Relevance: Because there are 74.0 million children 0 to 17 years old in the United States, the projected numbers of severe cases could overextend available pediatric hospital care resources under several moderate CPIP scenarios for 2020 despite lower severity of COVID-19 in children than in adults.

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Background/Objectives: In this report, the National Birth Defects Prevention Network (NBDPN) examines and compares gastroschisis and omphalocele for a recent 5-year birth cohort using data from 30 population-based birth defect surveillance programs in the United States. Methods: As a special call for data for the 2019 NBDPN Annual Report, state programs reported expanded data on gastroschisis and omphalocele for birth years 2012–2016. We estimated the overall prevalence (per 10,000 live births) and 95% confidence intervals (CI) for each defect as well as by maternal race/ethnicity, maternal age, infant sex, and case ascertainment methodology utilized by the program (active vs. passive). We also compared distribution of cases by maternal and infant factors and presence/absence of other birth defects. Results: The overall prevalence estimates (per 10,000 live births) were 4.3 (95% CI:4.1–4.4) for gastroschisis and 2.1 (95% CI: 2.0–2.2) for omphalocele. Gastroschisis was more frequent among young mothers (<25 years) and omphalocele more common among older mothers (>40 years). Mothers of infants with gastroschisis were more likely to be underweight/normal weight prior to pregnancy and mothers of infants with omphalocele more likely to be overweight/obese. Omphalocele was twice as likely as gastroschisis to co-occur with other birth defects. Conclusions: This report highlights important differences between gastroschisis and omphalocele. These differences indicate the importance of distinguishing between these defects in epidemiologic assessments. The report also provides additional data on co-occurrence of gastroschisis and omphalocele with other birth defects. This information can provide a basis for future research to better understand these defects.

Objective. We linked data from two independent birth defects surveillance systems with different case-finding methods in an overlapping geographic area to assess Florida's suveillance of birth defects (e.g., neural tube defects, orofacial clefts, gastroschisis/omphalocele, and chromosomal defects), focusing on sensitivity and completeness of ascertainment measures.Methods. Live-born infants identified from each system born during 2003-2006 in a nine-county catchment area with specific birth defects were linked to birth certificates. Using the enhanced surveillance system as a gold standard, we calculated the sensitivity of the Florida Birth Defects Registry (FBDR) for identifying infants. Next, we used capture-recapture models to estimate the completeness of case ascertainment and the prevalence of each birth defect in the catchment area. We used multivariable logistic regression models with backward elimination to estimate adjusted odds ratios and 95% confidence intervals for factors significantly associated with the FBDR's failure to capture infants ultimately identified by enhanced surveillance.Results. The FBDR's sensitivity was 89.3%, and the overall completeness of ascertainment was estimated as 86.6%. Defect-specific sensitivity and completeness of ascertainment varied significantly by defect. The combined defect-specific sensitivity for all malformations under study was 86.6%; completeness of ascertainment ranged from 45.6% for anencephaly to 88.6% for Down syndrome, 87.9% for spina bifida without anencephaly, and 87.0% for orofacial clefts.Conclusions. For the defects under study, the FBDR captured nearly nine of every 10 infants born with selected birth defects. However, the FBDR's ability to identify specific defects was both more limited and defect dependent with widely varying defect-specific sensitivities.

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Background The optimal approach for treating outpatient male urinary tract infections (UTIs) is unclear. We studied the current management of male UTI in private outpatient clinics, and we evaluated antibiotic choice, treatment duration, and the outcome of recurrence of UTI. Methods Visits for all male patients 18 years of age and older during 2011–2015 with International Classification of Diseases, Ninth Revision, Clinical Modification codes for UTI or associated symptoms were extracted from the EPIC Clarity Database of 2 family medicine, 2 urology, and 1 internal medicine clinics. For eligible visits in which an antibiotic was prescribed, we extracted data on the antibiotic used, treatment duration, recurrent UTI episodes, and patient medical and surgical history. Results A total of 637 visits were included for 573 unique patients (mean age 53.7 [±16.7 years]). Fluoroquinolones were the most commonly prescribed antibiotics (69.7%), followed by trimethoprim-sulfamethoxazole (21.2%), nitrofurantoin (5.3%), and beta-lactams (3.8%). Antibiotic choice was not associated with UTI recurrence. In the overall cohort, longer treatment duration was not significantly associated with UTI recurrence (odds ratio [OR] = 1.95; 95% confidence interval [CI], 0.91–4.21). Longer treatment was associated with increased recurrence after excluding men with urologic abnormalities, immunocompromising conditions, prostatitis, pyelonephritis, nephrolithiasis, and benign prostatic hyperplasia (OR = 2.62; 95% CI, 1.04–6.61). Conclusions Our study adds evidence that men with UTI without evidence of complicating conditions do not need to be treated for longer than 7 days. Shorter duration of treatment was not associated with increased risk of recurrence. Shorter treatment durations for many infections, including UTI, are becoming more attractive to reduce the risk of resistance, adverse events, and costs.