Key Points Question Among children with a COVID-19 diagnosis, what conditions are common, and which are associated with severe COVID-19 illness? Findings In this cross-sectional study of 43 465 patients aged 18 years or younger with COVID-19, more than one-quarter had 1 or more underlying condition; asthma, obesity, neurodevelopmental disorders, and certain mental health conditions were most common. Certain conditions as well as medical complexity were associated with a higher risk of severe COVID-19 illness. Meaning These findings expand the knowledge available regarding children with COVID-19 and could inform pediatric clinical practice and public health priorities, such as prevention and mitigation of COVID-19.

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In this cross-sectional study of 540,667 adult hospitalized patients with COVID-19, 94.9% had at least 1 underlying medical condition. Hypertension and disorders of lipid metabolism were the most frequent, whereas obesity, diabetes with complication, anxiety disorders, and the total number of conditions were the strongest risk factors for severe COVID-19 illness. What are the implications for public health practice?Preventing COVID-19 in populations with these underlying conditions and multiple conditions should remain a public health priority, with targeted mitigation efforts and ensuring high uptake of vaccine, when available, in these individuals and their close contacts.

This cohort study uses data from the Premier Healthcare Database Special COVID-19 Release to assess the association of demographic and clinical characteristics with severe COVID-19 illness among hospitalized US pediatric patients with COVID-19.

Background Older adults and people from certain racial and ethnic groups are disproportionately represented in coronavirus disease 2019 (COVID-19) hospitalizations and deaths. Methods Using data from the Premier Healthcare Database on 181 813 hospitalized adults diagnosed with COVID-19 during March–September 2020, we applied multivariable log-binomial regression to assess the associations between age and race/ethnicity and COVID-19 clinical severity (intensive care unit [ICU] admission, invasive mechanical ventilation [IMV], and death) and to determine whether the impact of age on clinical severity differs by race/ethnicity. Results Overall, 84 497 (47%) patients were admitted to the ICU, 29 078 (16%) received IMV, and 27 864 (15%) died in the hospital. Increased age was strongly associated with clinical severity when controlling for underlying medical conditions and other covariates; the strength of this association differed by race/ethnicity. Compared with non-Hispanic White patients, risk of death was lower among non-Hispanic Black patients (adjusted risk ratio, 0.96; 95% CI, 0.92–0.99) and higher among Hispanic/Latino patients (risk ratio [RR], 1.15; 95% CI, 1.09–1.20), non-Hispanic Asian patients (RR, 1.16; 95% CI, 1.09–1.23), and patients of other racial and ethnic groups (RR, 1.13; 95% CI, 1.06–1.21). Risk of ICU admission and risk of IMV were elevated among some racial and ethnic groups. Conclusions These results indicate that age is a driver of poor outcomes among hospitalized persons with COVID-19. Additionally, clinical severity may be elevated among patients of some racial and ethnic minority groups. Public health strategies to reduce severe acute respiratory syndrome coronavirus 2 infection rates among older adults and racial and ethnic minorities are essential to reduce poor outcomes.

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Background Escherichia coli is one of the most common causes of healthcare-associated infections (HAI); multidrug resistance reduces available options for antibiotic treatment. We examined factors associated with the spread of multidrug-resistant E. coli phenotypes responsible for device- and procedure-related HAI from acute care hospitals, long term acute care hospitals and inpatient rehabilitation facilities, using isolate and antimicrobial susceptibility data reported to the National Healthcare Safety Network (NHSN) from 2013-2017. Methods We used multivariable logistic regression to examine associations between co-resistant phenotypes, patient and healthcare facility characteristics, and time. We also examined the geographic distributione of co-resistant phenotypes each year by state and by hospital referral region to identify hot spots. Results A total of 96,672 E. coli isolates were included. Patient median age was 62 years; 60% were females; over half (54%) were reported from catheter-associated urinary tract infections. From 2013-2017, 35% of the isolates were non-susceptible to FQs; 17% to ESCs; and 13% to both ESCs and FQs. The proportion of isolates co-resistant to ESCs and FQs was higher in 2017 (14%) than in 2013 (11%) (P<0.0001); overall prevalence and increases were heterogeneously distributed across healthcare referral regions. Co-resistance to FQs and ESCs was independently associated with male sex, central line-associated bloodstream infections, long-term acute care hospitals, and the 2016-17 (v. 2013-14) reporting period. Conclusions Multidrug-resistance among E.coli causing device- and procedure-related HAIs has increased in the United States. FQ and ESC co-resistant strains appear to be spreading heterogeneously across hospital referral regions.

Background Community-onset urinary tract infections (coUTIs) are one of the most common indications for antibiotic prescribing. It is important to understand patient demographic factors associated with microorganisms causing coUTI and their antibiotic resistance profiles, to tailor antibiotic prescribing practices. We analyzed microbiology data to understand factors associated with coUTI in the United States (US). Methods CoUTIs were identified in the Premier Healthcare Database and Cerner Health Facts among patients treated at participating healthcare facilities in the US between 2012-2017. Cases were defined by urine cultures yielding a bacterial organism and were collected in outpatient settings or within three days of hospitalization. Only the first specimen for each encounter was included in the analysis. Data on the organisms isolated, patient’s age, sex, and US census regions of the submitting facilities were described and compared using chi-square tests for associations. Encounters were classified as inpatient (INPT), observation (OBS), emergency department (ED), and outpatient (OTPT) based on the setting in which the culture was submitted. Results Using data from 637 acute care hospitals, urine samples from 3,291,561 encounters were included, with 776,653 (25.7%) INPT, 1,063,219 (34.8%) ED, 107,760 (3.5%) OBS, and 1,092,658 (35.8%) OTPT. The pathogens most frequently associated with coUTIs were Escherichia coli (57.3%), Klebsiella pneumoniae (9.7%), Enterococcus faecalis (5.1%), Proteus mirabilis (4.9%), and Pseudomonas aeruginosa (2.9%). Female sex, age < 65y and OTPT and ED settings were associated with higher relative frequency of E. coli (all p < 0.0001). Male sex, INPT setting and age >65 y were associated with higher relative frequency of P. aeruginosa, P. mirabilis and E. faecalis (all p < 0.0001, Figure). K. pneumoniae was found at higher relative frequency in those >45y, and in INPT and OBS settings (all p < 0.0001). Figure. Distribution of pathogens most frequently associated with community onset urinary tract infections Conclusion Understanding patient factors associated with the microbiology of coUTIs is an important step in developing treatment recommendations and antibiotic stewardship efforts. Further analyses will include assessing the impact of major antibiotic resistance phenotypes, geographic and healthcare settings. Disclosures All Authors: No reported disclosures