Highlights Health professional students can effectively implement a contact tracing initiative A replicable workflow and onboarding system aids in efficient contact tracing Testing capacity, community buy-in, and sparse resources can impact contact tracing

Purpose Contact tracing has proven successful at controlling COVID-19 globally and the Center for Health Security has recommended that the United States add 100,000 contact tracers to the current workforce. Methods To address gaps in local contact tracing, health professional students partnered with their academic institution to conduct contact tracing for all COVID-19 cases diagnosed on site, which included identifying and reaching their contacts, educating participants and providing social resources to support effective quarantine and isolation. Results From March 24 th to May 28 th , 536 laboratory-confirmed COVID-19 cases were contacted and reported an average of 2.6 contacts. Contacts were informed of their exposure, asked to quarantine and monitored for the onset of symptoms. Callers reached 94% of cases and 84% of contacts. 74% of cases reported at least 1 contact. Household members had higher rates of reporting symptoms (OR 1.65, 95% CI 1.19:2.28). The average test turnaround time decreased from 21.8 days for the first patients of this program to 2.3 days on the eleventh week. Conclusions This provides evidence for the untapped potential of community contact tracing to respond to regional needs, confront barriers to effective quarantine and mitigate the spread of COVID-19.

Neonatal sepsis (NS) is responsible for over 1 million yearly deaths worldwide. In the developing world, NS is often treated without an identified microbial pathogen. Amplicon sequencing of the bacterial 16S rRNA gene can be used to identify organisms that are difficult to detect by routine microbiological methods. However, contaminating bacteria are ubiquitous in both hospital settings and research reagents and must be accounted for to make effective use of these data. In this study, we sequenced the bacterial 16S rRNA gene obtained from blood and cerebrospinal fluid (CSF) of 80 neonates presenting with NS to the Mbarara Regional Hospital in Uganda. Assuming that patterns of background contamination would be independent of pathogenic microorganism DNA, we applied a novel quantitative approach using principal orthogonal decomposition to separate background contamination from potential pathogens in sequencing data. We designed our quantitative approach contrasting blood, CSF, and control specimens and employed a variety of statistical random matrix bootstrap hypotheses to estimate statistical significance. These analyses demonstrate that Leptospira appears present in some infants presenting within 48 h of birth, indicative of infection in utero, and up to 28 days of age, suggesting environmental exposure. This organism cannot be cultured in routine bacteriological settings and is enzootic in the cattle that often live in close proximity to the rural peoples of western Uganda. Our findings demonstrate that statistical approaches to remove background organisms common in 16S sequence data can reveal putative pathogens in small volume biological samples from newborns. This computational analysis thus reveals an important medical finding that has the potential to alter therapy and prevention efforts in a critically ill population.

The majority of patients with Type 1 Diabetes Mellitus (T1D) present with similar symptoms including polyuria, polydipsia, weight loss and fatigue. Unfortunately, some patients progress to diabetic ketoacidosis (DKA) at the time of diagnosis of T1D 1 . Children diagnosed in DKA have increased risk of morbidity, mortality, poor glycaemic control, higher medical costs and healthcare resource utilization including ICU level care 1,2 . Previous research has identified the predictors for children to present in DKA, which include younger children (under 5 years of age), Hispanic or African American race, low socioeconomic status, misdiagnosis at an initial clinical encounter and lack of private health insurance 3 . Thus far, there are limited data on the impact of the COVID-19 pandemic on the rate and severity of DKA in children at initial diagnosis of T1D. Interestingly, some geographic locations noted an increase in DKA frequency during the

For centuries, cannabis and its components have been used to manage a wide variety of symptoms associated with many illnesses. Gastrointestinal (GI) diseases are no exception in this regard. Individuals suffering from inflammatory bowel disease (IBD) are among those who have sought out the ameliorating properties of this plant. As legal limitations of its use have eased, interest has grown from both patients and their providers regarding the potential of cannabis to be used in the clinical setting. Similarly, a growing number of animal and human studies have been undertaken to evaluate the impact of cannabis and cannabinoid signaling elements on the natural history of IBD and its associated complications. There is little clinical evidence supporting the ability of cannabis or related products to treat the GI inflammation underlying these disorders. However, 1 recurring theme from both animal and human studies is that these agents have a significant impact on several IBD-related symptoms, including abdominal pain. In this review, we discuss the role of cannabis and cannabinoid signaling in visceral pain perception, what is currently known regarding the efficacy of cannabis and its derivatives for managing pain, related symptoms and inflammation in IBD, and what work remains to effectively utilize cannabis and its derivatives in the clinical setting.

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Several symptoms have been connected to increased healthcare resource utilization (HRU) in the context of inflammatory bowel disease (IBD), including both Crohn’s disease (CD) and ulcerative colitis (UC). This study was designed to investigate the prevalence of IBD-associated symptoms and to determine whether any are independently associated with HRU. We undertook a retrospective analysis of data related to consecutive IBD patient encounters from a tertiary care referral center between 1/1/2015 and 8/31/2019. Demographics, clinical activity, endoscopic severity, IBD-related symptom scores, anxiety and depression scores, and other key clinical data were abstracted. Four hundred sixty-seven IBD patients [247f.: 220 m; 315 CD, 142 UC and 11 indeterminate colitis] were included in this study. The most common symptoms were fatigue (83.6%), fecal urgency (68.2%) and abdominal pain (63.5%). Fatigue, abdominal pain, anxiety or depression, corticosteroids, and opioids were each positively associated with HRU, while NSAID and mesalamine use were inversely associated on bivariate analysis. The only factor that demonstrated a statistically significant association with HRU in the whole cohort on multivariable analysis was abdominal pain. Abdominal pain is independently associated with HRU and should be specifically screened for in IBD patients to identify individuals at risk of undergoing expensive interventions. This study also reinforces the importance of optimizing diagnostic and therapeutic management of abdominal pain in IBD.

Objective To explore the rate and factors associated with diabetic ketoacidosis (DKA) at diagnosis of type 1 diabetes (T1D) in a single tertiary medical centre in Central Pennsylvania. Methods Retrospective chart review of all individuals ≤ 18 years of age who were diagnosed with T1D (N = 350) at the Penn State Hershey Pediatric Diabetes Clinic from January 2017 to December 2019. We report logistic regression models for DKA at diagnosis of T1D for age, gender, race/ethnicity, BMI percentile, health insurance, outcome of any healthcare encounter 30 days prior to T1D diagnosis, HbA1c level, altered mental status at diagnosis, and diagnosis of autism spectrum disorder and a multivariable logistic regression model including all aforementioned variables. Results Of the 350 newly diagnosed children with T1D from 2017 to 2019, 161/350 (46%) presented in DKA. Among patients with DKA, there were 45 (28%) in mild DKA and 116 (72%) in moderate/severe DKA, which represents 13% and 33% of all patients diagnosed with T1D, respectively. Variables associated with increased risk of DKA at presentation of T1D included age (<3 or 9‐13), BMI percentile (<3% or > 97%), no referral during preceding healthcare encounter, HbA1c level and altered mental status. In a multivariable model, age (<3 or 9‐13), no referral during preceding healthcare encounter, HbA1c level and altered mental status were associated with DKA at presentation, whereas gender, race/ethnicity, BMI percentile, health insurance and autism spectrum disorder diagnosis were not. Discussion Our study notes an overall higher rate of DKA at diagnosis (46%) compared to the SEARCH study (approximately 30%) but a lower rate compared to a recent study in Colorado children (58%).