Increase in gunshot wounds at a level 1 trauma center following the COVID19 pandemic.

OBJECTIVES: To compare the number of patients with gunshot wounds presenting to our level 1 trauma center before and during the COVID-19 pandemic with a focus on volume trends after the lifting of stay-at-home directives through August 2020. DESIGN: Retrospective. SETTING: Level 1 trauma center. PATIENTS/PARTICIPANTS: Seven hundred six gunshot wound patients between 2016 and 2020 (months March to September only). INTERVENTION: COVID-19 pandemic and resultant stay at home directives. MAIN OUTCOME MEASUREMENTS: Number of patients presenting with gunshot wounds per time period. RESULTS: The number of patients with gunshot wounds presenting to our institution increased by 11.7% in March-April 2020 and by 67% in May-August 2020 when compared to previous years. Length of stay significantly decreased in 2020 compared to 2018 and 2019. In 2020, significantly fewer patients had orthopaedic procedures than in 2018. CONCLUSIONS: Patients presenting with gunshot wounds increased during the initial "stay-at-home" portion of the pandemic in March to April and increased significantly more after the restrictions were relaxed during May to August.Level of Evidence: Therapeutic Level III.

Phenotyping coronavirus disease 2019 during a global health pandemic: Lessons learned from the characterization of an early cohort.

From the start of the coronavirus disease 2019 (COVID-19) pandemic, researchers have looked to electronic health record (EHR) data as a way to study possible risk factors and outcomes. To ensure the validity and accuracy of research using these data, investigators need to be confident that the phenotypes they construct are reliable and accurate, reflecting the healthcare settings from which they are ascertained. We developed a COVID-19 registry at a single academic medical center and used data from March 1 to June 5, 2020 to assess differences in population-level characteristics in pandemic and non-pandemic years respectively. Median EHR length, previously shown to impact phenotype performance in type 2 diabetes, was significantly shorter in the SARS-CoV-2 positive group relative to a 2019 influenza tested group (median 3.1 years vs 8.7; Wilcoxon rank sum P = 1.3e-52). Using three phenotyping methods of increasing complexity (billing codes alone and domain-specific algorithms provided by an EHR vendor and clinical experts), common medical comorbidities were abstracted from COVID-19 EHRs, defined by the presence of a positive laboratory test (positive predictive value 100%, recall 93%). After combining performance data across phenotyping methods, we observed significantly lower false negative rates for those records billed for a comprehensive care visit (p = 4e-11) and those with complete demographics data recorded (p = 7e-5). In an early COVID-19 cohort, we found that phenotyping performance of nine common comorbidities was influenced by median EHR length, consistent with previous studies, as well as by data density, which can be measured using portable metrics including CPT codes. Here we present those challenges and potential solutions to creating deeply phenotyped, acute COVID-19 cohorts.

Pediatric Patients with SARS-CoV-2 Infection: Clinical Characteristics in the United States from a Large Global Health Research Network.

Background Few reports have been published on the clinical presentation of pediatric patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We aim to shed more light on the clinical presentation of pediatric patients infected with coronavirus disease 2019 (COVID-19), and also potential risk factors for more severe clinical case presentation. Methods We used a large global health research network to gather clinical data extracted from the electronic medical records of pediatric patients aged < 18 years with confirmed SARS-CoV-2 from January 1, 2020 to May 7, 2020. Clinical symptoms at presentation, hospitalization status, associated co-morbidities, and treatments received were reviewed. Results A total of 627 patients with COVID-19 diagnosis (334 were outpatient, 293 were inpatient) were included from a total of 20 organizations across the United States. The mean age of patients was seven years, 48% were females. Inpatients were younger than outpatients (mean age of 5.6 years vs 8.2 years, p<0.001). Sixty-one percent of patients in the inpatient group were < 5 years of age vs. 44% in the outpatient group. Amongst 293 inpatients, 90% (n=265) were non-severe and 10% (n=28) were classified as severe. The percentage of patients <5 years was higher in severe inpatients vs. non-severe (71% vs 60%.) Significantly more patients with a severe illness vs. non-severe illness had a history of co-morbidity including non-congenital heart disease (50% vs 11%, p<0.001) and disease of the respiratory system (86% vs 53%, p< 0.001). Conclusion Clinicians should closely monitor young children with underlying conditions and COVID-19, as they may be more likely to be hospitalized and have a higher severity of the disease.