Active SARS-CoV-2 (coronavirus) transmission continues in the US. It is unclear whether better access to coronavirus testing and more consistent use of testing could substantially reduce transmission.
Objective
To describe coronavirus testing in persons with new onset of febrile illness and analyze whether there are changes over time and differences by race and ethnicity.
Design, Setting, and Participants
This cohort study used data from the COVID-19 Citizen Science Study, launched in March 2020, which recruited participants via press release, word-of-mouth, and partner organizations. Participants completed daily surveys about COVID-19 symptoms and weekly surveys about coronavirus testing. All adults (aged at least 18 years) with a smartphone were eligible to join. For this analysis, US participants with new onset of febrile illness from April 2020 to October 2020 were included. Data analysis was performed from November 2020 to March 2021.
Main Outcomes and Measures
Receipt of a coronavirus test result within 7 days of febrile illness onset.
Results
Of the 2679 participants included in this analysis, the mean (SD) age was 46.3 (13.4) years, 1983 were female (74%), 2017 were college educated (75%), and a total of 3865 distinct new febrile illness episodes were reported (300 episodes [7.8%] from Hispanic participants, 71 episodes [1.8%] from Black participants, and 3494 episodes [90.4%] from not Black, not Hispanic participants) between April 2 and October 23, 2020. In weekly surveys delivered during the 14 days after fever onset, 12% overall (753 participants) indicated receipt of a test result. Using serial survey responses and parametric time-to-event modeling, it was estimated that by 7 days after onset of febrile illness, a total of 20.5% (95% CI, 19.1%-22.0%) had received a test result. This proportion increased from 9.8% (95% CI, 7.5%-12.0%) early in the epidemic to 24.1% (95% CI, 21.5%-26.7%) at the end of July, but testing rates did not substantially improve since then, increasing to 25.9% (95% CI; 21.6%-30.3%) in late October at the start of the winter surge. Black participants reported receiving a test result about half as often as others (7% [7 of 103] of survey responses vs 12% [53 of 461] for Hispanic vs 13% [693 of 5516] for not Black, not Hispanic;P = .03). This association was not statistically significant in adjusted time-to-event models (hazard ratio = 0.59 vs not Black, not Hispanic participants; 95% CI, 0.26-1.34).
Conclusions and Relevance
Systematic underuse of coronavirus testing was observed in this cohort study through late October 2020, at the beginning of the winter COVID-19 surge, which may have contributed to preventable coronavirus transmission.
ObjectiveTo describe PCORnet, a clinical research network developed for patient-centered outcomes research on a national scale.Study Design and SettingDescriptive study of the current state and future directions for PCORnet. We conducted cross-sectional analyses of the health systems and patient populations of the 9 Clinical Research Networks and 2 Health Plan Research Networks that are part of PCORnet.ResultsWithin the Clinical Research Networks, electronic health data are currently collected from 337 hospitals, 169,695 physicians, 3,564 primary care practices, 338 emergency departments, and 1,024 community clinics. Patients can be recruited for prospective studies from any of these clinical sites. The Clinical Research Networks have accumulated data from 80 million patients with at least one visit from 2009 to 2018. The PCORnet Health Plan Research Network population of individuals with a valid enrollment segment from 2009 to 2019 exceeds 60 million individuals, who on average have 2.63 years of follow-up.ConclusionPCORnet's infrastructure comprises clinical data from a diverse cohort of patients and has the capacity to rapidly access these patient populations for pragmatic clinical trials, epidemiological research, and patient-centered research on rare diseases.
Abstract Background Prior studies have documented differences in the age, racial, and ethnic characteristics among patients with SARS-CoV-2 infection. However, little is known about how these characteristics changed over time during the pandemic and whether racial, ethnic, and age disparities evident early in the pandemic were persistent over time. This study reports on trends in SARS-CoV-2 infections among U.S. adults from March 1, 2020 to January, 31 2022, using data from electronic health records. Methods and Findings We captured repeated cross-sectional information from 43 large healthcare systems in 52 U.S. States and territories, participating in PCORnet ® , the National Patient-Centered Clinical Research Network. Using distributed queries executed at each participating institution, we acquired information for all patients ≥ 20 years of age who were tested for SARS-CoV-2 (both positive and negative results), including care setting, age, sex, race, and ethnicity by month as well as comorbidities (assessed with diagnostic codes). During this time period, 1,325,563 patients had positive (13% inpatient) and 6,705,868 patients had negative (25% inpatient) viral tests for SARS-CoV-2. Disparities in testing positive were present across racial and ethnic groups, especially in the inpatient setting. Compared to White patients, Black or African American and other race patients had relative risks for testing positive of 1.5 or greater in the inpatient setting for 12 of the 23-month study period. Compared to non-Hispanic patients, Hispanic patients had relative risks for testing positive in the inpatient setting of 1.5 or greater for 16 of 23. Ethnic and racial differences were present in emergency department and ambulatory settings but were less common across time than in inpatient settings. Trends in infections by age group demonstrated higher test positivity for older patients in the inpatient setting only for most months, except for June and July of 2020, April to August 2021, and January 2022. Comorbidities were common, with much higher rates among those hospitalized; hypertension (38% of patients SARS-CoV-2 positive vs. 29% for those negative) and type 2 diabetes mellitus (22% vs. 13%) were the most common. Conclusion and Relevance Racial and ethnic disparities changed over time among persons infected with SARS-CoV-2. These trends highlight potential underlying mechanisms, such as poor access to care and differential vaccination rates, that may have contributed to greater disparities, especially early in the pandemic. Monitoring data on characteristics of patients testing positive in real time could allow public health officials and policymakers to tailor interventions to ensure that patients and communities most in need are receiving adequate testing, mitigation strategies, and treatment.
Incidence estimates of post-acute sequelae of SARS-CoV-2 infection, also known as long-COVID, have varied across studies and changed over time. We estimated long-COVID incidence among adult and pediatric populations in three nationwide research networks of electronic health records (EHR) participating in the RECOVER Initiative using different classification algorithms (computable phenotypes). This EHR-based retrospective cohort study included adult and pediatric patients with documented acute SARS-CoV-2 infection and two control groups-- contemporary COVID-19 negative and historical patients (2019). We examined the proportion of individuals identified as having symptoms or conditions consistent with probable long-COVID within 30-180 days after COVID-19 infection (incidence proportion). Each network (the National COVID Cohort Collaborative (N3C), National Patient-Centered Clinical Research Network (PCORnet), and PEDSnet) implemented its own long-COVID definition. We introduced a harmonized definition for adults in a supplementary analysis. Overall, 4% of children and 10-26% of adults developed long-COVID, depending on computable phenotype used. Excess incidence among SARS-CoV-2 patients was 1.5% in children and ranged from 5-6% among adults, representing a lower-bound incidence estimation based on our control groups. Temporal patterns were consistent across networks, with peaks associated with introduction of new viral variants. Our findings indicate that preventing and mitigating long-COVID remains a public health priority. Examining temporal patterns and risk factors of long-COVID incidence informs our understanding of etiology and can improve prevention and management.
Introduction In the field of lung cancer treatments, significant progresses have been realized during last decade, such as targeted therapies and immunotherapies. Nevertheless, chemotherapy remains the gold standard for cancer. Pemetrexed is a chemotherapeutic agent commonly used in advanced lung cancer. This drug has a broad-spectrum effect that can induce significant side effects in patients. However, the impact of pemetrexed on gut microbiota and gastrointestinal inflammation in PDX mice remains unknown, although the role of the microbiota in carcinogenesis and modulation of efficacy or toxicity of chemotherapy agents has been demonstrated. The aim of this new study was to explore the impact of pemetrexed on the gut microbiota and the integrity of intestinal epithelial barrier and inflammation markers of PDX models following treatment.Methods Upon establishment of the PDX model, mice were treated with pemetrexed for 2 weeks. Stool specimens were collected at 3 time-points: before, after and one week after treatment. Gut microbiota composition was studied by 16S rRNA gene sequencing. The colon integrity of the epithelial barrier was evaluated by a histological examination, a permeability measurement and a selected cytokines expression. In parallel, body weight was recorded and tissues were sampled for assessment of toxicity and inflammation.Results Pemetrexed induced a significant body weight loss after each treatment cycle reflecting toxicity as known in clinical results. We have found that pemetrexed and tumor induced several modifications on microbiota composition, and the more important perturbation was the significant increase of the relative abundance of Enterobacteriaceae. A significant alteration of epithelial barrier integrity associated with early inflammation and infiltration of leukocytes into mucosal tissues was observed following treatment. Moreover, we have shown that pemetrexed effect on the microbiota was reproducible on several models of lung PDX models of lung carcinoma, and that dysbiosis seem proportional to the effectiveness of chemotherapy.Conclusion This work is a preliminary approach, that confirms the relationship between microbiota and chemotherapy. A better understanding of gut microbiota alterations induced by chemotherapy could help reduce side effects. It is essential to expand our knowledge about the chemotherapy impact on microbiota in order to minimize the side effects, avoid infection complications, and improve therapy efficiency.Citation Format: Cindy Pensec, Dominique Guenot, Loreley Calvet, Caroline Mignard, Olivier Duchamp, Thomas Carton, Sébastien Leuillet, Hervé M. Blottière, Françoise Le Vacon. Impact of chemotherapy on the intestinal microbiome and epithelial barrier in PDX models of lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 662.
Background Little is known about whether people who use both tobacco and cannabis (co-use) are more or less likely to have mental health disorders than single substance users or non-users. We aimed to examine associations between use of tobacco and/or cannabis with anxiety and depression. Methods We analyzed data from the COVID-19 Citizen Science Study, a digital cohort study, collected via online surveys during 2020–2022 from a convenience sample of 53,843 US adults (≥ 18 years old) nationwide. Past 30-day use of tobacco and cannabis was self-reported at baseline and categorized into four exclusive patterns: tobacco-only use, cannabis-only use, co-use of both substances, and non-use. Anxiety and depression were repeatedly measured in monthly surveys. To account for multiple assessments of mental health outcomes within a participant, we used Generalized Estimating Equations to examine associations between the patterns of tobacco and cannabis use with each outcome. Results In the total sample (mean age 51.0 years old, 67.9% female), 4.9% reported tobacco-only use, 6.9% cannabis-only use, 1.6% co-use, and 86.6% non-use. Proportions of reporting anxiety and depression were highest for the co-use group (26.5% and 28.3%, respectively) and lowest for the non-use group (10.6% and 11.2%, respectively). Compared to non-use, the adjusted odds of mental health disorders were highest for co-use ( Anxiety : OR = 1 . 89 , 95%CI = 1 . 64–2 . 18; Depression : OR = 1 . 77 , 95%CI = 1 . 46–2 . 16 ), followed by cannabis-only use, and tobacco-only use. Compared to tobacco-only use, co-use (OR = 1 . 35 , 95%CI = 1 . 08–1 . 69) and cannabis-only use (OR = 1 . 17 , 95%CI = 1 . 00–1 . 37 ) were associated with higher adjusted odds for anxiety, but not for depression. Daily use (vs. non-daily use) of cigarettes, e-cigarettes, and cannabis were associated with higher adjusted odds for anxiety and depression. Conclusions Use of tobacco and/or cannabis, particularly co-use of both substances, were associated with poor mental health. Integrating mental health support with tobacco and cannabis cessation may address this co-morbidity.
