Comprehensive Code List Associated with CDC-Defined High-Risk Underlying Medical Conditions Leading to Potential Progression to Severe COVID-19 Outcomes

Objectives: This analysis was conducted to develop a comprehensive list of ICD-10 CM codes for underlying conditions identified by the CDC as being associated with high-risk of developing severe COVID-19 and assessed the consistency of these codes when applied to large US based datasets. Method(s): The comprehensive list of ICD 10-CM codes for CDC-defined high-risk underlying conditions were mapped from CDC references and FDA Sentinel code lists. These codes were subsequently applied to Optum's de-identified Clinformatics Data Mart Database (claims) and the Optum de-identified Electronic Health Record (EHR) database across 3 years (2018, 2019 and 2020) among continuously enrolled subjects >= 12 years of age to determine the performance and consistency in identifying these high-risk underlying conditions annually over these years. Result(s): A total of 10,276 ICD-10 codes were mapped to 21 underlying conditions. Within the claims data, 62.7% of subjects >= 12 years had >= 1 CDC-defined high-risk condition (excluding age) with 26.6% of patients >= 65 years while in the EHR data 38% had >= 1 high-risk underlying condition (excluding age) with 14.4% >= 65 years. These results were similar and consistent in both datasets across all years. Patients aged 12-64 years in the claims data had a higher rate of >=1 high risk underlying condition relative to the EHR data, 49.3% and 34%, respectively. The top 5 conditions among the >= 65 were identical across both databases: hypertension, immunocompromised status, heart conditions, diabetes (type 1 or 2), and overweight/obesity. The top 5 conditions among the 12-64 age group were also similar among the databases and included: immunocompromised status, hypertension, overweight/obesity, smoking (current or former), and mental health conditions. Conclusion(s): These findings present a comprehensive list of codes that can be used by researchers, clinicians and policy makers to identify and characterize patients that may be at high-risk for severe COVID-19 outcomes.Copyright © 2023

Using Real World Evidence (Rwe) to Assess Drug-Drug Interaction (Ddi) between Paxlovid and the Top 100 Prescribed Drugs in the Us

BACKGROUND: Paxlovid (nirmatrelvir/ritonavir) has received a US Emergency Use Authorization for patients >=12 years with mild-to- moderate COVID-19 at high-risk of progression to severe disease. DDI studies conducted with Paxlovid implicate the PK enhancer ritonavir as the main perpetrator of DDIs. Ritonavir is a potent inhibitor of CYP3A4, CYP2D6, and P-gp. The Paxlovid Fact Sheet1 identifies contraindicated drugs and those with a potentially important interaction. METHOD(S): A retrospective analysis was conducted using RWE from the Optum Clinformatics Data Mart. Patients were identified based on CDC criteria for high-risk COVID-19 and confirmed continuous insurance enrollment from Jan 1 to Dec 31, 2019 with >=1 prescription claim. Excluding non-drug claims (e.g., vaccines), the top 100 drugs were selected and ranked based on total patient counts. DDI potential with Paxlovid was evaluated using US Prescribing and DailyMed Information or relevant literature for each drug. RESULT(S): Of the top 100, 70 drugs are not expected to have a DDI with Paxlovid. These drugs are eliminated unchanged in urine, cleared by enzymes other than CYP3A4 or CYP2D6, are not P-gp substrates, or are cleared by multiple pathways. The remaining 30 drugs expected to have a DDI are represented in the Paxlovid Fact Sheet. The top four drug classes expected to interact with Paxlovid include corticosteroids, narcotic analgesics, anticoagulants, and statins. One drug, simvastatin, is contraindicated. The mechanism of interaction with Paxlovid, or lack thereof, will be presented in detail for each drug. CONCLUSION(S): Paxlovid DDI management is important to ensure the right patients receive this antiviral. This analysis provides an understanding of Paxlovid interactions with the top 100 drugs likely to be used in high-risk COVID-19 patients and serves as an additional DDI management resource.

Understanding the Psychosocial Burden Associated with Hospitalization Among Adults Diagnosed with COVID-19 in the United States

Background. Due to the coronavirus disease 2019 (COVID-19) pandemic in the United States (US), public health officials sought to reduce transmission. However, the psychosocial impact associated with COVID-19 has received less attention. This study describes psychosocial burden among adults diagnosed with COVID-19 and assesses the unique impact on those who had a COVID-19 hospitalization. Methods. This cross-sectional retrospective study used 2021 US National Health and Wellness Survey (NHWS;N=75,098) data. NHWS is an annual web-based selfreport survey of the US general adult population (aged >= 18 years). Results were weighted to reflect the population on age, gender, race/ethnicity, and education based on US Census. Among adults who self-reported a COVID-19 diagnosis, those with COVID-related hospitalization, emergency room (ER) visit/no hospitalization, and no hospitalization/no ER visit were descriptively compared on demographics, health characteristics, and psychosocial burden measures. Results. Almost 16 million adults had a COVID-19 diagnosis in the past year;of these, 8% had a COVID-related hospitalization, and 6% had a COVID-related ER visit/ no hospitalization. Compared to adults with no ER visit/no hospitalization or ER visit/no hospitalization, those with a hospitalization were more often male, college educated, and employed. Relative to those with no ER visit/no hospitalization, adults with a hospitalization were more often diagnosed, either pre- or post-COVID-19 diagnosis, with allergies (47% vs 38%), asthma (20% vs 11%), pain (37% vs. 25%), headache (25% vs 16%), migraine (27% vs 15%), type 2 diabetes (16% vs 10%), dry eye (25% vs 12%), and sleep apnea (15% vs 11%). Adults with a hospitalization had lower mental, physical, and general health-related quality of life, 2-3.4 times higher work/nonwork impairment, and 2 times higher positive depression screen rate than those with no ER visit/no hospitalization. Conclusion. US adults with a COVID-related hospitalization had higher psychosocial burden than those without a hospitalization on several domains. Accordingly, reducing COVID-related hospitalizations, particularly among the employed and those with comorbidities, will be vital to help mitigate this burden.

The times they are a-changin’: But how fundamentally and how rapidly? Academic library services post-pandemic

During the coronavirus pandemic, the use of online shopping has grown rapidly. In the United Kingdom, it has been estimated that the uptake has increased to a level that it would have taken up to 5 years to achieve if the pandemic had not occurred. It is thought to be unlikely that online shopping will reduce significantly post-pandemic with major consequences for physical retail provision. Will similar trends apply to academic libraries? Will the range of online services introducing lockdown be a permanent feature? Will additional online services be required? Will there be a move back to some of the more traditional face-to-face services? This chapter looks to envision academic libraries post-pandemic. The content is based on questionnaire responses from a range of academic librarians and managers, based in the United Kingdom, the Republic of Ireland, Finland, Australia, and the United States, many of whom have contributed to three recent volumes edited by the author and published by Chandos/Elsevier. © 2021 David Baker and Lucy Ellis Published by Elsevier Ltd.

Ex Vivo and In Vivo CD46 Receptor Utilization by Species D Human Adenovirus Serotype 26 (HAdV26)

Human adenovirus serotype 26 (Ad26) is used as a gene-based vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and HIV-1. However, its primary receptor portfolio remains controversial, potentially including sialic acid, coxsackie and adenovirus receptor (CAR), integrins, and CD46. We and others have shown that Ad26 can use CD46, but these observations were questioned on the basis of the inability to cocrystallize Ad26 fiber with CD46. Recent work demonstrated that Ad26 binds CD46 with its hexon protein rather than its fiber. We examined the functional consequences of Ad26 for infection in vitro and in vivo. Ectopic expression of human CD46 on Chinese hamster ovary cells increased Ad26 infection significantly. Deletion of the complement control protein domain CCP1 or CCP2 or the serine-threonine-proline (STP) region of CD46 reduced infection. Comparing wild-type and sialic acid-deficient CHO cells, we show that the usage of CD46 is independent of its sialylation status. Ad26 transduction was increased in CD46 transgenic mice after intramuscular (i.m.) injection but not after intranasal (i.n.) administration. Ad26 transduction was 10-fold lower than Ad5 transduction after intratumoral (i.t.) injection of CD46expressing tumors. Ad26 transduction of liver was 1,000-fold lower than that ofAd5 after intravenous (i.v.) injection. These data demonstrate the use of CD46 by Ad26 in certain situations but also show that the receptor has little consequence by other routes of administration. Finally, i.v. injection of high doses of Ad26 into CD46 mice induced release of liver enzymes into the bloodstream and reduced white blood cell counts but did not induce thrombocytopenia. This suggests that Ad26 virions do not induce direct clotting side effects seen during coronavirus disease 2019 (COVID-19) vaccination with this serotype of adenovirus. IMPORTANCE The human species D Ad26 is being investigated as a low-seroprevalence vector for oncolytic virotherapy and gene-based vaccination against HIV-1 and SARS-CoV-2. However, there is debate in the literature about its tropism and receptor utilization, which directly influence its efficiency for certain applications. This work was aimed at determining which receptor(s) this virus uses for infection and its role in virus biology, vaccine efficacy, and, importantly, vaccine safety.

Staying safe while waiting for the vaccine: what we need to do.

Societies are organizing themselves to keep the COVID-19 virus at bay for the foreseeable future. The World Health Organization (WHO) has proposed that every country implement a comprehensive set of measures to prevent infection, detect cases, interrupt transmission, control clusters, suppress outbreaks and reduce mortality. Throughout the world, four systems capabilities are emerging that are important for societies to get ahead of the virus and become COVID-19 ready. First: understand the pattern of infection locally and act on it effectively: assess the status of the outbreak; act rapidly and robustly to interrupt transmission. Second: enable people to be active participants in their own responses. Third: focus on the places where people are most at risk of infection. Fourth: assess the performance of responses to COVID-19 infection: detecting cases, interrupting chains of transmission, minimizing adverse consequences, protecting the most vulnerable and ensuring opportunities for sustainable livelihoods and well-being for all, leaving no-one behind. These four capabilities are being woven together within societies: successful weaving can be helped through focusing on three interlinked elements: making information available; assessing and reducing risk; and being able to suppress outbreaks rapidly. This means involving everyone in the response and having strong public health defences. Governments, authorities, public health teams, employers and community organizations make it possible for us to stay safe but, in the end, what happens is up to all of us, individually and collectively. If we are to live well with the threat of COVID-19, solidarity really does matter.