Data-Resource Profile: United Kingdom Optimum Patient Care Research Database.

Introduction: Electronic medical records (EMRs) maintained in primary care in the UK and collected and stored in EMR databases offer a world-leading resource for observational clinical research. We aimed to profile one such database: the Optimum Patient Care Research Database (OPCRD). Methods and Participants: The OPCRD, incepted in 2010, is a growing primary care EMR database collecting data from 992 general practices within the UK. It covers over 16.6 million patients across all four countries within the UK, and is broadly representative of the UK population in terms of age, sex, ethnicity and socio-economic status. Patients have a mean duration of 11.7 years' follow-up (SD 17.50), with a majority having key summary data from birth to last data entry. Data for the OPCRD are collected incrementally monthly and extracted from all of the major clinical software systems used within the UK and across all four coding systems (Read version 2, Read CTV3, SNOMED DM+D and SNOMED CT codes). Via quality-improvement programmes provided to GP surgeries, the OPCRD also includes patient-reported outcomes from a range of disease-specific validated questionnaires, with over 66,000 patient responses on asthma, COPD, and COVID-19. Further, bespoke data collection is possible by working with GPs to collect new research via patient-reported questionnaires. Findings to Date: The OPCRD has contributed to over 96 peer-reviewed research publications since its inception encompassing a broad range of medical conditions, including COVID-19. Conclusion: The OPCRD represents a unique resource with great potential to support epidemiological research, from retrospective observational studies through to embedded cluster-randomised trials. Advantages of the OPCRD over other EMR databases are its large size, UK-wide geographical coverage, the availability of up-to-date patient data from all major GP software systems, and the unique collection of patient-reported information on respiratory health.

Supporting syringe services programs in the initiation and scale-up of vaccine administration: findings from in-depth interviews.

BACKGROUND: Vaccine-hesitant persons who inject drugs are at increased risk for several vaccine-preventable diseases. However, vaccination rates among this population remain low. While syringe services programs (SSPs) are places where persons who inject drugs feel comfortable accessing services, few offer vaccination services. This study describes facilitators and barriers to vaccination at SSPs. METHODS: We used convenience sampling to conduct semi-structured, qualitative in-depth interviews with 21 SSPs in the USA from June to August 2021. Interview questions asked SSPs about their perceptions, priorities, barriers, facilitators, and the effects of partnerships and policies on vaccine administration. We used deductive thematic analysis to identify the main themes. RESULTS: Eight (n = 8) SSPs offered vaccinations, and thirteen (n = 13) did not offer vaccinations. Most SSPs believed offering vaccination services was important, although addressing SSP participants' immediate needs often took precedence. Staffing, physical space, and logistical issues were the most common barriers to vaccine administration reported by SSPs, followed by SSP participant-related barriers. Facilitators of vaccine administration included access to a tracking system, partnering with agencies or other organizations providing vaccines, and having a licensed vaccination provider on-site. Partnerships provided SSPs opportunities to expand capacity but could also restrict how SSPs operate. Recommended policy changes to facilitate vaccine administration included subsidizing the cost of vaccinations and addressing restrictions around who could administer vaccinations. CONCLUSIONS: Increasing the availability of vaccination services at SSPs requires addressing the varying capacity needs of SSPs, such as tracking systems, licensed vaccinators, and free or low-cost vaccination supplies. While these needs can be met through partnerships and supportive policies, both must consider and reflect cultural competence around the lived experiences of persons who inject drugs.

Vaccination barriers and opportunities at syringe services programs in the United States, June-August 2021-A cross-sectional survey.

BACKGROUND: Syringe services programs (SSPs) are an important venue for reaching people who inject drugs (PWID) to offer preventive services; however, not all SSPs offer vaccinations. We aimed to describe barriers and opportunities for SSPs to offer vaccinations. METHODS: During June-August 2021, we conducted a descriptive, cross-sectional survey of SSP providers in the United States. SSPs were recruited from national listservs using purposive sampling to ensure geographic diversity. The survey included questions about SSP characteristics, client demographics, existing vaccination resources, resource needs, and staff perspectives on client vaccination barriers. Statistical comparisons were made using Pearson's chi-square test. RESULTS: In total, 105 SSPs from 34 states responded to the survey; 46 SSPs (43.8%) offered on-site vaccinations. SSPs without on-site vaccinations were more likely operated by community-based organizations (81.4% vs 30.4%, p < 0.001) in urban areas (71.4% vs 40.0%, p = 0.002) than SSPs offering on-site vaccinations. The most common staffing need was for personnel licensed to administer vaccines (74/98, 75.5%). Over half of SSPs reported vaccine supply, administration supplies, storage equipment, and systems to follow-up clients for multidose series as important resource needs. The most common resource need was for reminder/recall systems for vaccines with multidose series (75/92, 81.5%). Vaccine safety concerns (92/95, 96.8%) and competing priorities (92/96, 95.8%) were the most common staff-reported client barriers to vaccinations. CONCLUSIONS: Addressing missed opportunities for offering vaccinations to PWID who use SSPs will require increased numbers of on-site personnel licensed to administer vaccines and additional training, vaccination supplies, and storage and handling equipment.

Characteristics of patients in platform C19, a COVID-19 research database combining primary care electronic health record and patient reported information.

BACKGROUND: Data to better understand and manage the COVID-19 pandemic is urgently needed. However, there are gaps in information stored within even the best routinely-collected electronic health records (EHR) including test results, remote consultations for suspected COVID-19, shielding, physical activity, mental health, and undiagnosed or untested COVID-19 patients. Observational and Pragmatic Research Institute (OPRI) Singapore and Optimum Patient Care (OPC) UK established Platform C19, a research database combining EHR data and bespoke patient questionnaire. We describe the demographics, clinical characteristics, patient behavior, and impact of the COVID-19 pandemic using data within Platform C19. METHODS: EHR data from Platform C19 were extracted from 14 practices across UK participating in the OPC COVID-19 Quality Improvement program on a continuous, monthly basis. Starting 7th August 2020, consenting patients aged 18-85 years were invited in waves to fill an online questionnaire. Descriptive statistics were summarized using all data available up to 22nd January 2021. FINDINGS: From 129,978 invitees, 31,033 responded. Respondents were predominantly female (59.6%), white (93.5%), and current or ex-smokers (52.6%). Testing for COVID-19 was received by 23.8% of respondents, of which 7.9% received positive results. COVID-19 symptoms lasted ≥4 weeks in 19.5% of COVID-19 positive respondents. Up to 39% respondents reported a negative impact on questions regarding their mental health. Most (67%-76%) respondents with asthma, Chronic Obstructive Pulmonary Disease (COPD), diabetes, heart, or kidney disease reported no change in the condition of their diseases. INTERPRETATION: Platform C19 will enable research on key questions relating to COVID-19 pandemic not possible using EHR data alone.

Risk Predictors and Symptom Features of Long COVID Within a Broad Primary Care Patient Population Including Both Tested and Untested Patients.

INTRODUCTION: Symptoms may persist after the initial phases of COVID-19 infection, a phenomenon termed long COVID. Current knowledge on long COVID has been mostly derived from test-confirmed and hospitalized COVID-19 patients. Data are required on the burden and predictors of long COVID in a broader patient group, which includes both tested and untested COVID-19 patients in primary care. METHODS: This is an observational study using data from Platform C19, a quality improvement program-derived research database linking primary care electronic health record data (EHR) with patient-reported questionnaire information. Participating general practices invited consenting patients aged 18-85 to complete an online questionnaire since 7th August 2020. COVID-19 self-diagnosis, clinician-diagnosis, testing, and the presence and duration of symptoms were assessed via the questionnaire. Patients were considered present with long COVID if they reported symptoms lasting ≥4 weeks. EHR and questionnaire data up till 22nd January 2021 were extracted for analysis. Multivariable regression analyses were conducted comparing demographics, clinical characteristics, and presence of symptoms between patients with long COVID and patients with shorter symptom duration. RESULTS: Long COVID was present in 310/3151 (9.8%) patients with self-diagnosed, clinician-diagnosed, or test-confirmed COVID-19. Only 106/310 (34.2%) long COVID patients had test-confirmed COVID-19. Risk predictors of long COVID were age ≥40 years (adjusted Odds Ratio [AdjOR]=1.49 [1.05-2.17]), female sex (adjOR=1.37 [1.02-1.85]), frailty (adjOR=2.39 [1.29-4.27]), visit to A&E (adjOR=4.28 [2.31-7.78]), and hospital admission for COVID-19 symptoms (adjOR=3.22 [1.77-5.79]). Aches and pain (adjOR=1.70 [1.21-2.39]), appetite loss (adjOR=3.15 [1.78-5.92]), confusion and disorientation (adjOR=2.17 [1.57-2.99]), diarrhea (adjOR=1.4 [1.03-1.89]), and persistent dry cough (adjOR=2.77 [1.94-3.98]) were symptom features statistically more common in long COVID. CONCLUSION: This study reports the factors and symptom features predicting long COVID in a broad primary care population, including both test-confirmed and the previously missed group of COVID-19 patients.

Identifying SARS-CoV-2 antiviral compounds by screening for small molecule inhibitors of nsp14/nsp10 exoribonuclease.

SARS-CoV-2 is a coronavirus that emerged in 2019 and rapidly spread across the world causing a deadly pandemic with tremendous social and economic costs. Healthcare systems worldwide are under great pressure, and there is an urgent need for effective antiviral treatments. The only currently approved antiviral treatment for COVID-19 is remdesivir, an inhibitor of viral genome replication. SARS-CoV-2 proliferation relies on the enzymatic activities of the non-structural proteins (nsp), which makes them interesting targets for the development of new antiviral treatments. With the aim to identify novel SARS-CoV-2 antivirals, we have purified the exoribonuclease/methyltransferase (nsp14) and its cofactor (nsp10) and developed biochemical assays compatible with high-throughput approaches to screen for exoribonuclease inhibitors. We have screened a library of over 5000 commercial compounds and identified patulin and aurintricarboxylic acid (ATA) as inhibitors of nsp14 exoribonuclease in vitro. We found that patulin and ATA inhibit replication of SARS-CoV-2 in a VERO E6 cell-culture model. These two new antiviral compounds will be valuable tools for further coronavirus research as well as potentially contributing to new therapeutic opportunities for COVID-19.

Identifying SARS-CoV-2 antiviral compounds by screening for small molecule inhibitors of Nsp14 RNA cap methyltransferase.

The COVID-19 pandemic has presented itself as one of the most critical public health challenges of the century, with SARS-CoV-2 being the third member of the Coronaviridae family to cause a fatal disease in humans. There is currently only one antiviral compound, remdesivir, that can be used for the treatment of COVID-19. To identify additional potential therapeutics, we investigated the enzymatic proteins encoded in the SARS-CoV-2 genome. In this study, we focussed on the viral RNA cap methyltransferases, which play key roles in enabling viral protein translation and facilitating viral escape from the immune system. We expressed and purified both the guanine-N7 methyltransferase nsp14, and the nsp16 2'-O-methyltransferase with its activating cofactor, nsp10. We performed an in vitro high-throughput screen for inhibitors of nsp14 using a custom compound library of over 5000 pharmaceutical compounds that have previously been characterised in either clinical or basic research. We identified four compounds as potential inhibitors of nsp14, all of which also showed antiviral capacity in a cell-based model of SARS-CoV-2 infection. Three of the four compounds also exhibited synergistic effects on viral replication with remdesivir.

Hospitalization and mortality associated with SARS-CoV-2 viral clades in COVID-19.

The COVID-19 epidemic of 2019-20 is due to the novel coronavirus SARS-CoV-2. Following first case description in December, 2019 this virus has infected over 10 million individuals and resulted in at least 500,000 deaths world-wide. The virus is undergoing rapid mutation, with two major clades of sequence variants emerging. This study sought to determine whether SARS-CoV-2 sequence variants are associated with differing outcomes among COVID-19 patients in a single medical system. Whole genome SARS-CoV-2 RNA sequence was obtained from isolates collected from patients registered in the University of Washington Medicine health system between March 1 and April 15, 2020. Demographic and baseline clinical characteristics of patients and their outcome data including their hospitalization and death were collected. Statistical and machine learning models were applied to determine if viral genetic variants were associated with specific outcomes of hospitalization or death. Full length SARS-CoV-2 sequence was obtained 190 subjects with clinical outcome data. 35 (18.4%) were hospitalized and 14 (7.4%) died from complications of infection. A total of 289 single nucleotide variants were identified. Clustering methods demonstrated two major viral clades, which could be readily distinguished by 12 polymorphisms in 5 genes. A trend toward higher rates of hospitalization of patients with Clade 2 infections was observed (p = 0.06, Fisher's exact). Machine learning models utilizing patient demographics and co-morbidities achieved area-under-the-curve (AUC) values of 0.93 for predicting hospitalization. Addition of viral clade or sequence information did not significantly improve models for outcome prediction. In summary, SARS-CoV-2 shows substantial sequence diversity in a community-based sample. Two dominant clades of virus are in circulation. Among patients sufficiently ill to warrant testing for virus, no significant difference in outcomes of hospitalization or death could be discerned between clades in this sample. Major risk factors for hospitalization and death for either major clade of virus include patient age and comorbid conditions.

Outcomes associated with SARS-CoV-2 viral clades in COVID-19.

Background The COVID-19 epidemic of 2019-20 is due to the novel coronavirus SARS-CoV-2. Following first case description in December, 2019 this virus has infected over 10 million individuals and resulted in at least 500,000 deaths world-wide. The virus is undergoing rapid mutation, with two major clades of sequence variants emerging. This study sought to determine whether SARS-CoV-2 sequence variants are associated with differing outcomes among COVID-19 patients in a single medical system. Methods Whole genome SARS-CoV-2 RNA sequence was obtained from isolates collected from patients registered in the University of Washington Medicine health system between March 1 and April 15, 2020. Demographic and baseline medical data along with outcomes of hospitalization and death were collected. Statistical and machine learning models were applied to determine if viral genetic variants were associated with specific outcomes of hospitalization or death. Findings Full length SARS-CoV-2 sequence was obtained 190 subjects with clinical outcome data. 35 (18.4%) were hospitalized and 14 (7.4%) died from complications of infection. A total of 289 single nucleotide variants were identified. Clustering methods demonstrated two major viral clades, which could be readily distinguished by 12 polymorphisms in 5 genes. A trend toward higher rates of hospitalization of patients with Clade 2 was observed (p=0.06). Machine learning models utilizing patient demographics and co-morbidities achieved area-under-the-curve (AUC) values of 0.93 for predicting hospitalization. Addition of viral clade or sequence information did not significantly improve models for outcome prediction. Conclusion SARS-CoV-2 shows substantial sequence diversity in a community-based sample. Two dominant clades of virus are in circulation. Among patients sufficiently ill to warrant testing for virus, no significant difference in outcomes of hospitalization or death could be discerned between clades in this sample. Major risk factors for hospitalization and death for either major clade of virus include patient age and comorbid conditions.