ORCID Profile
0000-0001-6888-2212
Current Organisations
University of Tokyo
,
University of Bristol
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Publisher: Cold Spring Harbor Laboratory
Date: 04-12-2020
DOI: 10.1101/2020.12.03.20243535
Abstract: Early in the COVID-19 pandemic the NHS recommended that appropriate patients anticoagulated with warfarin should be switched to direct acting oral anticoagulants (DOACs), requiring less frequent blood testing. Subsequently, a national safety alert was issued regarding patients being inappropriately co-prescribed two anticoagulants following a medication change, and associated monitoring. To describe which people were switched from warfarin to DOACs identify potentially unsafe co-prescribing of anticoagulants and assess whether abnormal clotting results have become more frequent during the pandemic. Working on behalf of NHS England we conducted a population cohort based study using routine clinical data from million adults in England. 20,000 of 164,000 warfarin patients (12.2%) switched to DOACs between March and May 2020, most commonly to edoxaban and apixaban. Factors associated with switching included: older age, recent renal function test, higher number of recent INR tests recorded, atrial fibrillation diagnosis and care home residency. There was a sharp rise in co-prescribing of warfarin and DOACs from typically 50-100 per month to 246 in April 2020, 0.06% of all people receiving a DOAC or warfarin. INR testing fell by 14% to 506.8 patients tested per 1000 warfarin patients each month. We observed a very small increase in elevated INRs (n=470) during April compared with January (n=420). Increased switching of anticoagulants from warfarin to DOACs was observed at the outset of the COVID-19 pandemic in England following national guidance. There was a small but substantial number of people co-prescribed warfarin and DOACs during this period. Despite a national safety alert on the issue, a widespread rise in elevated INR test results was not found. Primary care has responded rapidly to changes in patient care during the COVID-19 pandemic.
Publisher: OpenSAFELY
Date: 2021
Abstract: This OpenSAFELY report is a routine update of our peer-review paper published in the British Journal of General Practice on the Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY. It is a routine update of the analysis described in the paper. The data requires careful interpretation and there are a number of caveats. Please read the full detail about our methods and discussionis and the full analytical methods on this routine report are available on GitHub. OpenSAFELY is a new secure analytics platform for electronic patient records built on behalf of NHS England to deliver urgent academic and operational research during the pandemic. You can read more about OpenSAFELY on our website.
Publisher: BMJ
Date: 20-07-2022
Abstract: To compare the effectiveness of the BNT162b2 mRNA (Pfizer-BioNTech) and the ChAdOx1 (Oxford-AstraZeneca) covid-19 vaccines against infection and covid-19 disease in health and social care workers. Cohort study, emulating a comparative effectiveness trial, on behalf of NHS England. Linked primary care, hospital, and covid-19 surveillance records available within the OpenSAFELY-TPP research platform, covering a period when the SARS-CoV-2 Alpha variant was dominant. 317 341 health and social care workers vaccinated between 4 January and 28 February 2021, registered with a general practice using the TPP SystmOne clinical information system in England, and not clinically extremely vulnerable. Vaccination with either BNT162b2 or ChAdOx1 administered as part of the national covid-19 vaccine roll-out. Recorded SARS-CoV-2 positive test, or covid-19 related attendance at an accident and emergency (A& E) department or hospital admission occurring within 20 weeks of receipt of the first vaccine dose. Over the duration of 118 771 person-years of follow-up there were 6962 positive SARS-CoV-2 tests, 282 covid-19 related A& E attendances, and 166 covid-19 related hospital admissions. The cumulative incidence of each outcome was similar for both vaccines during the first 20 weeks after vaccination. The cumulative incidence of recorded SARS-CoV-2 infection 20 weeks after first-dose vaccination with BNT162b2 was 21.7 per 1000 people (95% confidence interval 20.9 to 22.4) and with ChAdOx1 was 23.7 (21.8 to 25.6), representing a difference of 2.04 per 1000 people (0.04 to 4.04). The difference in the cumulative incidence per 1000 people of covid-19 related A& E attendance at 20 weeks was 0.06 per 1000 people (95% CI −0.31 to 0.43). For covid-19 related hospital admission, this difference was 0.11 per 1000 people (−0.22 to 0.44). In this cohort of healthcare workers where we would not anticipate vaccine type to be related to health status, we found no substantial differences in the incidence of SARS-CoV-2 infection or covid-19 disease up to 20 weeks after vaccination. Incidence dropped sharply at 3-4 weeks after vaccination, and there were few covid-19 related hospital attendance and admission events after this period. This is in line with expected onset of vaccine induced immunity and suggests strong protection against Alpha variant covid-19 disease for both vaccines in this relatively young and healthy population of healthcare workers.
Publisher: F1000 Research Ltd
Date: 27-04-2021
DOI: 10.12688/WELLCOMEOPENRES.16737.1
Abstract: Background: Care home residents have been severely affected by the COVID-19 pandemic. Electronic Health Records (EHR) hold significant potential for studying the healthcare needs of this vulnerable population however, identifying care home residents in EHR is not straightforward. We describe and compare three different methods for identifying care home residents in the newly created OpenSAFELY-TPP data analytics platform. Methods: Working on behalf of NHS England, we identified in iduals aged 65 years or older potentially living in a care home on the 1st of February 2020 using (1) a complex address linkage, in which cleaned GP registered addresses were matched to old age care home addresses using data from the Care and Quality Commission (CQC) (2) coded events in the EHR (3) household identifiers, age and household size to identify households with more than 3 in iduals aged 65 years or older as potential care home residents. Raw addresses were not available to the investigators. Results: Of 4,437,286 in iduals aged 65 years or older, 2.27% were identified as potential care home residents using the complex address linkage, 1.96% using coded events, 3.13% using household size and age and 3.74% using either of these methods. 53,210 in iduals (32.0% of all potential care home residents) were classified as care home residents using all three methods. Address linkage had the largest overlap with the other methods 93.3% of in iduals identified as care home residents using the address linkage were also identified as such using either coded events or household age and size. Conclusion: We have described the partial overlap between three methods for identifying care home residents in EHR, and provide detailed instructions for how to implement these in OpenSAFELY-TPP to support research into the impact of the COVID-19 pandemic on care home residents.
Publisher: Cold Spring Harbor Laboratory
Date: 03-2021
DOI: 10.1101/2021.02.25.21252433
Abstract: To compare approaches for obtaining relative and absolute estimates of risk of 28-day COVID-19 mortality for adults in the general population of England in the context of changing levels of circulating infection. Three designs were compared. (A) case-cohort which does not explicitly account for the time-changing prevalence of COVID-19 infection, (B) 28-day landmarking, a series of sequential overlapping sub-studies incorporating time-updating proxy measures of the prevalence of infection, and (C) daily landmarking. Regression models were fitted to predict 28-day COVID-19 mortality. Working on behalf of NHS England, we used clinical data from adult patients from all regions of England held in the TPP SystmOne electronic health record system, linked to Office for National Statistics (ONS) mortality data, using the OpenSAFELY platform. Eligible participants were adults aged 18 or over, registered at a general practice using TPP software on 1 st March 2020 with recorded sex, postcode and ethnicity. 11,972,947 in iduals were included, and 7,999 participants experienced a COVID-19 related death. The study period lasted 100 days, ending 8 th June 2020. A range of demographic characteristics and comorbidities were used as potential predictors. Local infection prevalence was estimated with three proxies: modelled based on local prevalence and other key factors rate of A& E COVID-19 related attendances and rate of suspected COVID-19 cases in primary care. COVID-19 related death. All models discriminated well between patients who did and did not experience COVID-19 related death, with C-statistics ranging from 0.92-0.94. Accurate estimates of absolute risk required data on local infection prevalence, with modelled estimates providing the best performance. Reliable estimates of absolute risk need to incorporate changing local prevalence of infection. Simple models can provide very good discrimination and may simplify implementation of risk prediction tools in practice.
Publisher: Cold Spring Harbor Laboratory
Date: 18-10-2021
DOI: 10.1101/2021.10.13.21264937
Abstract: To compare the effectiveness of the BNT162b2 mRNA (Pfizer-BioNTech) and the ChAdOx1 (Oxford-AstraZeneca) COVID-19 vaccines against infection and COVID-19 disease in health and social care workers. Cohort study, emulating a comparative effectiveness trial. Linked primary care, hospital, and COVID-19 surveillance records available within the OpenSAFELY-TPP research platform. 317,341 health and social care workers vaccinated between 4 January and 28 February 2021, registered with a GP practice using the TPP SystmOne clinical information system in England, and not clinically extremely vulnerable. Vaccination with either BNT162b2 or ChAdOx1 administered as part of the national COVID-19 vaccine roll-out. Recorded SARS-CoV-2 positive test, or COVID-19 related Accident and Emergency attendance or hospital admission occurring within 20 weeks of vaccination. The cumulative incidence of each outcome was similar for both vaccines during the first 20 weeks post-vaccination. The cumulative incidence of recorded SARS-CoV-2 infection 6 weeks after vaccination with BNT162b2 was 19.2 per 1000 people (95%CI 18.6 to 19.7) and with ChAdOx1 was 18.9 (95%CI 17.6 to 20.3), representing a difference of -0.24 per 1000 people (95%CI -1.71 to 1.22). The difference in the cumulative incidence per 1000 people of COVID-19 accident and emergency attendance at 6 weeks was 0.01 per 1000 people (95%CI -0.27 to 0.28). For COVID-19 hospital admission, this difference was 0.03 per 1000 people (95%CI -0.22 to 0.27). In this cohort of healthcare workers where we would not anticipate vaccine type to be related to health status, we found no substantial differences in the incidence of SARS-CoV-2 infection or COVID-19 disease up to 20 weeks after vaccination. Incidence dropped sharply after 3-4 weeks and there were very few COVID-19 hospital attendance and admission events after this period. This is in line with expected onset of vaccine-induced immunity, and suggests strong protection against COVID-19 disease for both vaccines.
Publisher: Cold Spring Harbor Laboratory
Date: 08-11-2021
DOI: 10.1101/2021.11.08.21265380
Abstract: While the vaccines against COVID-19 are considered to be highly effective, COVID-19 vaccine breakthrough is likely and a small number of people will still fall ill, be hospitalised, or die from COVID-19, despite being fully vaccinated. With the continued increase in numbers of positive SARS-CoV-2 tests, describing the characters of in iduals who have experienced a COVID-19 vaccine breakthrough could be hugely important in helping to determine who may be at greatest risk. With the approval of NHS England we conducted a retrospective cohort study using routine clinical data from the OpenSAFELY TPP database of fully vaccinated in iduals, linked to secondary care and death registry data, and described the characteristics of those experiencing a COVID-19 vaccine breakthrough. As of 01 st November 2021, a total of 15,436,455 in iduals were identified as being fully vaccinated against COVID-19, with a median follow-up time of 149 days (IQR: 107-179). From within this population, a total of 577245 ( %) in iduals reported a positive SARS-CoV-2 test. For every 1000 years of patient follow-up time, the corresponding incidence rate was 98.02 (95% CI 97.9-98.15). There were 16,120 COVID-19-related hospital admissions, 1,100 COVID-19 critical care admission patients and 3,925 COVID-19-related deaths corresponding incidence rates of 2.72 (95% C 2.7-2.74), 0.19 (95% C 0.18-0.19) and 0.66 (95% C 0.65-0.67), respectively. When broken down by the initial priority group, higher rates of hospitalisation and death were seen in those in care homes and those over 80 years of age. Comorbidities with the highest rates of breakthrough COVID-19 included chronic kidney disease, dialysis, transplant, haematological malignancy, and immunocompromised. The majority of COVID-19 vaccine breakthrough cases in England were mild with relatively few fully vaccinated in iduals being hospitalised or dying as a result. However, some concerning differences in rates of breakthrough cases were identified in several clinical and demographic groups. While it is important to note that these findings are simply descriptive and cannot be used to answer why certain groups have higher rates of COVID-19 breakthrough than others, the emergence of the Omicron variant of COVID-19 coupled with the continued increase in numbers of positive SARS-CoV-2 tests are concerning. As numbers of fully vaccinated in iduals increases and follow-up time lengthens, so too will the number of COVID-19 breakthrough cases. Additional analyses, aimed at identifying in iduals at higher risk, are therefore required.
Publisher: Oxford University Press (OUP)
Date: 25-05-2021
Abstract: Deprescribing may benefit older frail patients experiencing polypharmacy. We investigated the scope for deprescribing in acutely hospitalised patients and the long-term implications of continuation of medications that could potentially be deprescribed. Acutely hospitalised patients (n = 170) discharged to Residential Aged Care Facilities, ≥75 years and receiving ≥5 regular medications were assessed during admission to determine eligibility for deprescribing of key drug classes, along with the actual incidence of deprescribing. The impact of continuation of nominated drug classes (anticoagulants, antidiabetics, antiplatelets, antipsychotics, benzodiazepines, proton pump inhibitors (PPIs), statins) on a combined endpoint (death/readmission) was determined. Hyperpolypharmacy (& regular medications) was common (49.4%) at admission. Varying rates of deprescribing occurred during hospitalisation for the nominated drug classes (8–53%), with considerable potential for further deprescribing (34–90%). PPI use was prevalent (56%) and 89.5% of these had no clear indication. Of the drug classes studied, only continued PPI use at discharge was associated with increased mortality/readmission at 1 year (hazard ratio 1.54, 95% confidence interval (1.06–2.26), P = 0.025), driven largely by readmission. There is considerable scope for acute hospitalisation to act as a triage point for deprescribing in older patients. PPIs in particular appeared overprescribed in this susceptible patient group, and this was associated with earlier readmission. Polypharmacy in older hospitalised patients should be targeted for possible deprescribing during hospitalisation, especially PPIs.
Publisher: F1000 Research Ltd
Date: 15-10-2020
DOI: 10.12688/WELLCOMEOPENRES.16353.1
Abstract: On March 11th 2020, the World Health Organization characterised COVID-19 as a pandemic. Responses to containing the spread of the virus have relied heavily on policies involving restricting contact between people. Evolving policies regarding shielding and in idual choices about restricting social contact will rely heavily on perceived risk of poor outcomes from COVID-19. In order to make informed decisions, both in idual and collective, good predictive models are required. For outcomes related to an infectious disease, the performance of any risk prediction model will depend heavily on the underlying prevalence of infection in the population of interest. Incorporating measures of how this changes over time may result in important improvements in prediction model performance. This protocol reports details of a planned study to explore the extent to which incorporating time-varying measures of infection burden over time improves the quality of risk prediction models for COVID-19 death in a large population of adult patients in England. To achieve this aim, we will compare the performance of different modelling approaches to risk prediction, including static cohort approaches typically used in chronic disease settings and landmarking approaches incorporating time-varying measures of infection prevalence and policy change, using COVID-19 related deaths data linked to longitudinal primary care electronic health records data within the OpenSAFELY secure analytics platform.
Publisher: Springer Science and Business Media LLC
Date: 08-07-2020
Publisher: Springer Science and Business Media LLC
Date: 02-03-2023
Publisher: Cold Spring Harbor Laboratory
Date: 14-08-2020
DOI: 10.1101/2020.08.12.20171405
Abstract: There has been speculation that non-steroidal anti-inflammatory drugs (NSAIDs) may negatively affect coronavirus disease 2019 (COVID-19) outcomes, yet clinical evidence is limited. To assess the association between NSAID use and deaths from COVID-19 using OpenSAFELY, a secure analytical platform. Two cohort studies (1 st March-14 th June 2020). Working on behalf of NHS England, we used routine clinical data from million patients in England linked to death data from the Office for National Statistics. Study 1: General population (people with an NSAID prescription in the last three years). Study 2: people with rheumatoid arthritis/osteoarthritis. Current NSAID prescription within the 4 months before 1 st March 2020. We used Cox regression to estimate hazard ratios (HRs) for COVID-19 related death in people currently prescribed NSAIDs, compared with those not currently prescribed NSAIDs, adjusting for age, sex, comorbidities and other medications. In Study 1, we included 535,519 current NSAID users and 1,924,095 non-users in the general population. The crude HR for current use was 1.25 (95% CI, 1.07–1.46), versus non-use. We observed no evidence of difference in risk of COVID-19 related death associated with current use (HR, 0.95, 95% CI, 0.80–1.13) in the fully adjusted model. In Study 2, we included 1,711,052 people with rheumatoid arthritis/osteoarthritis, of whom 175,631 (10%) were current NSAID users. The crude HR for current use was 0.43 (95% CI, 0.36–0.52), versus non-use. In the fully adjusted model, we observed a lower risk of COVID-19 related death (HR, 0.78, 95% CI, 0.65–0.94) associated with current use of NSAID versus non-use. We found no evidence of a harmful effect of NSAIDs on COVID-19 related deaths. Risks of COVID-19 do not need to influence decisions about therapeutic use of NSAIDs.
Publisher: Cold Spring Harbor Laboratory
Date: 08-07-2021
DOI: 10.1101/2021.07.07.21253295
Abstract: Residents in care homes have been severely impacted by the COVID-19 pandemic. We describe trends in risk of mortality among care home residents compared to residents in private homes in England. On behalf of NHS England, we used OpenSAFELY-TPP, an analytics platform running across the linked electronic health records of approximately a third of the English population, to calculate monthly age-standardised risks of death due to all causes and COVID-19 among adults aged =65 years between 1/2/2019 and 31/03/2021. Care home residents were identified using linkage to the Care and Quality Commission. We included 4,329,078 people aged 65 years or older on the 1st of February 2019, 2.2% of whom were classified as residing in a care or nursing home. Age-standardised mortality risks were approximately 10 times higher among care home residents compared to non-residents in February 2019 residents (CMF = 10.59, 95%CI = 9.51, 11.81 among women, CMF = 10.82, 95%CI = 9.89, 11.84 among men). This increased to more than 17 times in April 2020 (CMF = 17.52, 95%CI = 16.38, 18.74 among women, CMF = 18.12, 95%CI = 17.17 – 19.12 among men) before returning to pre-pandemic levels in June 2020. CMFs did not increase during the second wave, despite a rise in the absolute age-standardised COVID-19 mortality risks. The first COVID-19 wave had a disproportionate impact on care home residents in England compared to older private home residents. A degree of immunity, improved protective measures or changes in the underlying frailty of the populations may explain the lack of an increase in the relative mortality risks during the second wave. The care home population should be prioritised for measures aimed at controlling the spread of COVID-19. Medical Research Council MR/V015737/1
Publisher: Cold Spring Harbor Laboratory
Date: 23-09-2020
DOI: 10.1101/2020.09.22.20198754
Abstract: COVID-19 has had a disproportionate impact on ethnic minority populations, both in the UK and internationally. To date, much of the evidence has been derived from studies within single healthcare settings, mainly those hospitalised with COVID-19. Working on behalf of NHS England, the aim of this study was to identify ethnic differences in the risk of COVID-19 infection, hospitalisation and mortality using a large general population cohort in England. We conducted an observational cohort study using linked primary care records of 17.5 million adults between 1 February 2020 and 3 August 2020. Exposure was self-reported ethnicity collapsed into the 5 and 16 ethnicity categories of the English Census. Multivariable Cox proportional hazards regression was used to identify ethnic differences in the risk of being tested and testing positive for SARS-CoV-2 infection, COVID-19 related intensive care unit (ICU) admission, and COVID-19 mortality, adjusted for socio-demographic factors, clinical co-morbidities, geographic region, care home residency, and household size. A total of 17,510,002 adults were included in the study 63% white (n=11,030,673), 6% south Asian (n=1,034,337), 2% black (n=344,889), 2% other (n=324,730), 1% mixed (n=172,551), and 26% unknown (n=4,602,822). After adjusting for measured explanatory factors, south Asian, black, and mixed groups were marginally more likely to be tested (south Asian HR 1.08, 95%CI 1.07-1.09 black HR 1.08 95%CI 1.06-1.09, mixed HR 1.03, 95%CI 1.01-1.05), and substantially more likely to test positive for SARS-CoV-2 compared with white adults (south Asian HR 2.02. 95% CI 1.97-2.07 black HR 1.68, 95%CI 1.61-1.76 mixed HR 1.46, 95%CI 1.36-1.56). The risk of being admitted to ICU for COVID-19 was substantially increased in all ethnic minority groups compared with white adults (south Asian HR 2.22, 95%CI 1.96-2.52 black HR 3.07, 95%CI 2.61-3.61 mixed HR 2.86, 95%CI 2.19-3.75, other HR 2.86, 95%CI 2.31-3.63). Risk of COVID-19 mortality was increased by 25-56% in ethnic minority groups compared with white adults (south Asian HR 1.27, 95%CI 1.17-1.38 black HR 1.55, 95%CI 1.38-1.75 mixed HR 1.40, 95%CI 1.12-1.76 other HR 1.25, 95%CI 1.05-1.49). We observed heterogeneity of associations after disaggregation into detailed ethnic groupings Indian and African groups were at higher risk of all outcomes Pakistani, Bangladeshi and Caribbean groups were less or equally likely to be tested for SARS-CoV-2, but at higher risk of all other outcomes, Chinese groups were less likely to be tested for and test positive for SARS-CoV-2, more likely to be admitted to ICU, and equally likely to die from COVID-19. We found evidence of substantial ethnic inequalities in the risk of testing positive for SARS-CoV-2, ICU admission, and mortality, which persisted after accounting for explanatory factors, including household size. It is likely that some of this excess risk is related to factors not captured in clinical records such as occupation, experiences of structural discrimination, or inequitable access to health and social services. Prioritizing linkage between health, social care, and employment data and engaging with ethnic minority communities to better understand their lived experiences is essential for generating evidence to prevent further widening of inequalities in a timely and actionable manner.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Harriet Forbes.