Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 5 de 5
Filtrar
Mais filtros










Base de dados
Intervalo de ano de publicação
1.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22283458

RESUMO

BackgroundThe COVID-19 pandemic and associated national lockdowns created unprecedented disruption to healthcare, with reduced access to services and planned clinical encounters postponed or cancelled. It was widely anticipated that failure to obtain timely treatment would cause progression of illness and increased hospital admissions. Additional concerns were that social and spatial inequalities would widen given the disproportionate impacts of COVID-19 directly. The aim of our study is to determine whether this was observable in England. MethodsWith the approval of NHS England we utilised individual-level electronic health records from OpenSAFELY, which covered [~]40% of general practices in England (mean monthly population size 23.5 million people). We estimated crude and directly age-standardised rates for potentially preventable unplanned hospital admissions: ambulatory care sensitive conditions and urgent emergency sensitive conditions. We considered how trends in these outcomes varied by three measures of social and spatial inequality: neighbourhood socioeconomic deprivation, ethnicity, and geographical region. FindingsThere were large declines in avoidable hospitalisations during the first national lockdown, which then reversed post-lockdown albeit never reaching pre-pandemic levels. While trends were consistent by each measure of inequality, absolute levels of inequalities narrowed throughout 2020 (especially during the first national lockdown) and remained lower than pre-pandemic trends. While the scale of inequalities remained similar into 2021 for deprivation and ethnicity, we found evidence of widening absolute and relative inequalities by geographic region in 2021 and 2022. InterpretationThe anticipation that healthcare disruption from the COVID-19 pandemic and lockdowns would result in more (avoidable) hospitalisations and widening social inequalities was wrong. However, the recent growing gap between geographic regions suggests that the effects of the pandemic has reinforced spatial inequalities.

2.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22272804

RESUMO

BackgroundThe rate at which COVID-19 vaccine effectiveness wanes over time is crucial for vaccination policies, but is incompletely understood with conflicting results from different studies. MethodsThis cohort study, using the OpenSAFELY-TPP database and approved by NHS England, included individuals without prior SARS-CoV-2 infection assigned to vaccines priority groups 2-12 defined by the UK Joint Committee on Vaccination and Immunisation. We compared individuals who had received two doses of BNT162b2 or ChAdOx1 with unvaccinated individuals during six 4-week comparison periods, separately for subgroups aged 65+ years; 16-64 years and clinically vulnerable; 40-64 years and 18-39 years. We used Cox regression, stratified by first dose eligibility and geographical region and controlled for calendar time, to estimate adjusted hazard ratios (aHRs) comparing vaccinated with unvaccinated individuals, and quantified waning vaccine effectiveness as ratios of aHRs per-4-week period. The outcomes were COVID-19 hospitalisation, COVID-19 death, positive SARS-CoV-2 test, and non-COVID-19 death. FindingsThe BNT162b2, ChAdOx1 and unvaccinated groups comprised 1,773,970, 2,961,011 and 2,433,988 individuals, respectively. Waning of vaccine effectiveness was similar across outcomes and vaccine brands: e.g. in the 65+ years subgroup ratios of aHRs versus unvaccinated for COVID-19 hospitalisation, COVID-19 death and positive SARS-CoV-2 test ranged from 1.23 (95% CI 1.15-1.32) to 1.27 (1.20-1.34) for BNT162b2 and 1.16 (0.98-1.37) to 1.20 (1.14-1.27) for ChAdOx1. Despite waning, rates of COVID-19 hospitalisation and COVID-19 death were substantially lower among vaccinated individuals compared to unvaccinated individuals up to 26 weeks after second dose, with estimated aHRs <0.20 (>80% vaccine effectiveness) for BNT162b2, and <0.26 (>74%) for ChAdOx1. By weeks 23-26, rates of SARS-CoV-2 infection in fully vaccinated individuals were similar to or higher than those in unvaccinated individuals: aHRs ranged from 0.85 (0.78-0.92) to 1.53 (1.07-2.18) for BNT162b2, and 1.21 (1.13-1.30) to 1.99 (1.94-2.05) for ChAdOx1. InterpretationThe rate at which estimated vaccine effectiveness waned was strikingly consistent for COVID-19 hospitalisation, COVID-19 death and positive SARS-CoV-2 test, and similar across subgroups defined by age and clinical vulnerability. If sustained to outcomes of infection with the Omicron variant and to booster vaccination, these findings will facilitate scheduling of booster vaccination doses.

3.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21252528

RESUMO

The B.1.1.7 variant of concern (VOC) is increasing in prevalence across Europe. Accurate estimation of disease severity associated with this VOC is critical for pandemic planning. We found increased risk of death for VOC compared with non-VOC cases in England (HR: 1.67 (95% CI: 1.34 - 2.09; P<.0001). Absolute risk of death by 28-days increased with age and comorbidities. VOC has potential to spread faster with higher mortality than the pandemic to date.

4.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21253112

RESUMO

ObjectivesTo assess the association between learning disability and risk of hospitalisation and mortality from COVID-19 in England among adults and children. DesignWorking on behalf of NHS England, two cohort studies using patient-level data for >17 million people from primary care electronic health records were linked with death data from the Office for National Statistics and hospitalization data from NHS Secondary Uses Service using the OpenSAFELY platform. SettingGeneral practices in England which use TPP software. ParticipantsParticipants were males and females, aged up to 105 years, from two cohorts: (1) wave 1, registered with a TPP practice as of 1st March 2020 and followed until 31st August, 2020; (2) wave 2 registered 1st September 2020 and followed until 31st December 2020 (for admissions) or 8th February 2021 (for deaths). The main exposure group was people included on a general practice learning disability register (LDR), with a subgroup of people classified as having profound or severe learning disability. We also identified patients with Down syndrome and cerebral palsy (whether or not on the learning disability register). Main outcome measures(i) COVID-19 related death, (ii) COVID-19 related hospitalisation. Non-COVID-19 related death was also explored. ResultsIn wave 1, of 14,301,415 included individuals aged 16 and over, 90,095 (0.63%) were identified as being on the LDR. 30,173 COVID-related hospital admissions, 13,919 COVID-19 related deaths and 69,803 non-COVID deaths occurred; of which 538 (1.8%), 221 (1.6%) and 596 (0.85%) were among individuals on the LDR, respectively. In wave 2, 27,611 COVID-related hospital admissions, 17,933 COVID-19 related deaths and 54,171 non-COVID deaths occurred; of which 383 (1.4%), 260 (1.4%) and 470 (0.87%) were among individuals on the LDR. Wave 1 hazard ratios for individuals on the LDR, adjusted for age, sex, ethnicity and geographical location, were 5.3 (95% confidence interval (CI) 4.9, 5.8) for COVID-19 related hospital admissions and 8.2 (95% CI: 7.1, 9.4) for COVID-19 related death. Wave 2 produced similar estimates. Associations were stronger among those classed as severe-profound and among those in residential care. Down syndrome and cerebral palsy were associated with increased hazard of both events in both waves; Down syndrome to a much greater extent. Hazards of non-COVID-19 related death followed similar patterns with weaker associations. ConclusionsPeople with learning disabilities have markedly increased risks of hospitalisation and mortality from COVID-19. This raised risk is over and above that seen for non-COVID causes of death. Ensuring prompt access to Covid-19 testing and health care and consideration of prioritisation for COVID-19 vaccination and other targeted preventive measures are warranted.

5.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21252433

RESUMO

ObjectivesTo 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. DesignThree 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. SettingWorking 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. ParticipantsEligible participants were adults aged 18 or over, registered at a general practice using TPP software on 1st March 2020 with recorded sex, postcode and ethnicity. 11,972,947 individuals were included, and 7,999 participants experienced a COVID-19 related death. The study period lasted 100 days, ending 8th June 2020. PredictorsA 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. Main outcome measuresCOVID-19 related death. ResultsAll 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. ConclusionsReliable 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.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...