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Background: People with blood cancers have increased risk of severe outcomes from COVID-19 and were prioritised for vaccination. Methods: Individuals in the QResearch database aged 12 years and above on 1st December 2020 were included in the analysis. Kaplan-Meier analysis described time to COVID-19 vaccine uptake in people with blood cancer and other high-risk disorders. Cox regression was used to identify factors associated with vaccine uptake in people with blood cancer. Results: The analysis included 12,274,948 individuals, of whom 97,707 had a blood cancer diagnosis. 92% of people with blood cancer received at least one dose of vaccine, compared to 80% of the general population, but there was lower uptake of each subsequent vaccine dose (31% for fourth dose). Vaccine uptake decreased with social deprivation (HR 0.72, 95%CI 0.70-0.74 for most deprived versus most affluent quintile for first vaccine). Compared with White groups, uptake of all vaccine doses was significantly lower in people of Pakistani and Black ethnicity, and more of these groups remain unvaccinated. Conclusions: COVID-19 vaccine uptake declines following second dose and there are ethnic and social disparities in uptake in blood cancer populations. Enhanced communication of benefits of vaccination to these groups is needed.

IntroductionThis study aims to explore the impact of COVID-19 vaccination on critical care by examining associations between vaccination and admission to critical care with COVID-19 during England’s Delta wave, by age group, dose, and over time.MethodsWe used linked routinely-collected data to conduct a population cohort study of patients admitted to adult critical care in England for management of COVID-19 between 1 May and 15 December 2021. Included participants were the whole population of England aged 18 years or over (44.7 million), including 10,141 patients admitted to critical care with COVID-19. The intervention was vaccination with one, two, or a booster/three doses of any COVID-19 vaccine.ResultsCompared with unvaccinated patients, vaccinated patients were older (median 64 years for patients receiving two or more doses versus 50 years for unvaccinated), with higher levels of severe comorbidity (20.3% versus 3.9%) and immunocompromise (15.0% versus 2.3%). Compared with patients who were unvaccinated, those vaccinated with two doses had a relative risk reduction (RRR) of between 90.1% (patients aged 18–29, 95% CI, 86.8% to 92.7%) and 95.9% (patients aged 60–69, 95% CI, 95.5% to 96.2%). Waning was only observed for those aged 70+, for whom the RRR reduced from 97.3% (91.0% to 99.2%) to 86.7% (85.3% to 90.1%) between May and December but increased again to 98.3% (97.6% to 98.8%) with a booster/third dose.ConclusionImportant demographic and clinical differences exist between vaccinated and unvaccinated patients admitted to critical care with COVID-19. While not a causal analysis, our findings are consistent with a substantial and sustained impact of vaccination on reducing admissions to critical care during England’s Delta wave, with evidence of waning predominantly restricted to those aged 70+.

Objective In this Italian population-based study, we aimed to evaluate neurological complications after first and/or second dose of COVID-19 vaccines and factors potentially associated with adverse effects. Methods Our study included adults aged-18 years and older, receiving two vaccine doses in vaccination Hub Novegro (Lombardy) between July 7–16 2021. NEURO-COVAX questionnaire was able to capture neurological events, onset and duration. Data digitized centrally by Lombardy-Region were used to match demographic/clinical characteristics and identify a vulnerable profile. Associations between vaccine-lines and development of complications were assessed. Results NEURO-COVAX-cohort included 19.108 vaccinated-people: 15.368 mRNA BNT162b2, 2077 mRNA-1273, 1651 ChAdOx1nCov-19 and 12 Ad26.COV2, subsequently excluded. About 31.3% of sample developed post-vaccination neurological complications, particularly ChAdOx1nCov-19. Vulnerable clinical profile emerged, over 40% of symptomatic people showed comorbidities in clinical history. Defining neurological risk profile, we found increased risk for ChAdOx1nCov-19 of tremor (OR:5.12, 95% CI:3.51–7.48), insomnia (OR:1.87, 95% CI:1.02–3.39); muscle spasms (OR:1.62, 95% CI:1.08–2.46) and headache (OR:1.49, 95% CI:0.96–1.57); for mRNA-1273 of parethesias (OR:2.37, 95% CI:1.48–3.79), vertigo (OR:1.68, 95% CI:1.20–2.35), diplopia (OR:1.55, 95% CI:0.67–3.57), daytime sleepiness (OR:1.28, 95% CI:0.98–1.67). Discussion This study estimates prevalence and risk of neurological complications associated to COVID-19 vaccines, improving vaccination guidelines and loading in future to personalized preventive medicine.

Sotrovimab is a neutralising monoclonal antibody (nMAB), currently administrated in England to treat extremely clinically vulnerable COVID-19 patients. Trials have shown it to have mild or moderate side effects, however safety in real-world settings has not been yet evaluated. We used national databases to investigate its uptake and safety in community patients across England. We used a cohort study to describe uptake and a self-controlled case series design to evaluate the risks of 49 pre-specified suspected adverse events in the 2-28 days post-treatment. Between December 11, 2021 and May 24, 2022, there were 172,860 COVID-19 patients eligible for treatment. Of the 22,815 people who received Sotrovimab, 21,487 (94.2%) had a positive SARS-CoV-2 test and 5,999 (26.3%) were not on the eligible list. Between treated and untreated eligible individuals, the mean age (54.6, SD: 16.1 vs 54.1, SD: 18.3) and sex distribution (women: 60.9% vs 58.1%; men: 38.9% vs 41.1%) were similar. There were marked variations in uptake between ethnic groups, which was higher amongst Indian (15.0%; 95%CI 13.8, 16.3), Other Asian (13.7%; 95%CI 11.9, 15.8), White (13.4%; 95%CI 13.3, 13.6), and Bangladeshi (11.4%; 95%CI 8.8, 14.6); and lower amongst Black Caribbean individuals (6.4%; 95%CI 5.4, 7.5) and Black Africans (4.7%; 95%CI 4.1, 5.4). We found no increased risk of any of the suspected adverse events in the overall period of 2-28 days post-treatment, but an increased risk of rheumatoid arthritis (IRR 3.08, 95% CI 1.44, 6.58) and of systematic lupus erythematosus (IRR 5.15, 95% CI 1.60, 16.60) in the 2-3 days post-treatment, when we narrowed the risk period.FundingNational Institute of Health Research (Grant reference 135561)

Background A high BMI has been associated with a reduced immune response to vaccination against influenza. We aimed to investigate the association between BMI and COVID-19 vaccine uptake, vaccine effectiveness, and risk of severe COVID-19 outcomes after vaccination by using a large, representative population-based cohort from England. Methods In this population-based cohort study, we used the QResearch database of general practice records and included patients aged 18 years or older who were registered at a practice that was part of the database in England between Dec 8, 2020 (date of the first vaccination in the UK), to Nov 17, 2021, with available data on BMI. Uptake was calculated as the proportion of people with zero, one, two, or three doses of the vaccine across BMI categories. Effectiveness was assessed through a nested matched case-control design to estimate odds ratios (OR) for severe COVID-19 outcomes (ie, admission to hospital or death) in people who had been vaccinated versus those who had not, considering vaccine dose and time periods since vaccination. Vaccine effectiveness against infection with SARS-CoV-2 was also investigated. Multivariable Cox proportional hazard models estimated the risk of severe COVID-19 outcomes associated with BMI (reference BMI 23 kg/m²) after vaccination. Findings Among 9 171 524 participants (mean age 52 [SD 19] years; BMI 26·7 [5·6] kg/m²), 566 461 tested positive for SARS-CoV-2 during follow-up, of whom 32 808 were admitted to hospital and 14 389 died. Of the total study sample, 19·2% (1 758 689) were unvaccinated, 3·1% (287 246) had one vaccine dose, 52·6% (4 828 327) had two doses, and 25·0% (2 297 262) had three doses. In people aged 40 years and older, uptake of two or three vaccine doses was more than 80% among people with overweight or obesity, which was slightly lower in people with underweight (70–83%). Although significant heterogeneity was found across BMI groups, protection against severe COVID-19 disease (comparing people who were vaccinated vs those who were not) was high after 14 days or more from the second dose for hospital admission (underweight: OR 0·51 [95% CI 0·41–0·63]; healthy weight: 0·34 [0·32–0·36]; overweight: 0·32 [0·30–0·34]; and obesity: 0·32 [0·30–0·34]) and death (underweight: 0·60 [0·36–0·98]; healthy weight: 0·39 [0·33–0·47]; overweight: 0·30 [0·25–0·35]; and obesity: 0·26 [0·22–0·30]). In the vaccinated cohort, there were significant linear associations between BMI and COVID-19 hospitalisation and death after the first dose, and J-shaped associations after the second dose. Interpretation Using BMI categories, there is evidence of protection against severe COVID-19 in people with overweight or obesity who have been vaccinated, which was of a similar magnitude to that of people of healthy weight. Vaccine effectiveness was slightly lower in people with underweight, in whom vaccine uptake was also the lowest for all ages. In the vaccinated cohort, there were increased risks of severe COVID-19 outcomes for people with underweight or obesity compared with the vaccinated population with a healthy weight. These results suggest the need for targeted efforts to increase uptake in people with low BMI (, UK Research & Innovation (UKRI), National Institute for Health Research (NIHR)

Importance: Individuals surviving severe COVID-19 may be at increased risk of neuropsychiatric sequelae. Robust assessment of these risks may improve clinical understanding of the post-COVID syndrome, aid clinical care during the ongoing pandemic, and inform post-pandemic planning. Objective: To quantify the risks of new-onset neuropsychiatric conditions, and new neuropsychiatric medication prescriptions following discharge from a COVID-19-related hospitalization. To compare these to risks after discharge from hospitalization for other severe acute respiratory infections (SARI) during the COVID-19 pandemic. Design: Cohort study from 24th January 2020 to 7th July 2021. Setting: QResearch primary care and linked electronic health record databases, including national SARS-CoV-2 testing, hospital episode statistics, intensive care admissions data, and mortality registers in England. Participants: Adults aged 18+ years. Exposures: COVID-19 or SARI-related hospital admission (including intensive care admission). Main outcomes and measures: New-onset diagnoses of neuropsychiatric conditions (anxiety, dementia, psychosis, depression, bipolar disorder) or first prescription for relevant medications (antidepressants, hypnotic/anxiolytics, antipsychotics) during 12 months follow-up from hospital discharge. Maximally-adjusted hazard ratios (HR) with 95% confidence intervals (CI) were estimated using flexible parametric survival models. Results: The cohort comprised 8.38 million adults (4.18 million women, 4.20 million men; mean age 49.18 years): 16,679 survived a hospital admission for SARI, and 32,525 survived a hospital admission for COVID-19. Compared to the remaining population, SARI and COVID-19 hospitalization survivors had higher risks of all subsequent neuropsychiatric diagnoses, e.g.: anxiety (HR 1.86 [95% CI: 1.56-2.21] and 2.36 [2.03-2.74], respectively); dementia (2.55 [2.17-3.00] and 2.63 [2.21-3.14]). Similar trends were observed for all medications analysed, e.g., first prescriptions of anti-depressants (HR 2.55 [95% CI: 2.24-2.90], 3.24 [2.91-3.61], respectively). There were no significant differences observed when directly comparing the COVID-19 group to the SARI group apart from a lower risk of anti-psychotic prescriptions in the former (HR 0.80, 95% CI 0.69-0.92). Conclusions and relevance: The neuropsychiatric sequelae of severe COVID-19 are similar to those for other severe acute respiratory infections. This may inform post-discharge support for people surviving severe respiratory acute infections.

Importance Although children mainly experience mild COVID-19 disease, hospitalization rates are increasing, with limited understanding of underlying factors. There is an established association between race and severe COVID-19 outcomes in adults in England; however, whether a similar association exists in children is unclear. Objective To investigate the association between race and childhood COVID-19 testing and hospital outcomes. Design, Setting, Participants In this cohort study, children (0-18 years of age) from participating family practices in England were identified in the QResearch database between January 24 and November 30, 2020. The QResearch database has individually linked patients with national SARS-CoV-2 testing, hospital admission, and mortality data. Exposures The main characteristic of interest is self-reported race. Other exposures were age, sex, deprivation level, geographic region, household size, and comorbidities (asthma; diabetes; and cardiac, neurologic, and hematologic conditions). Main Outcomes and Measures The primary outcome was hospital admission with confirmed COVID-19. Secondary outcomes were SARS-CoV-2–positive test result and any hospital attendance with confirmed COVID-19 and intensive care admission. Results Of 2 576 353 children (mean [SD] age, 9.23 [5.24] years; 48.8% female), 410 726 (15.9%) were tested for SARS-CoV-2 and 26 322 (6.4%) tested positive. A total of 1853 children (0.07%) with confirmed COVID-19 attended hospital, 343 (0.01%) were admitted to the hospital, and 73 (0.002%) required intensive care. Testing varied across race. White children had the highest proportion of SARS-CoV-2 tests (223 701/1 311 041 [17.1%]), whereas Asian children (33 213/243 545 [13.6%]), Black children (7727/93 620 [8.3%]), and children of mixed or other races (18 971/147 529 [12.9%]) had lower proportions. Compared with White children, Asian children were more likely to have COVID-19 hospital admissions (adjusted odds ratio [OR], 1.62; 95% CI, 1.12-2.36), whereas Black children (adjusted OR, 1.44; 95% CI, 0.90-2.31) and children of mixed or other races (adjusted OR, 1.40; 95% CI, 0.93-2.10) had comparable hospital admissions. Asian children were more likely to be admitted to intensive care (adjusted OR, 2.11; 95% CI, 1.07-4.14), and Black children (adjusted OR, 2.31; 95% CI, 1.08-4.94) and children of mixed or other races (adjusted OR, 2.14; 95% CI, 1.25-3.65) had longer hospital admissions (≥36 hours). Conclusions and Relevance In this large population-based study exploring the association between race and childhood COVID-19 testing and hospital outcomes, several race-specific disparities were observed in severe COVID-19 outcomes. However, ascertainment bias and residual confounding in this cohort study should be considered before drawing any further conclusions. Overall, findings of this study have important public health implications internationally.

Although myocarditis and pericarditis were not observed as adverse events in coronavirus disease 2019 (COVID-19) vaccine trials, there have been numerous reports of suspected cases following vaccination in the general population. We undertook a self-controlled case series study of people aged 16 or older vaccinated for COVID-19 in England between 1 December 2020 and 24 August 2021 to investigate hospital admission or death from myocarditis, pericarditis and cardiac arrhythmias in the 1–28 days following adenovirus (ChAdOx1, n = 20,615,911) or messenger RNA-based (BNT162b2, n = 16,993,389; mRNA-1273, n = 1,006,191) vaccines or a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive test (n = 3,028,867). We found increased risks of myocarditis associated with the first dose of ChAdOx1 and BNT162b2 vaccines and the first and second doses of the mRNA-1273 vaccine over the 1–28 days postvaccination period, and after a SARS-CoV-2 positive test. We estimated an extra two (95% confidence interval (CI) 0, 3), one (95% CI 0, 2) and six (95% CI 2, 8) myocarditis events per 1 million people vaccinated with ChAdOx1, BNT162b2 and mRNA-1273, respectively, in the 28 days following a first dose and an extra ten (95% CI 7, 11) myocarditis events per 1 million vaccinated in the 28 days after a second dose of mRNA-1273. This compares with an extra 40 (95% CI 38, 41) myocarditis events per 1 million patients in the 28 days following a SARS-CoV-2 positive test. We also observed increased risks of pericarditis and cardiac arrhythmias following a positive SARS-CoV-2 test. Similar associations were not observed with any of the COVID-19 vaccines, apart from an increased risk of arrhythmia following a second dose of mRNA-1273. Subgroup analyses by age showed the increased risk of myocarditis associated with the two mRNA vaccines was present only in those younger than 40.

Bipartite incidence graph sampling provides a unified representation of many sampling situations for the purpose of estimation, including the existing unconventional sampling methods, such as indirect, network or adaptive cluster sampling, which are not originally described as graph problems. We develop a large class of design-based linear estimators, defined for the sample edges and subjected to a general condition of design unbiasedness. The class contains as special cases the classic Horvitz-Thompson estimator, as well as the other unbiased estimators in the literature of unconventional sampling, which can be traced back to Birnbaum et al. (1965). Our generalisation allows one to devise other unbiased estimators in future, thereby providing a potential of efficiency gains. Illustrations are given for adaptive cluster sampling, line-intercept sampling and simulated graphs.

BackgroundPancreatic cancer continues to have an extremely poor prognosis in part due to late diagnosis. 25% of pancreatic cancer patients have a prior diagnosis of diabetes, and hence identifying individuals at risk of pancreatic cancer in those with recently diagnosed type 2 diabetes may be a useful opportunity to identify candidates for screening and early detection. In this study, we will comparatively evaluate regression and machine learning-based clinical prediction models for estimating individual risk of developing pancreatic cancer two years after type 2 diabetes diagnosis.MethodsIn the development dataset, we will include adults aged 30-84 years with incident type-2 diabetes registered with QResearch primary care database. Patients will be followed up from type-2 diabetes diagnosis to first diagnosis of pancreatic cancer as recorded in any one of primary care records, hospital episode statistics, cancer registry data, or death records. Cox-proportional hazards models will be used to develop a risk prediction model for estimating individual risk of developing pancreatic cancer during up to 2 years of follow-up. We will perform variable selection using a combination of clinical and statistical significance approach i.e. HR 1.1 and pInternal-external cross-validation (IECV) framework across geographical regions within England will be used to assess performance and pooled using random effects meta-analysis using: (i) model fit in terms of variation explained by the model Royston & Sauerbrei’s R2D, (ii) calibration slope and calibration-in-the-large, and (iii) discrimination measured in terms of Harrell’s C and Royston & Sauerbrei’s D-statistic.Further, we will evaluate machine learning (ML) approaches for the clinical prediction model using neural networks (NN) and XGBoost. The model predictors and performance of these will be compared with the results of those derived from the regression-based strategy.DiscussionThe proposed study will develop and validate a novel risk prediction model to aid early diagnosis of pancreatic cancer in patients with new-onset diabetes in primary care. With an enhanced decision-risk tool for use at point-of care by general practitioners to assess pancreatic cancer risk, it may improve decision-making so that at-risk patients are rapidly prioritised to aid early diagnosis of pancreatic cancer in patients with newly diagnosed diabetes.

In an updated self-controlled case series analysis of 42,200,614 people aged 13 years or more, we evaluate the association between COVID-19 vaccination and myocarditis, stratified by age and sex, including 10,978,507 people receiving a third vaccine dose. Myocarditis risk was increased during 1-28 days following a third dose of BNT162b2 (IRR 2.02, 95%CI 1.40, 2.91). Associations were strongest in males younger than 40 years for all vaccine types with an additional 3 (95%CI 1, 5) and 12 (95% CI 1,17) events per million estimated in the 1-28 days following a first dose of BNT162b2 and mRNA-1273, respectively; 14 (95%CI 8, 17), 12 (95%CI 1, 7) and 101 (95%CI 95, 104) additional events following a second dose of ChAdOx1, BNT162b2 and mRNA-1273, respectively; and 13 (95%CI 7, 15) additional events following a third dose of BNT162b2, compared with 7 (95%CI 2, 11) additional events following COVID-19 infection. An association between COVID-19 infection and myocarditis was observed in all ages for both sexes but was substantially higher in those older than 40 years. These findings have important implications for public health and vaccination policy.FundingHealth Data Research UK.

Emerging reports of rare neurological complications associated with COVID-19 infection and vaccinations are leading to regulatory, clinical and public health concerns. We undertook a self-controlled case series study to investigate hospital admissions from neurological complications in the 28 days after a first dose of ChAdOx1nCoV-19 (n = 20,417,752) or BNT162b2 (n = 12,134,782), and after a SARS-CoV-2-positive test (n = 2,005,280). There was an increased risk of Guillain–Barré syndrome (incidence rate ratio (IRR), 2.90; 95% confidence interval (CI): 2.15–3.92 at 15–21 days after vaccination) and Bell’s palsy (IRR, 1.29; 95% CI: 1.08–1.56 at 15–21 days) with ChAdOx1nCoV-19. There was an increased risk of hemorrhagic stroke (IRR, 1.38; 95% CI: 1.12–1.71 at 15–21 days) with BNT162b2. An independent Scottish cohort provided further support for the association between ChAdOx1nCoV and Guillain–Barré syndrome (IRR, 2.32; 95% CI: 1.08–5.02 at 1–28 days). There was a substantially higher risk of all neurological outcomes in the 28 days after a positive SARS-CoV-2 test including Guillain–Barré syndrome (IRR, 5.25; 95% CI: 3.00–9.18). Overall, we estimated 38 excess cases of Guillain–Barré syndrome per 10 million people receiving ChAdOx1nCoV-19 and 145 excess cases per 10 million people after a positive SARS-CoV-2 test. In summary, although we find an increased risk of neurological complications in those who received COVID-19 vaccines, the risk of these complications is greater following a positive SARS-CoV-2 test., A self-controlled case series analysis of nearly 32 million people in England shows an increased risk of rare neurological complications in those who received COVID-19 vaccines and following SARS-CoV-2 infection. The results highlight 38 excess cases of Guillain–Barré syndrome per 10 million ChAdOx1nCoV-19 vaccinations.

ImportanceEvidence indicates that preexisting neuropsychiatric conditions confer increased risks of severe outcomes from COVID-19 infection. It is unclear how this increased risk compares with risks associated with other severe acute respiratory infections (SARIs).ObjectiveTo determine whether preexisting diagnosis of and/or treatment for a neuropsychiatric condition is associated with severe outcomes from COVID-19 infection and other SARIs and whether any observed association is similar between the 2 outcomes.Design, Setting, and ParticipantsPrepandemic (2015-2020) and contemporary (2020-2021) longitudinal cohorts were derived from the QResearch database of English primary care records. Adjusted hazard ratios (HRs) with 99% CIs were estimated in April 2022 using flexible parametric survival models clustered by primary care clinic. This study included a population-based sample, including all adults in the database who had been registered with a primary care clinic for at least 1 year. Analysis of routinely collected primary care electronic medical records was performed.ExposuresDiagnosis of and/or medication for anxiety, mood, or psychotic disorders and diagnosis of dementia, depression, schizophrenia, or bipolar disorder.Main Outcomes and MeasuresCOVID-19–related mortality, or hospital or intensive care unit admission; SARI-related mortality, or hospital or intensive care unit admission.ResultsThe prepandemic cohort comprised 11 134 789 adults (223 569 SARI cases [2.0%]) with a median (IQR) age of 42 (29-58) years, of which 5 644 525 (50.7%) were female. The contemporary cohort comprised 8 388 956 adults (58 203 severe COVID-19 cases [0.7%]) with a median (IQR) age of 48 (34-63) years, of which 4 207 192 were male (50.2%). Diagnosis and/or treatment for neuropsychiatric conditions other than dementia was associated with an increased likelihood of a severe outcome from SARI (anxiety diagnosis: HR, 1.16; 99% CI, 1.13-1.18; psychotic disorder diagnosis and treatment: HR, 2.56; 99% CI, 2.40-2.72) and COVID-19 (anxiety diagnosis: HR, 1.16; 99% CI, 1.12-1.20; psychotic disorder treatment: HR, 2.37; 99% CI, 2.20-2.55). The effect estimate for severe outcome with dementia was higher for those with COVID-19 than SARI (HR, 2.85; 99% CI, 2.71-3.00 vs HR, 2.13; 99% CI, 2.07-2.19).Conclusions and RelevanceIn this longitudinal cohort study, UK patients with preexisting neuropsychiatric conditions and treatments were associated with similarly increased risks of severe outcome from COVID-19 infection and SARIs, except for dementia.

Objective To assess the association between covid-19 vaccines and risk of thrombocytopenia and thromboembolic events in England among adults. Design Self-controlled case series study using national data on covid-19 vaccination and hospital admissions. Setting Patient level data were obtained for approximately 30 million people vaccinated in England between 1 December 2020 and 24 April 2021. Electronic health records were linked with death data from the Office for National Statistics, SARS-CoV-2 positive test data, and hospital admission data from the United Kingdom’s health service (NHS). Participants 29 121 633 people were vaccinated with first doses (19 608 008 with Oxford-AstraZeneca (ChAdOx1 nCoV-19) and 9 513 625 with Pfizer-BioNTech (BNT162b2 mRNA)) and 1 758 095 people had a positive SARS-CoV-2 test. People aged ≥16 years who had first doses of the ChAdOx1 nCoV-19 or BNT162b2 mRNA vaccines and any outcome of interest were included in the study. Main outcome measures The primary outcomes were hospital admission or death associated with thrombocytopenia, venous thromboembolism, and arterial thromboembolism within 28 days of three exposures: first dose of the ChAdOx1 nCoV-19 vaccine; first dose of the BNT162b2 mRNA vaccine; and a SARS-CoV-2 positive test. Secondary outcomes were subsets of the primary outcomes: cerebral venous sinus thrombosis (CVST), ischaemic stroke, myocardial infarction, and other rare arterial thrombotic events. Results The study found increased risk of thrombocytopenia after ChAdOx1 nCoV-19 vaccination (incidence rate ratio 1.33, 95% confidence interval 1.19 to 1.47 at 8-14 days) and after a positive SARS-CoV-2 test (5.27, 4.34 to 6.40 at 8-14 days); increased risk of venous thromboembolism after ChAdOx1 nCoV-19 vaccination (1.10, 1.02 to 1.18 at 8-14 days) and after SARS-CoV-2 infection (13.86, 12.76 to 15.05 at 8-14 days); and increased risk of arterial thromboembolism after BNT162b2 mRNA vaccination (1.06, 1.01 to 1.10 at 15-21 days) and after SARS-CoV-2 infection (2.02, 1.82 to 2.24 at 15-21 days). Secondary analyses found increased risk of CVST after ChAdOx1 nCoV-19 vaccination (4.01, 2.08 to 7.71 at 8-14 days), after BNT162b2 mRNA vaccination (3.58, 1.39 to 9.27 at 15-21 days), and after a positive SARS-CoV-2 test; increased risk of ischaemic stroke after BNT162b2 mRNA vaccination (1.12, 1.04 to 1.20 at 15-21 days) and after a positive SARS-CoV-2 test; and increased risk of other rare arterial thrombotic events after ChAdOx1 nCoV-19 vaccination (1.21, 1.02 to 1.43 at 8-14 days) and after a positive SARS-CoV-2 test. Conclusion Increased risks of haematological and vascular events that led to hospital admission or death were observed for short time intervals after first doses of the ChAdOx1 nCoV-19 and BNT162b2 mRNA vaccines. The risks of most of these events were substantially higher and more prolonged after SARS-CoV-2 infection than after vaccination in the same population.

Background A more transmissible variant of SARS-CoV-2, the variant of concern 202012/01 or lineage B.1.1.7, has emerged in the UK. We aimed to estimate the risk of critical care admission, mortality in patients who are critically ill, and overall mortality associated with lineage B.1.1.7 compared with non-B.1.1.7. We also compared clinical outcomes between these two groups. Methods For this observational cohort study, we linked large primary care (QResearch), national critical care (Intensive Care National Audit & Research Centre Case Mix Programme), and national COVID-19 testing (Public Health England) databases. We used SARS-CoV-2 positive samples with S-gene molecular diagnostic assay failure (SGTF) as a proxy for the presence of lineage B.1.1.7. We extracted two cohorts from the data: the primary care cohort, comprising patients in primary care with a positive community COVID-19 test reported between Nov 1, 2020, and Jan 26, 2021, and known SGTF status; and the critical care cohort, comprising patients admitted for critical care with a positive community COVID-19 test reported between Nov 1, 2020, and Jan 27, 2021, and known SGTF status. We explored the associations between SARS-CoV-2 infection with and without lineage B.1.1.7 and admission to a critical care unit (CCU), 28-day mortality, and 28-day mortality following CCU admission. We used Royston-Parmar models adjusted for age, sex, geographical region, other sociodemographic factors (deprivation index, ethnicity, household housing category, and smoking status for the primary care cohort; and ethnicity, body-mass index, deprivation index, and dependency before admission to acute hospital for the CCU cohort), and comorbidities (asthma, chronic obstructive pulmonary disease, type 1 and 2 diabetes, and hypertension for the primary care cohort; and cardiovascular disease, respiratory disease, metastatic disease, and immunocompromised conditions for the CCU cohort). We reported information on types and duration of organ support for the B.1.1.7 and non-B.1.1.7 groups. Findings The primary care cohort included 198 420 patients with SARS-CoV-2 infection. Of these, 117 926 (59·4%) had lineage B.1.1.7, 836 (0·4%) were admitted to CCU, and 899 (0·4%) died within 28 days. The critical care cohort included 4272 patients admitted to CCU. Of these, 2685 (62·8%) had lineage B.1.1.7 and 662 (15·5%) died at the end of critical care. In the primary care cohort, we estimated adjusted hazard ratios (HRs) of 2·15 (95% CI 1·75–2·65) for CCU admission and 1·65 (1·36–2·01) for 28-day mortality for patients with lineage B.1.1.7 compared with the non-B.1.1.7 group. The adjusted HR for mortality in critical care, estimated with the critical care cohort, was 0·91 (0·76–1·09) for patients with lineage B.1.1.7 compared with those with non-B.1.1.7 infection. Interpretation Patients with lineage B.1.1.7 were at increased risk of CCU admission and 28-day mortality compared with patients with non-B.1.1.7 SARS-CoV-2. For patients receiving critical care, mortality appeared to be independent of virus strain. Our findings emphasise the importance of measures to control exposure to and infection with COVID-19. Funding Wellcome Trust, National Institute for Health Research Oxford Biomedical Research Centre, and the Medical Sciences Division of the University of Oxford.

BackgroundA new, more transmissible variant of SARS-CoV-2, variant of concern (VOC) 202012/01 or lineage B.1.1.7, has emerged in the UK. We estimate the risk of critical care admission, mortality in critical ill patients, and overall mortality associated with VOC B.1.1.7 compared with the original variant. We also compare clinical outcomes between these variants ‘ groups.MethodsWe linked a large primary care (QResearch), the national critical care (ICNARC CMP) and the COVID-19 testing (PHE) database and extracted two cohorts. The first was used to explore the association between VOC B.1.1.7 and critical care admission and 28-day mortality. The second to determine the risk of mortality in critically ill patients with VOC B.1.1.7 compared to those without. We used Royston-Parmar models adjusted for age, sex, region, other socio-demographics and comorbidities (asthma, COPD, type I and II, hypertension). We reported information on types and duration of organ supports for the two variants ‘ groups.FindingsThe first cohort included 198,420 patients. Of these, 80,494 had VOC B.1.1.7, 712 were critically ill and 630 died by 28 days. The second cohort included 3432 critically ill patients. Of these, 2019 had VOC B.1.1.7 and 822 died at the end of critical care. Using the first cohort, we estimated adjusted hazard ratios for critical care admission and mortality to be 1.99 (95% CI: 1.59, 2.49) and 1.59 (95% CI: 1.25-2.03) for VOC B.1.1.7 compared with the original variant group, respectively. The adjusted hazard ratio for mortality in critical care, estimated using the second cohort, was 0.93 (95% CI 0.76-1.15) for patients with VOC B.1.1.7, compared to those without.InterpretationVOC B.1.1.7 appears to be more severe. Patients with VOC B.1.1.7 are at increased risk of critical care admission and mortality compared with patients without. For patients receiving critical care, mortality appears independent of virus strain.RESEARCH IN CONTEXTEvidence before this studyA new variant of the SARS-CoV-2 virus, variant of concern (VOC) 202012/01, or lineage B.1.1.7, was detected in England in September 2020. The characteristics and outcomes of patients infected with VOC B.1.1.7 are not yet known. VOC B.1.1.7 has been associated with increased transmissibility. Early analyses have suggested infection with VOC B.1.1.7 may be associated with a higher risk of mortality compared with infection with other virus variants, but these analyses had either limited ability to adjust for key confounding variables or did not consider critical care admission. The effects of VOC B.1.1.7 on severe COVID-19 outcomes remain unclear.Added value of this studyThis study found a 60% higher risk of 28-day mortality associated with infection with VOC B.1.1.7 in patients tested in the community in comparison with the original variant, when adjusted for key confounding variables. The risk of critical care admission for those with VOC B.1.1.7 is double the risk associated with the original variant. For patients receiving critical care, the infecting variant is not associated with the risk of mortality at the end of critical care.Implications of all the available evidenceThe higher mortality and rate of critical care admission associated with VOC B.1.1.7, combined with its known increased transmissibility, are likely to put health care systems under further stress. These effects may be mitigated by the ongoing vaccination programme.

BackgroundPancreatic cancer has the worst survival rate among all cancers. Almost 70% of patients in the UK were diagnosed at Stage IV.AimThis study aimed to investigate the symptoms associated with the diagnoses of pancreatic ductal adenocarcinoma (PDAC) and pancreatic neuroendocrine neoplasms (PNEN), and comparatively characterise the symptomatology between the two tumour types to inform earlier diagnosis.Design and settingA nested case-control study in primary care was conducted using data from the QResearch® database. Patients aged ≥25 years and diagnosed with PDAC or PNEN during 2000 to 2019 were included as cases. Up to 10 controls from the same general practice were matched with each case by age, sex, and calendar year using incidence density sampling.MethodConditional logistic regression was used to investigate the association between the 42 shortlisted symptoms and the diagnoses of PDAC and (or) PNEN in different timeframes relative to the index date, adjusting for patients’ sociodemographic characteristics, lifestyle, and relevant comorbidities.ResultsA total of 23 640 patients were identified as diagnosed with PDAC and 596 with PNEN. Of the symptoms identified, 23 were significantly associated with PDAC, and nine symptoms with PNEN. The two alarm symptoms for both tumours were jaundice and gastrointestinal bleeding. The two newly identified symptoms for PDAC were thirst and dark urine. The risk of unintentional weight loss may be longer than 2 years before the diagnosis of PNEN.ConclusionPDAC and PNEN have overlapping symptom profiles. The QCancer® (pancreas) risk prediction model could be updated by including the newly identified symptoms and comorbidities, which could help GPs identify high-risk patients for timely investigation in primary care.

This article is the study protocol and statistical analysis plan for the project. This study is set up to identify and quantify “red flag” symptoms associated with the diagnosis of Pancreatic Neuroendocrine Neoplasm (PNEN) and compare these with the symptoms associated with Pancreatic Ductal Adenocarcinoma (PDAC). The results of this study will inform the evidence base for the refinement of the QCancer (Pancreas) tools, which have been integrated into the UK NHS primary care computer systems, to improve the early recognition of PNEN.

Background: As COVID-19 vaccination programs are being rolled out globally, we studied the ethnic, deprivation, household size and comorbidity ‘patterning’ of existing vaccination programs in populations at high-risk for COVID-19, to inform risk-stratified vaccination strategies and mitigate health inequalities. Methods: A population-level cohort study of UK adults aged 65 years or older, using a large primary care database. We used multivariable logistic regression to assess uptake of influenza, pneumococcal and shingles vaccination across ethnic groups, deprivation quintile, household size, and comorbidities, computing odds ratios (OR) adjusted for age, sex, demographics, body mass index and smoking. Offers and refusals of each vaccination type were analysed in those not receiving them. Findings: The cohort comprised 2,054,463 patients from 1,318 general practices. 1,452,014 (70.7%) patients received influenza vaccine, 1,391,228 (67.7%) received pneumococcal vaccine, and 690,783 (53.4%) received shingles vaccine. Compared to Whites, influenza vaccination uptake was lower in Pakistani (adjusted odds ratio (OR) 0.82; 99% confidence interval: 0.74-0.90), Black Caribbean (OR 0.46; 0.43-0.48), Black African (OR 0.63; 0.58-0.68), Chinese (OR 0.70; 0.64-0.76) and ‘Other ethnic group’ (OR 0.65; 0.63-0.69). The Black Caribbean group had higher vaccination refusal than the White group for influenza vaccination (OR 1.17; 1.05-1.30). Vaccination uptake was lower among the more deprived and those living in household sizes above 3 or more persons, with some significant interactions between ethnicity and comorbidities. Uptake of all three vaccines was higher in those with asthma, COPD, type 2 diabetes, hypertension and learning disability, whilst lower in those with dementia. Interpretation: Whilst uptake and refusal of influenza, shingles and pneumococcal vaccination are patterned by ethnicity, deprivation, household size and comorbidities, vaccination offer is mostly patterned by comorbidities. This information can inform national policies to ensure equitable implementation of COVID-19 vaccination programs to avoid exacerbating health inequalities. Funding Statement: This project was funded by the Medical Research Council (Grant Ref: MR/V027778/1). Declaration of Interests: PST reports previous consultation with AstraZeneca and Duke-NUS outside the submitted work. KK is a Member of the Scientific Advisory Group for Emergencies (SAGE), Member of Independent SAGE, Director of the University of Leicester Centre for Black Minority Health and Trustee of the south Asian Health Foundation. JHC is a member of several SAGE committees and chair of the risk stratification subgroup of the NERVTAG. She is unpaid director of QResearch and founder and former medical director of ClinRisk Ltd (outside the submitted work). MP, AKC, HDM, DS, TAR, FZ, BRS, SJG, CC, CG have no interests to declare.

Using social media data for statistical analysis of general population faces commonly two basic obstacles: firstly, social media data are collected for different objects than the population units of interest; secondly, the relevant measures are typically not available directly but need to be extracted by algorithms or machine learning techniques. In this paper we examine and summarise two existing approaches to statistical analysis based on social media data, which can be discerned in the literature. In the first approach, analysis is applied to the social media data that are organised around the objects directly observed in the data; in the second one, a different analysis is applied to a constructed pseudo survey dataset, aimed to transform the observed social media data to a set of units from the target population. We elaborate systematically the relevant data quality frameworks, exemplify their applications, and highlight some typical challenges associated with social media data.