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1.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-334173

ABSTRACT

BACKGROUND Covid-19 vaccination has been associated with an increased risk of venous thromboembolism (VTE). However, it is unknown whether genetic predisposition to VTE is associated with an increased risk of thrombosis following vaccination. METHODS Using data from the UK Biobank, which contains in-depth genotyping data and linked vaccination and health outcomes information, we generated a polygenic risk score (PRS) using 299 genetic variants identified from a previous large genome-wide association study. We prospectively assessed associations between PRS and incident VTE after first and the second-dose vaccination separately. We conducted sensitivity analyses stratified by vaccine type (adenovirus- and mRNA-based) and using two historical unvaccinated cohorts. We estimated hazard ratios (HR) for PRS-VTE associations using Cox models. RESULTS Of 359,310 individuals receiving one dose of a Covid-19 vaccine, 160,327 (44.6%) were males, and the mean age at the vaccination date was 69.05 (standard deviation [SD] 8.04) years. After 28- and 90-days follow-up, 88 and 299 individuals developed VTE respectively, equivalent to an incidence rate of 0.88 (95% confidence interval [CI] 0.70 to 1.08) and 0.92 (95% CI 0.82 to 1.04) per 100,000 person-days. The PRS was significantly associated with a higher risk of VTE (HR per 1 SD increase in PRS, 1.41 (95% CI 1.15 to 1.73) in 28 days and 1.36 (95% CI 1.22 to 1.52) in 90 days). Similar associations were found after stratification by vaccine type, in the two-dose cohort and across the historical unvaccinated cohorts. CONCLUSIONS The genetic determinants of post-Covid-19-vaccination VTE are similar to those seen in historical data. This suggests that, at the population level, post-vaccine VTE has similar aetiology to conventional VTE. Additionally, the observed PRS-VTE associations were equivalent for adenovirus- and mRNA-based vaccines.

2.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-331619

ABSTRACT

Background: Characterization studies of COVID-19 patients with chronic obstructive pulmonary disease (COPD) are limited in size and scope. The aim of the study is to provide a large-scale characterization of COVID-19 patients with COPD. Methods: We included thirteen databases contributing data from January-June 2020 from North America (US), Europe and Asia. We defined two cohorts of patients with COVID-19 namely a ‘diagnosed’ and ‘hospitalized’ cohort. We followed patients from COVID-19 index date to 30 days or death. We performed descriptive analysis and reported the frequency of characteristics and outcomes among COPD patients with COVID-19. Results: The study included 934,778 patients in the diagnosed COVID-19 cohort and 177,201 in the hospitalized COVID-19 cohort. Observed COPD prevalence in the diagnosed cohort ranged from 3.8% (95%CI 3.5-4.1%) in French data to 22.7% (95%CI 22.4-23.0) in US data, and from 1.9% (95%CI 1.6-2.2) in South Korean to 44.0% (95%CI 43.1-45.0) in US data, in the hospitalized cohorts. COPD patients in the hospitalized cohort had greater comorbidity than those in the diagnosed cohort, including hypertension, heart disease, diabetes and obesity. Mortality was higher in COPD patients in the hospitalized cohort and ranged from 7.6% (95%CI 6.9-8.4) to 32.2% (95%CI 28.0-36.7) across databases. ARDS, acute renal failure, cardiac arrhythmia and sepsis were the most common outcomes among hospitalized COPD patients.   Conclusion: COPD patients with COVID-19 have high levels of COVID-19-associated comorbidities and poor COVID-19 outcomes. Further research is required to identify patients with COPD at high risk of worse outcomes.

3.
Nat Commun ; 13(1): 1639, 2022 03 23.
Article in English | MEDLINE | ID: covidwho-1758236

ABSTRACT

Small trials have suggested that heterologous vaccination with first-dose ChAdOx1 and second-dose BNT162b2 may generate a better immune response than homologous vaccination with two doses of ChAdOx1. In this cohort analysis, we use linked data from Catalonia (Spain), where those aged <60 who received a first dose of ChAdOx1 could choose between ChAdOx1 and BNT162b2 for their second dose. Comparable cohorts were obtained after exact-matching 14,325/17,849 (80.3%) people receiving heterologous vaccination to 14,325/149,386 (9.6%) receiving homologous vaccination by age, sex, region, and date of second dose. Of these, 464 (3.2%) in the heterologous and 694 (4.8%) in the homologous groups developed COVID-19 between 1st June 2021 and 5th December 2021. The resulting hazard ratio (95% confidence interval) is 0.66 [0.59-0.74], favouring heterologous vaccination. The two groups had similar testing rates and safety outcomes. Sensitivity and negative control outcome analyses confirm these findings. In conclusion, we demonstrate that a heterologous vaccination schedule with ChAdOx1 followed by BNT162b2 was more efficacious than and similarly safe to homologous vaccination with two doses of ChAdOx1. Most of the infections in our study occurred when Delta was the predominant SARS-CoV-2 variant in Spain. These data agree with previous phase 2 randomised trials.


Subject(s)
COVID-19 , SARS-CoV-2 , Aged , /therapeutic use , COVID-19/epidemiology , COVID-19/prevention & control , /therapeutic use , Humans , Vaccination/adverse effects , Vaccination/methods
4.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-331084

ABSTRACT

Background: Substantial evidence suggests that severe Covid-19 leads to an increased risk of Venous Thromboembolism (VTE). We aimed to quantify the risk of VTE associated with ambulatory Covid-19, study the potential protective role of vaccination, and establish key clinical and genetic determinants of post-Covid VTE. Methods We analyzed a cohort of ambulatory Covid-19 patients from UK Biobank, and compared their 30-day VTE risk with propensity-score-matched non-infected participants. We fitted multivariable models to study the associations between age, sex, ethnicity, socio-economic status, obesity, vaccination status and inherited thrombophilia with post-Covid VTE. Results Overall, VTE risk was nearly 20-fold higher in Covid-19 vs matched non-infected participants (hazard ratio [HR] 19.49, 95% confidence interval [CI] 11.50 to 33.05). However, the risk was substantially attenuated amongst the vaccinated (HR: 2.79, 95% CI 0.82 to 9.54). Older age, male sex, and obesity were independently associated with higher risk, with adjusted HRs of 2.00 (1.61 to 2.47) per 10 years, 1.66 (1.28 to 2.15), and 1.85 (1.29 to 2.64), respectively. Further, inherited thrombophilia led to an HR 2.05, 95% CI 1.15 to 3.66. Conclusions Ambulatory Covid-19 was associated with a striking 20-fold increase in incident VTE, but no elevated risk after breakthrough infection in the fully vaccinated. Older age, male sex, and obesity were clinical determinants of Covid-19-related VTE. Additionally, inherited thrombophilia doubled risk further, comparable to the effect of 10-year ageing. These findings reinforce the need for vaccination, and call for targeted strategies to prevent VTE during outpatient care of Covid-19

5.
BMJ ; 376: e068373, 2022 03 16.
Article in English | MEDLINE | ID: covidwho-1745759

ABSTRACT

OBJECTIVE: To study the association between covid-19 vaccines, SARS-CoV-2 infection, and risk of immune mediated neurological events. DESIGN: Population based historical rate comparison study and self-controlled case series analysis. SETTING: Primary care records from the United Kingdom, and primary care records from Spain linked to hospital data. PARTICIPANTS: 8 330 497 people who received at least one dose of covid-19 vaccines ChAdOx1 nCoV-19, BNT162b2, mRNA-1273, or Ad.26.COV2.S between the rollout of the vaccination campaigns and end of data availability (UK: 9 May 2021; Spain: 30 June 2021). The study sample also comprised a cohort of 735 870 unvaccinated individuals with a first positive reverse transcription polymerase chain reaction test result for SARS-CoV-2 from 1 September 2020, and 14 330 080 participants from the general population. MAIN OUTCOME MEASURES: Outcomes were incidence of Bell's palsy, encephalomyelitis, Guillain-Barré syndrome, and transverse myelitis. Incidence rates were estimated in the 21 days after the first vaccine dose, 90 days after a positive test result for SARS-CoV-2, and between 2017 and 2019 for background rates in the general population cohort. Indirectly standardised incidence ratios were estimated. Adjusted incidence rate ratios were estimated from the self-controlled case series. RESULTS: The study included 4 376 535 people who received ChAdOx1 nCoV-19, 3 588 318 who received BNT162b2, 244 913 who received mRNA-1273, and 120 731 who received Ad26.CoV.2; 735 870 people with SARS-CoV-2 infection; and 14 330 080 people from the general population. Overall, post-vaccine rates were consistent with expected (background) rates for Bell's palsy, encephalomyelitis, and Guillain-Barré syndrome. Self-controlled case series was conducted only for Bell's palsy, given limited statistical power, but with no safety signal seen for those vaccinated. Rates were, however, higher than expected after SARS-CoV-2 infection. For example, in the data from the UK, the standardised incidence ratio for Bell's palsy was 1.33 (1.02 to 1.74), for encephalomyelitis was 6.89 (3.82 to 12.44), and for Guillain-Barré syndrome was 3.53 (1.83 to 6.77). Transverse myelitis was rare (<5 events in all vaccinated cohorts) and could not be analysed. CONCLUSIONS: No safety signal was observed between covid-19 vaccines and the immune mediated neurological events of Bell's palsy, encephalomyelitis, Guillain-Barré syndrome, and transverse myelitis. An increased risk of Bell's palsy, encephalomyelitis, and Guillain-Barré syndrome was, however, observed for people with SARS-CoV-2 infection.


Subject(s)
Bell Palsy/epidemiology , COVID-19 Vaccines/administration & dosage , COVID-19/prevention & control , Encephalomyelitis/epidemiology , Guillain-Barre Syndrome/epidemiology , Myelitis, Transverse/epidemiology , SARS-CoV-2/immunology , Adult , Aged , Female , Humans , Incidence , Male , Middle Aged , Routinely Collected Health Data , Spain , United Kingdom , Vaccination/adverse effects
6.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-329301

ABSTRACT

Summary Background Mandatory COVID-19 certification was introduced at different times in the four countries of the UK. We aimed to study the effect of this intervention on the incidence of cases and hospital admissions. Methods The main outcome was the weekly averaged incidence of COVID-19 confirmed cases and hospital admissions. We performed Negative Binomial Segmented Regression (NBSR) and Autoregressive Integrated Moving Average (ARIMA) analyses for the four countries (England, Northern Ireland, Scotland and Wales), and fitted Difference-in-Differences (DiD) models to compare the latter three to England, where COVID-19 certification was imposed the latest. Findings NBSR methods suggested COVID-19 certification led to a decrease in the incidence of cases in Northern Ireland, but not in hospitalizations. In Wales, they also caused a decrease in the incidence of cases but not in hospital admissions. In Scotland, we observed a decrease in both cases and admissions. ARIMA models confirmed these results. The DiD model showed that the intervention decreased the incidence of COVID compared to England in all countries except Wales, in October. Then, the incidence rate of cases already had a decreasing tendency, as well as in England, hence a particular impact of Covid Passport was less obvious. In Wales, the model coefficients were 2.2 (95% CI -6.24,10.70) for cases and -0.144 (95% CI -0.248, -0.039) for admissions in October and -7.75 (95% CI -13.1, -2.46) for cases and -0.169 (95% CI-0.308, -0.031) for admissions in November. In Northern Ireland, -10.1 (95% CI -18.4, -1.79) for cases and -0.269 (95% CI -0.385, -0.153) for admissions. In Scotland they were 7.91 (95% CI 4.46,11.4) for cases and -0.097 (95% CI - 0.219,0.024) for admissions. Interpretation The introduction of mandatory certificates decreased cases in all countries except in England. Differences on concomitant measures, on vaccination uptake or Omicron variant prevalence could explain this discrepancy.

8.
BMC Med Res Methodol ; 22(1): 35, 2022 01 30.
Article in English | MEDLINE | ID: covidwho-1699687

ABSTRACT

BACKGROUND: We investigated whether we could use influenza data to develop prediction models for COVID-19 to increase the speed at which prediction models can reliably be developed and validated early in a pandemic. We developed COVID-19 Estimated Risk (COVER) scores that quantify a patient's risk of hospital admission with pneumonia (COVER-H), hospitalization with pneumonia requiring intensive services or death (COVER-I), or fatality (COVER-F) in the 30-days following COVID-19 diagnosis using historical data from patients with influenza or flu-like symptoms and tested this in COVID-19 patients. METHODS: We analyzed a federated network of electronic medical records and administrative claims data from 14 data sources and 6 countries containing data collected on or before 4/27/2020. We used a 2-step process to develop 3 scores using historical data from patients with influenza or flu-like symptoms any time prior to 2020. The first step was to create a data-driven model using LASSO regularized logistic regression, the covariates of which were used to develop aggregate covariates for the second step where the COVER scores were developed using a smaller set of features. These 3 COVER scores were then externally validated on patients with 1) influenza or flu-like symptoms and 2) confirmed or suspected COVID-19 diagnosis across 5 databases from South Korea, Spain, and the United States. Outcomes included i) hospitalization with pneumonia, ii) hospitalization with pneumonia requiring intensive services or death, and iii) death in the 30 days after index date. RESULTS: Overall, 44,507 COVID-19 patients were included for model validation. We identified 7 predictors (history of cancer, chronic obstructive pulmonary disease, diabetes, heart disease, hypertension, hyperlipidemia, kidney disease) which combined with age and sex discriminated which patients would experience any of our three outcomes. The models achieved good performance in influenza and COVID-19 cohorts. For COVID-19 the AUC ranges were, COVER-H: 0.69-0.81, COVER-I: 0.73-0.91, and COVER-F: 0.72-0.90. Calibration varied across the validations with some of the COVID-19 validations being less well calibrated than the influenza validations. CONCLUSIONS: This research demonstrated the utility of using a proxy disease to develop a prediction model. The 3 COVER models with 9-predictors that were developed using influenza data perform well for COVID-19 patients for predicting hospitalization, intensive services, and fatality. The scores showed good discriminatory performance which transferred well to the COVID-19 population. There was some miscalibration in the COVID-19 validations, which is potentially due to the difference in symptom severity between the two diseases. A possible solution for this is to recalibrate the models in each location before use.


Subject(s)
COVID-19 , Influenza, Human , Pneumonia , COVID-19 Testing , Humans , Influenza, Human/epidemiology , SARS-CoV-2 , United States
9.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-307499

ABSTRACT

Background: Thromboembolism and thrombocytopenia have emerged as potential adverse events associated with vaccines against SARS-CoV-2. We compared rates of thromboembolism and thrombocytopenia following vaccination with BNT162b2 and ChAdOx1 with expected rates. Rates for people with COVID-19 were estimated to provide context. Methods: Primary care data from Catalonia, Spain, informed the analysis. Study participants were vaccinated with BNT162b2 or ChAdOx1 (27/12/2020-19/05/2021), diagnosed with COVID-19 (1/09/2020-1/03/2021) or present as of 1/01/2017. Outcomes included venous thromboembolism (VTE), arterial thromboembolism (ATE), thrombocytopenia, and thrombosis with thrombocytopenia syndrome (TTS). Incidence rates were estimated in the 21 and 90 days after vaccination and COVID-19 diagnosis, respectively, and up to 31/03/2019 for background rates. Age indirectly standardised incidence ratios (SIR) were estimated. Findings: We included 945,941 BNT162b2 (778,534 with 2 doses), 426,272 ChAdOx1, 222,710 COVID-19, and 4,570,149 background participants. SIRs for VTE were 1.29 [95% CI 1.13-1.48] and 0.90 [0.76-1.07] after first- and second-dose BNT162b2, and 1.15 [0.83-1.58] after first-dose ChAdOx1. The SIR for VTE in COVID-19 was 8.04 [7.37-8.78]. SIRs for thrombocytopenia were 1.35 (1.30-1.41) and 1.19 (1.14-1.25) after first- and second-dose BNT162b2, 1.03 (0.93-1.14) after first-dose ChAdOx1 and 3.52 (3.39 to 3.67) for COVID-19. Rates of ATE were similar to expected rates for BNT162b2 and ChAdOx1, as were rates of TTS for BNT162b2, while fewer than 5 such events were seen for ChAdOx1. Interpretation: Safety profiles of BNT162b2 and ChAdOx1 were similar. A safety signal was seen for VTE after first-dose of BNT162b2. Although confidence intervals were wider, a similar estimate was seen for first-dose of ChAdOx1. The 1.3 fold increase in the rate of VTE after first-dose of BNT162b2 compared with an 8 fold increase after diagnosis of COVID-19. No safety signals were seen for ATE or TTS. Further research is needed to investigate the causality in the observed associations. Funding Information: This study was funded by the European Medicines Agency in the form of a competitive tender (Lot ROC No EMA/2017/09/PE). Declaration of Interests: DPA’s research group has received research grants from the European Medicines Agency, from the Innovative Medicines Initiative, from Amgen, Chiesi, and from UCB Biopharma;and consultancy or speaker fees from Astellas, Amgen and UCB Biopharma. Peter Rijnbeek works for a research institute who receives/received unconditional research grants from Yamanouchi, Pfizer-Boehringer Ingelheim, GSK, Amgen, UCB, Novartis, Astra-Zeneca, Chiesi, Janssen Research and Development, none of which relate to the content of this work. Katia Verhamme works for a research institute who receives/received unconditional research grants from Yamanouchi, Pfizer-Boehringer Ingelheim, GSK, Amgen, UCB, Novartis, Astra-Zeneca, Chiesi, none of which relate to the content of this work .All other authors have no conflicts of interest to declare.Ethics Approval Statement: This study was approved by the Clinical Research Ethics Committee of the IDIAPJGol (project code: 21/054-PCV).

10.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-327397

ABSTRACT

ABSTRACT Background The surge of treatments for COVID-19 in the ongoing pandemic presents an exemplar scenario with low prevalence of a given treatment and high outcome risk. Motivated by that, we conducted a simulation study for treatment effect estimation in such scenarios. We compared the performance of two methods for addressing confounding during the process of estimating treatment effects, namely disease risk scores (DRS) and propensity scores (PS) using different machine learning algorithms. Methods Monte Carlo simulated data with 25 different scenarios of treatment prevalence, outcome risk, data complexity, and sample size were created. PS and DRS matching with 1: 1 ratio were applied with logistic regression with least absolute shrinkage and selection operator (LASSO) regularization, multilayer perceptron (MLP), and eXtreme Gradient Boosting (XgBoost). Estimation performance was evaluated using relative bias and corresponding confidence intervals. Results Bias in treatment effect estimation increased with decreasing treatment prevalence regardless of matching method. DRS resulted in lower bias compared to PS when treatment prevalence was less than 10%, under strong confounding and nonlinear nonadditive data setting. However, DRS did not outperform PS under linear data setting and small sample size, even when the treatment prevalence was less than 10%. PS had a comparable or lower bias to DRS when treatment prevalence was common or high (10% - 50%). All three machine learning methods had similar performance, with LASSO and XgBoost yielding the lowest bias in some scenarios. Decreasing sample size or adding nonlinearity and non-additivity in data improved the performance of both PS and DRS. Conclusions Under strong confounding with large sample size DRS reduced bias compared to PS in scenarios with low treatment prevalence (less than 10%), whilst PS was preferable for the study of treatments with prevalence greater than 10%, regardless of the outcome prevalence. Key Messages When handling nonlinear nonadditive data with strong confounding, DRS estimated by machine learning methods outperforms PS in scenarios with low treatment prevalence (less than 10%). However, if having linear data and small sample size data with strong confounding, we did not observe DRS outperformed PS even when treatment prevalence was less than 10%. Our results suggested that using PS performed better compared to DRS in tackling strong confounding problems with treatment prevalence greater than 10%. Small sample size increased bias for both DRS and PS methods, and it affected DRS more than PS.

11.
Int J Cancer ; 150(5): 782-794, 2022 03 01.
Article in English | MEDLINE | ID: covidwho-1607528

ABSTRACT

The relationship between cancer and coronavirus disease 2019 (COVID-19) infection and severity remains poorly understood. We conducted a population-based cohort study between 1 March and 6 May 2020 describing the associations between cancer and risk of COVID-19 diagnosis, hospitalisation and COVID-19-related death. Data were obtained from the Information System for Research in Primary Care (SIDIAP) database, including primary care electronic health records from ~80% of the population in Catalonia, Spain. Cancer was defined as any primary invasive malignancy excluding non-melanoma skin cancer. We estimated adjusted hazard ratios (aHRs) for the risk of COVID-19 (outpatient) clinical diagnosis, hospitalisation (with or without a prior COVID-19 diagnosis) and COVID-19-related death using Cox proportional hazard regressions. Models were estimated for the overall cancer population and by years since cancer diagnosis (<1 year, 1-5 years and ≥5 years), sex, age and cancer type; and adjusted for age, sex, smoking status, deprivation and comorbidities. We included 4 618 377 adults, of which 260 667 (5.6%) had a history of cancer. A total of 98 951 individuals (5.5% with cancer) were diagnosed, and 6355 (16.4% with cancer) were directly hospitalised with COVID-19. Of those diagnosed, 6851 were subsequently hospitalised (10.7% with cancer), and 3227 died without being hospitalised (18.5% with cancer). Among those hospitalised, 1963 (22.5% with cancer) died. Cancer was associated with an increased risk of COVID-19 diagnosis (aHR: 1.08; 95% confidence interval [1.05-1.11]), direct COVID-19 hospitalisation (1.33 [1.24-1.43]) and death following hospitalisation (1.12 [1.01-1.25]). These associations were stronger for patients recently diagnosed with cancer, aged <70 years, and with haematological cancers. These patients should be prioritised in COVID-19 vaccination campaigns and continued non-pharmaceutical interventions.


Subject(s)
COVID-19 Testing/methods , COVID-19/mortality , Adolescent , Adult , Aged , Female , History, 21st Century , Hospitalization , Humans , Male , Middle Aged , SARS-CoV-2 , Spain/epidemiology , Young Adult
12.
Int J Cancer ; 150(5): 782-794, 2022 03 01.
Article in English | MEDLINE | ID: covidwho-1568104

ABSTRACT

The relationship between cancer and coronavirus disease 2019 (COVID-19) infection and severity remains poorly understood. We conducted a population-based cohort study between 1 March and 6 May 2020 describing the associations between cancer and risk of COVID-19 diagnosis, hospitalisation and COVID-19-related death. Data were obtained from the Information System for Research in Primary Care (SIDIAP) database, including primary care electronic health records from ~80% of the population in Catalonia, Spain. Cancer was defined as any primary invasive malignancy excluding non-melanoma skin cancer. We estimated adjusted hazard ratios (aHRs) for the risk of COVID-19 (outpatient) clinical diagnosis, hospitalisation (with or without a prior COVID-19 diagnosis) and COVID-19-related death using Cox proportional hazard regressions. Models were estimated for the overall cancer population and by years since cancer diagnosis (<1 year, 1-5 years and ≥5 years), sex, age and cancer type; and adjusted for age, sex, smoking status, deprivation and comorbidities. We included 4 618 377 adults, of which 260 667 (5.6%) had a history of cancer. A total of 98 951 individuals (5.5% with cancer) were diagnosed, and 6355 (16.4% with cancer) were directly hospitalised with COVID-19. Of those diagnosed, 6851 were subsequently hospitalised (10.7% with cancer), and 3227 died without being hospitalised (18.5% with cancer). Among those hospitalised, 1963 (22.5% with cancer) died. Cancer was associated with an increased risk of COVID-19 diagnosis (aHR: 1.08; 95% confidence interval [1.05-1.11]), direct COVID-19 hospitalisation (1.33 [1.24-1.43]) and death following hospitalisation (1.12 [1.01-1.25]). These associations were stronger for patients recently diagnosed with cancer, aged <70 years, and with haematological cancers. These patients should be prioritised in COVID-19 vaccination campaigns and continued non-pharmaceutical interventions.


Subject(s)
COVID-19 Testing/methods , COVID-19/mortality , Adolescent , Adult , Aged , Female , History, 21st Century , Hospitalization , Humans , Male , Middle Aged , SARS-CoV-2 , Spain/epidemiology , Young Adult
13.
2021.
Preprint in English | Other preprints | ID: ppcovidwho-294340

ABSTRACT

Background Thrombosis with thrombocytopenia syndrome (TTS) has been reported among individuals vaccinated with adenovirus-vectored COVID-19 vaccines. In this study we describe the background incidence of TTS in 6 European countries. Methods Electronic medical records from France, Netherlands, Italy, Germany, Spain, and the United Kingdom informed the study. Incidence rates of cerebral venous sinus thrombosis (CVST), splanchnic vein thrombosis (SVT), deep vein thrombosis (DVT), pulmonary embolism (PE), and stroke, all with concurrent thrombocytopenia, were estimated among the general population between 2017 to 2019. A range of additional adverse events of special interest for COVID-19 vaccinations were also studied in a similar manner. Findings A total of 25,432,658 individuals were included. Background rates ranged from 1.0 (0.7 to 1.4) to 8.5 (7.4 to 9.9) per 100,000 person-years for DVT with thrombocytopenia, from 0.5 (0.3 to 0.6) to 20.8 (18.9 to 22.8) for PE with thrombocytopenia, from 0.1 (0.0 to 0.1) to 2.5 (2.2 to 2.7) for SVT with thrombocytopenia, and from 0.2 (0.0 to 0.4) to 30.9 (28.6 to 33.3) for stroke with thrombocytopenia. CVST with thrombocytopenia was only identified in one database, with incidence rate of 0.1 (0.1 to 0.2) per 100,000 person-years. The incidence of TTS increased with age, with those affected typically having more comorbidities and greater medication use than the general population. TTS was also more often seen in men than women. A sizeable proportion of those affected were seen to have been taking antithrombotic and anticoagulant therapies prior to their TTS event. Interpretation Although rates vary across databases, TTS has consistently been seen to be a very rare event among the general population. While still very rare, rates of TTS are typically higher among older individuals, and those affected were also seen to generally be male and have more comorbidities and greater medication use than the general population. Funding This study was funded by the European Medicines Agency (EMA/2017/09/PE Lot 3).

14.
J Clin Endocrinol Metab ; 106(12): e5030-e5042, 2021 11 19.
Article in English | MEDLINE | ID: covidwho-1546810

ABSTRACT

CONTEXT: A comprehensive understanding of the association between body mass index (BMI) and coronavirus disease 2019 (COVID-19) is still lacking. OBJECTIVE: To investigate associations between BMI and risk of COVID-19 diagnosis, hospitalization with COVID-19, and death after a COVID-19 diagnosis or hospitalization (subsequent death), accounting for potential effect modification by age and sex. DESIGN: Population-based cohort study. SETTING: Primary care records covering >80% of the Catalan population, linked to regionwide testing, hospital, and mortality records from March to May 2020. PARTICIPANTS: Adults (≥18 years) with at least 1 measurement of weight and height. MAIN OUTCOME MEASURES: Hazard ratios (HR) for each outcome. RESULTS: We included 2 524 926 participants. After 67 days of follow-up, 57 443 individuals were diagnosed with COVID-19, 10 862 were hospitalized with COVID-19, and 2467 had a subsequent death. BMI was positively associated with being diagnosed and hospitalized with COVID-19. Compared to a BMI of 22 kg/m2, the HR (95% CI) of a BMI of 31 kg/m2 was 1.22 (1.19-1.24) for diagnosis and 1.88 (1.75-2.03) and 2.01 (1.86-2.18) for hospitalization without and with a prior outpatient diagnosis, respectively. The association between BMI and subsequent death was J-shaped, with a modestly higher risk of death among individuals with BMIs ≤ 19 kg/m2 and a more pronounced increasing risk for BMIs ≥ 40 kg/m2. The increase in risk for COVID-19 outcomes was particularly pronounced among younger patients. CONCLUSIONS: There is a monotonic association between BMI and COVID-19 diagnosis and hospitalization risks but a J-shaped relationship with mortality. More research is needed to unravel the mechanisms underlying these relationships.


Subject(s)
Body Mass Index , COVID-19/etiology , COVID-19/mortality , Hospitalization/statistics & numerical data , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19 Testing , Cohort Studies , Female , Hospital Mortality , Humans , Male , Middle Aged , Mortality , Risk Factors , Spain/epidemiology , Young Adult
15.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-292668

ABSTRACT

Small trials have suggested that heterologous vaccination with first-dose ChAdOx1 and second-dose BNT162b2 may generate a better immune response than homologous vaccination with two doses of ChAdOx1. We used linked data from Catalonia (Spain), where those aged <60 who received a first dose of ChAdOx1 could choose between ChAdOx1 and BNT162b2 for their second dose. Comparable cohorts were obtained after exact-matching 14,325/17,849 (80.3%) people receiving heterologous vaccination to 14,325/149,386 (9.6%) receiving homologous vaccination by age, sex, region, and date of second dose. Of these, 238 (1.7%) in the heterologous and 389 (2.7%) in the homologous groups developed COVID-19 between 1st June 2021 and 11th October 2021. The resulting hazard ratio (95% confidence interval) was 0.61 [ 0.52-0.71 ], favouring heterologous vaccination, with a Number Needed to Treat of 94.9 [ 71.8 - 139.8 ]. The two groups had similar testing rates and safety outcomes. Sensitivity and negative control outcome analyses confirmed these findings. In conclusion, we demonstrate that a heterologous vaccination schedule with ChAdOx1 followed by BNT162b2 was more efficacious than and similarly safe to homologous vaccination with two doses of ChAdOx1. Most of the infections in our study occurred when Delta was the predominant SARS-CoV-2 variant in Spain. These data agree with previous phase 2 randomised trials.

16.
Sci Rep ; 11(1): 18812, 2021 09 22.
Article in English | MEDLINE | ID: covidwho-1434151

ABSTRACT

Different strategies have been used to maximise the effect of COVID-19 vaccination campaigns in Europe. We modelled the impact of different prioritisation choices and dose intervals on infections, hospitalisations, mortality, and public health restrictions. An agent-based model was built to quantify the impact of different vaccination strategies over 6 months. Input parameters were derived from published phase 3 trials and official European figures. We explored the effect of prioritising vulnerable people, care-home staff and residents, versus contagious groups; and the impact of dose intervals ranging from 3 to 12 weeks. Prioritising vulnerable people, rather than the most contagious, led to higher numbers of COVID-19 infections, whilst reducing mortality, hospital admissions, and public health restrictions. At a realistic vaccination speed of ≤ 0·1% population/day, separating doses by 12 weeks (vs a baseline scenario of 3 weeks) reduced hospitalisations, mortality, and restrictions for vaccines with similar first- and second-dose efficacy (e.g., the Oxford-AstraZeneca and Moderna vaccines), but not for those with lower first vs second-dose efficacy (e.g., the Pfizer/BioNTech vaccine). Mass vaccination will dramatically reduce the effect of COVID-19 on Europe's health and economy. Early vaccination of vulnerable populations will reduce mortality, hospitalisations, and public health restrictions compared to prioritisation of the most contagious people. The choice of interval between doses should be based on expected vaccine availability and first-dose efficacy, with 12-week intervals preferred over shorter intervals in most realistic scenarios.


Subject(s)
COVID-19 Vaccines/administration & dosage , COVID-19/prevention & control , Mass Vaccination/methods , Mass Vaccination/statistics & numerical data , COVID-19/epidemiology , Cohort Studies , Computer Simulation , Disease Susceptibility , Europe/epidemiology , Hospitalization/statistics & numerical data , Humans , Immunization Schedule , Models, Theoretical , Public Health/methods , Time Factors , Vulnerable Populations
17.
Head Neck ; 43(12): 3743-3756, 2021 12.
Article in English | MEDLINE | ID: covidwho-1409182

ABSTRACT

BACKGROUND: Optimal timing for tracheotomy for critically ill COVID-19 patients requiring invasive mechanical ventilation (IMV) is not established. METHODS: Multicenter prospective cohort including all COVID-19 patients admitted to intensive care units (ICUs) in 36 hospitals who required tracheotomy during first pandemic wave. With a target emulation trial framework, we studied the causal effects of early (7-10 days) versus late (>10 days) tracheotomy (LT) on time from tracheotomy to weaning, postoperative mortality, and tracheotomy complications. RESULTS: Of 696 patients, 20.4% received early tracheotomy (ET). ET was associated with faster weaning (hazard ratio [HR] [95% confidence interval, CI]: 1.25 [1.00-1.56]) without differences in mortality (HR [95% CI]: 0.85 [0.60-1.21]) or complications (adjusted rate ratio [95% CI]: 0.56 [0.23-1.33]). CONCLUSIONS: ET had a similar or lower post-tracheotomy weaning time than LT, potentially shortening IMV and ICU stays, without changing complication or mortality rates in COVID-19 patients.


Subject(s)
COVID-19 , Respiration, Artificial , Critical Care , Humans , Intensive Care Units , Prospective Studies , SARS-CoV-2 , Tracheotomy
18.
Pediatrics ; 148(3)2021 09.
Article in English | MEDLINE | ID: covidwho-1394618

ABSTRACT

OBJECTIVES: To characterize the demographics, comorbidities, symptoms, in-hospital treatments, and health outcomes among children and adolescents diagnosed or hospitalized with coronavirus disease 2019 (COVID-19) and to compare them in secondary analyses with patients diagnosed with previous seasonal influenza in 2017-2018. METHODS: International network cohort using real-world data from European primary care records (France, Germany, and Spain), South Korean claims and US claims, and hospital databases. We included children and adolescents diagnosed and/or hospitalized with COVID-19 at age <18 between January and June 2020. We described baseline demographics, comorbidities, symptoms, 30-day in-hospital treatments, and outcomes including hospitalization, pneumonia, acute respiratory distress syndrome, multisystem inflammatory syndrome in children, and death. RESULTS: A total of 242 158 children and adolescents diagnosed and 9769 hospitalized with COVID-19 and 2 084 180 diagnosed with influenza were studied. Comorbidities including neurodevelopmental disorders, heart disease, and cancer were more common among those hospitalized with versus diagnosed with COVID-19. Dyspnea, bronchiolitis, anosmia, and gastrointestinal symptoms were more common in COVID-19 than influenza. In-hospital prevalent treatments for COVID-19 included repurposed medications (<10%) and adjunctive therapies: systemic corticosteroids (6.8%-7.6%), famotidine (9.0%-28.1%), and antithrombotics such as aspirin (2.0%-21.4%), heparin (2.2%-18.1%), and enoxaparin (2.8%-14.8%). Hospitalization was observed in 0.3% to 1.3% of the cohort diagnosed with COVID-19, with undetectable (n < 5 per database) 30-day fatality. Thirty-day outcomes including pneumonia and hypoxemia were more frequent in COVID-19 than influenza. CONCLUSIONS: Despite negligible fatality, complications including hospitalization, hypoxemia, and pneumonia were more frequent in children and adolescents with COVID-19 than with influenza. Dyspnea, anosmia, and gastrointestinal symptoms could help differentiate diagnoses. A wide range of medications was used for the inpatient management of pediatric COVID-19.


Subject(s)
COVID-19 , Adolescent , Age Distribution , COVID-19/complications , COVID-19/diagnosis , COVID-19/drug therapy , COVID-19/epidemiology , Child , Child, Preschool , Cohort Studies , Comorbidity , Databases, Factual , Diagnosis, Differential , Female , France/epidemiology , Germany/epidemiology , Hospitalization/statistics & numerical data , Humans , Infant , Infant, Newborn , Influenza, Human/complications , Influenza, Human/diagnosis , Influenza, Human/epidemiology , Male , Republic of Korea/epidemiology , Spain/epidemiology , Symptom Assessment , Time Factors , Treatment Outcome , United States/epidemiology
19.
BMJ ; 374: n1868, 2021 08 18.
Article in English | MEDLINE | ID: covidwho-1365155

ABSTRACT

OBJECTIVE: To determine associations of BNT162b2 vaccination with SARS-CoV-2 infection and hospital admission and death with covid-19 among nursing home residents, nursing home staff, and healthcare workers. DESIGN: Prospective cohort study. SETTING: Nursing homes and linked electronic medical record, test, and mortality data in Catalonia on 27 December 2020. PARTICIPANTS: 28 456 nursing home residents, 26 170 nursing home staff, and 61 791 healthcare workers. MAIN OUTCOME MEASURES: Participants were followed until the earliest outcome (confirmed SARS-CoV-2 infection, hospital admission or death with covid-19) or 26 May 2021. Vaccination status was introduced as a time varying exposure, with a 14 day run-in after the first dose. Mixed effects Cox models were fitted to estimate hazard ratios with index month as a fixed effect and adjusted for confounders including sociodemographics, comorbidity, and previous medicine use. RESULTS: Among the nursing home residents, SARS-CoV-2 infection was found in 2482, 411 were admitted to hospital with covid-19, and 450 died with covid-19 during the study period. In parallel, 1828 nursing home staff and 2968 healthcare workers were found to have SARS-CoV-2 infection, but fewer than five were admitted or died with covid-19. The adjusted hazard ratio for SARS-CoV-2 infection after two doses of vaccine was 0.09 (95% confidence interval 0.08 to 0.11) for nursing home residents, 0.20 (0.17 to 0.24) for nursing home staff, and 0.13 (0.11 to 0.16) for healthcare workers. Adjusted hazard ratios for hospital admission and mortality after two doses of vaccine were 0.05 (0.04 to 0.07) and 0.03 (0.02 to 0.04), respectively, for nursing home residents. Nursing home staff and healthcare workers recorded insufficient events for mortality analysis. CONCLUSIONS: Vaccination was associated with 80-91% reduction in SARS-CoV-2 infection in all three cohorts and greater reductions in hospital admissions and mortality among nursing home residents for up to five months. More data are needed on longer term effects of covid-19 vaccines.


Subject(s)
COVID-19 Vaccines/therapeutic use , COVID-19/mortality , Health Personnel/statistics & numerical data , Homes for the Aged/statistics & numerical data , Nursing Homes/statistics & numerical data , Patient Admission/statistics & numerical data , Adult , Aged , Aged, 80 and over , COVID-19/prevention & control , Female , Humans , Male , Middle Aged , Proportional Hazards Models , Prospective Studies , SARS-CoV-2 , Spain/epidemiology , Treatment Outcome
20.
J Clin Endocrinol Metab ; 106(12): e5030-e5042, 2021 11 19.
Article in English | MEDLINE | ID: covidwho-1322963

ABSTRACT

CONTEXT: A comprehensive understanding of the association between body mass index (BMI) and coronavirus disease 2019 (COVID-19) is still lacking. OBJECTIVE: To investigate associations between BMI and risk of COVID-19 diagnosis, hospitalization with COVID-19, and death after a COVID-19 diagnosis or hospitalization (subsequent death), accounting for potential effect modification by age and sex. DESIGN: Population-based cohort study. SETTING: Primary care records covering >80% of the Catalan population, linked to regionwide testing, hospital, and mortality records from March to May 2020. PARTICIPANTS: Adults (≥18 years) with at least 1 measurement of weight and height. MAIN OUTCOME MEASURES: Hazard ratios (HR) for each outcome. RESULTS: We included 2 524 926 participants. After 67 days of follow-up, 57 443 individuals were diagnosed with COVID-19, 10 862 were hospitalized with COVID-19, and 2467 had a subsequent death. BMI was positively associated with being diagnosed and hospitalized with COVID-19. Compared to a BMI of 22 kg/m2, the HR (95% CI) of a BMI of 31 kg/m2 was 1.22 (1.19-1.24) for diagnosis and 1.88 (1.75-2.03) and 2.01 (1.86-2.18) for hospitalization without and with a prior outpatient diagnosis, respectively. The association between BMI and subsequent death was J-shaped, with a modestly higher risk of death among individuals with BMIs ≤ 19 kg/m2 and a more pronounced increasing risk for BMIs ≥ 40 kg/m2. The increase in risk for COVID-19 outcomes was particularly pronounced among younger patients. CONCLUSIONS: There is a monotonic association between BMI and COVID-19 diagnosis and hospitalization risks but a J-shaped relationship with mortality. More research is needed to unravel the mechanisms underlying these relationships.


Subject(s)
Body Mass Index , COVID-19/etiology , COVID-19/mortality , Hospitalization/statistics & numerical data , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19 Testing , Cohort Studies , Female , Hospital Mortality , Humans , Male , Middle Aged , Mortality , Risk Factors , Spain/epidemiology , Young Adult
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