Clusters of post-acute COVID-19 symptoms: a latent class analysis across 9 databases and 7 countries (preprint)

Prior evidence has suggested the multisystem symptomatic manifestations of post-acute COVID-19 condition (PCC). Here we conducted a network cluster analysis of 24 WHO proposed symptoms to identify potential latent subclasses of PCC. Individuals with a positive test of or diagnosed with SARS-CoV-2 after 09/2020 and with at least one symptom within ≥ 90 to 365 days following infection were included. Sub-analyses were conducted among people with ≥ 3 different symptoms. Summary characteristics were provided for each cluster. All analyses were conducted separately in 9 databases from 7 countries, including data from primary care, hospitals, national health claims and national health registries, allowing to validate clusters across the different healthcare settings. 787,078 persons with PCC were included. Single-symptom clusters were common across all databases, particularly for joint pain, anxiety, depression and allergy. Complex clusters included anxiety-depression and abdominal-gastrointestinal symptoms. Substantial heterogeneity within and between PCC clusters was seen across healthcare settings. Current definitions of PCC should be critically reviewed to reflect this variety in clinical presentation.

Socioeconomic inequalities in COVID-19 infection and vaccine uptake among children and adolescents in Catalonia, Spain (preprint)

IMPORTANCE The relationship between socioeconomic deprivation and COVID-19 infection and vaccination among children and adolescents remains unclear. OBJECTIVE To investigate the association between deprivation and COVID-19 vaccine uptake and infection among children and adolescents before and after the vaccination rollout in Catalonia, Spain. DESIGN AND SETTING Population-based cohort study using primary care electronic health records from the Information System for Research in Primary Care. Individuals were followed 3 months before the start of the vaccination campaign in Spain and 3 months after the vaccination rollout among adolescents and children. PARTICIPANTS Children (5-11 years) and adolescents (12-15 years) with at least 1 year of prior history observation available and without missing deprivation data. EXPOSURE Deprivation, assessed using an ecological socioeconomic deprivation index (SDI) score for census tract urban areas and categorized into quintiles. MAIN OUTCOMES AND MEASURES COVID-19 infection and COVID-19 vaccination. For each outcome, we calculated cumulative incidence and crude Cox proportional-hazard models by SDI quintiles, and estimated hazard ratios (HRs) of COVID-19 infection and vaccine uptake relative to the least deprived quintile, Q1. RESULTS Before COVID-19 vaccination rollout, 290,625 children and 179,685 adolescents were analyzed. Increased HR of deprivation was associated with a higher risk of COVID-19 infection in both children (Q5: 1.55 [95% CI, 1.47 - 1.63]) and adolescents (Q5: 1.36 [95% CI, 1.29 - 1.43]). After the rollout, this pattern changed among children, with lower risk of infection in more deprived areas (Q5: 0.62 [95% CI, 0.61 - 0.64]). Vaccine uptake was higher among adolescents (72.6%) than children (44.8%), but in both age groups, non-vaccination was more common among those living in more deprived areas (39.3% and 74.6% in Q1 vs. 26.5% and 66.9% in Q5 among children and adolescents, respectively). CONCLUSIONS AND RELEVANCE In this cohort study, children and adolescents living in deprived areas were at higher risk of COVID-19 non-vaccination. Socioeconomic disparities in COVID-19 infection were also evident before vaccine rollout, with a higher infection risk in deprived areas across age groups. Our findings suggest that changes in the association between deprivation and infections among children after the vaccine rollout were likely due to testing disparities.

The role of COVID-19 vaccines in preventing post COVID-19 thromboembolic and cardiovascular complications: a multinational cohort study (preprint)

ImportanceThe overall effects of vaccination on the risk of cardiac, and venous and arterial thromboembolic complications following COVID-19 remain unclear. ObjectiveWe studied the association between COVID-19 vaccination and the risk of acute and subacute COVID-19 cardiac and thromboembolic complications. DesignMultinational staggered cohort study, based on national vaccination campaign rollouts. SettingNetwork study using electronic health records from primary care records from the UK, primary care data linked to hospital data from Spain, and national insurance claims from Estonia. ParticipantsAll adults with a prior medical history of [≥]180 days, with no history of COVID-19 or previous COVID-19 vaccination at the beginning of vaccine rollout were eligible. ExposureVaccination status was used as a time-varying exposure. Vaccinated individuals were classified by vaccine brand according to the first dose received. Main OutcomesPost COVID-19 complications including myocarditis, pericarditis, arrhythmia, heart failure (HF), venous (VTE) and arterial thromboembolism (ATE) up to 1 year after SARS-CoV-2 infection. MeasuresPropensity Score overlap weighting and empirical calibration based on negative control outcomes were used to minimise bias due to observed and unobserved confounding, respectively. Fine-Gray models were fitted to estimate sub-distribution Hazard Ratios (sHR) for each outcome according to vaccination status. Random effect meta-analyses were conducted across staggered cohorts and databases. ResultsOverall, 10.17 million vaccinated and 10.39 million unvaccinated people were included. Vaccination was consistently associated with reduced risks of acute (30-day) and subacute post COVID-19 VTE and HF: e.g., meta-analytic sHR 0.34 (95%CI, 0.27-0.44) and 0.59 (0.50-0.70) respectively for 0-30 days, sHR 0.58 (0.48 - 0.69) and 0.71 (0.59 - 0.85) respectively for 90-180 days post COVID-19. Additionally, reduced risks of ATE, myocarditis/pericarditis and arrhythmia were seen, but mostly in the acute phase (0-30 days post COVID-19). ConclusionsCOVID-19 vaccination reduced the risk of post COVID-19 complications, including cardiac and thromboembolic outcomes. These effects were more pronounced for acute (1-month) post COVID-19 outcomes, consistent with known reductions in disease severity following breakthrough vs unvaccinated SARS-CoV-2 infection. RelevanceThese findings highlight the importance of COVID-19 vaccination to prevent cardiovascular outcomes after COVID-19, beyond respiratory disease. Key PointsO_ST_ABSQuestionC_ST_ABSWhat is the impact of COVID-19 vaccination to prevent cardiac complications and thromboembolic events following a SARS-CoV-2 infection? FindingsResults from this multinational cohort study showed that COVID-19 vaccination reduced risk for acute and subacute COVID-19 heart failure, as well as venous and arterial thromboembolic events following SARS-CoV-2 infection. MeaningThese findings highlight yet another benefit of vaccination against COVID-19, and support the recommendations for COVID-19 vaccination even in people at high cardiovascular risk.

The burden of long COVID: a multinational cohort analysis of Spanish and UK data including SARS-CoV-2 infections, reinfections, and matched contemporaneous test negative controls (preprint)

As limited data was available on the effect of persisting COVID-19 symptoms, we characterised long COVID and identified key symptoms associated with persistent disease. Using primary care data from Spain and UK, we estimated incidence rates of long COVID in the population and among COVID-19 patients over time. Subsequently, we investigated which WHO-listed symptoms were particularly differential for long COVID by comparing their frequency in COVID-19 patients vs matched test-negative controls. Lastly, we compared persistent symptoms after first infections vs. reinfections. Fortunately, the proportion of COVID-19 cases resulting in long COVID declined over the study period.  Risk for altered smell/taste, dyspnoea, and fatigue were consistently higher in long COVID patient vs controls [RR between 5.97-1.09]. All persistent symptoms were less common after reinfection than first infection. More research is needed into the definition of long COVID, and the effect of interventions to minimise the risk and impact of persistent symptoms.

Establishing and characterising large COVID-19 cohorts after mapping the Information System for Research in Primary Care in Catalonia to the OMOP Common Data Model (preprint)

Background Few datasets have been established that capture the full breadth of COVID-19 patient interactions with a health system. Our first objective was to create a COVID-19 dataset that linked primary care data to COVID-19 testing, hospitalisation, and mortality data at a patient level. Our second objective was to provide a descriptive analysis of COVID-19 outcomes among the general population and describe the characteristics of the affected individuals. Methods We mapped patient-level data from Catalonia, Spain, to the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). More than 3,000 data quality checks were performed to assess the readiness of the database for research. Subsequently, to summarise the COVID-19 population captured, we established a general population cohort as of the 1st March 2020 and identified outpatient COVID-19 diagnoses or positive test results for SARS-CoV-2, hospitalisations with COVID-19, and COVID-19 deaths during follow-up, which went up until 30th June 2021. Findings Mapping data to the OMOP CDM was performed and high data quality was observed. The mapped database was used to identify a total of 5,870,274 individuals, who were included in the general population cohort as of 1st March 2020. Over follow up, 604,472 had either an outpatient COVID-19 diagnosis or positive test result, 58,991 had a hospitalisation with COVID-19, 5,642 had an ICU admission with COVID-19, and 11,233 had a COVID-19 death. People who were hospitalised or died were more commonly older, male, and with more comorbidities. Those admitted to ICU with COVID-19 were generally younger and more often male than those hospitalised in general and those who died. Interpretation We have established a comprehensive dataset that captures COVID-19 diagnoses, test results, hospitalisations, and deaths in Catalonia, Spain. Extensive data checks have shown the data to be fit for use. From this dataset, a general population cohort of 5.9 million individuals was identified and their COVID-19 outcomes over time were described. Funding Generalitat de Catalunya and European Health Data and Evidence Network (EHDEN).

“Association between COVID-19 vaccination, infection, and risk of Guillain-Barre syndrome, Bell’s palsy, encephalomyelitis and transverse myelitis: a population-based cohort and self-controlled case series analysis” (preprint)

ABSTRACT OBJECTIVE We aimed to study the association between COVID-19 vaccines, SARS-CoV-2 infection, and the risk of immune-mediated neurological events. METHODS Design Population-based historical rate comparison study and self-controlled case series (SCCS) analysis. Setting Primary care records from the United Kingdom. Participants Individuals who received the first dose of ChAdOx1 or BNT162b2 between 8 December 2020 and 6 March 2021. A cohort with a first positive RT-PCR test for SARS-CoV-2 between 1 September 2020 and 28 February 2021 was used for comparison. Main outcome measures Outcomes included Guillain-Barre syndrome (GBS), Bell’s palsy, encephalomyelitis, and transverse myelitis. Incidence rates were estimated in the 28 days post first-dose vaccine, 90 days post-COVID-19, and between 2017 to 2019 for the general population cohort for background rates. Indirectly standardised incidence ratios (SIRs) were estimated. Adjusted incidence rate ratios (IRR) were estimated from the SCCS when sufficient statistical power was reached. Results We included 1,868,767 ChAdOx1 and 1,661,139 BNT162b2 vaccinees; 299,311 people infected with COVID-19; and 2,290,537 from the general population. SIRs for GBS were 1.91 [95% CI: 0.86 to 4.26] after ChAdOx1, 1.29 [0.49 to 3.45] after BNT162b2, and 5.20 [1.95 to 13.85] after COVID-19. In the same cohorts, SIRs for Bell’s palsy were 1.34 [1.05 to 1.72], 1.15 [0.88 to 1.50], and 1.23 [0.80 to 1.89], and for encephalomyelitis 1.62 [0.61 to 4.31], 0.86 [0.22 to 3.46], and 11.05 [5.27 to 23.17], respectively. Transverse myelitis was too rare to analyse (n<5 in all cohorts). SCCS analysis was only conducted for Bell’s palsy due to limited statistical power. We found no association between either vaccine and Bell’s palsy, with an IRR of 1.10 [0.81 to 1.46] and 1.15 [0.87 to 1.49] for BNT162b2 and ChAdOx1, respectively. Conclusions We found no consistent association between either vaccine and any of the studied neuroimmune adverse events studied. Conversely, we found a 5-fold increase in risk of GBS and an 11-fold of encephalomyelitis following COVID-19.

The impact of the COVID-19 pandemic on diagnoses of common mental health disorders in adults in Catalonia, Spain (preprint)

ObjectivesTo investigate how incidence trends of anxiety and depressive disorders have been affected by the COVID-19 pandemic. DesignPopulation-based cohort study. SettingObservational cohort study from 2018 to 2021 using the Information System for Research in Primary Care (SIDIAP) database in Catalonia, Spain. Participants4,255,847 individuals aged 18 or older in SIDIAP on 1 March, 2018 with no prior history of anxiety and depressive disorders. Primary and secondary outcomes measuresIncidence of anxiety and depressive disorders prior to COVID-19 (March, 2018 to February, 2020), during the COVID-19 lockdown (March to June, 2020) and post-lockdown periods (from July, 2020 to March, 2021) were calculated. Forecasted rates over COVID-19 periods were estimated using negative binomial regression models based on previous data. The percentage reduction was estimated by comparing forecasted versus observed events, overall and by age, sex and socioeconomic status. ResultsThe incidence rates per 100,000 person-months of anxiety and depressive disorders were 171.0 (95%CI: 170.2-171.8) and 46.6 (46.2-47.0), respectively, during the pre-lockdown period. We observed an increase of 39.7% (95%PI: 26.5 to 53.3) in incident anxiety diagnoses compared to the expected in March, 2020, followed by a reduction of 16.9% (8.6 to 24.5) during the post-lockdown periods. A reduction of incident depressive disorders occurred during the lockdown and post-lockdown periods (46.6% [38.9 to 53.1] and 23.2% [12.0 to 32.7], respectively). Reductions were higher among adults aged 18 to 34 and individuals living in most deprived areas. ConclusionsThe COVID-19 pandemic in Catalonia was associated with an initial increase in anxiety disorders diagnosed in primary care, but a reduction in cases as the pandemic continued. Diagnoses of depressive disorders were lower than expected throughout the pandemic. Summary boxO_ST_ABSWhat is already known on this topicC_ST_ABS- While previous self-reported studies have provided evidence of increased mental health burden during the initial phase of the COVID-19 pandemic, a number of studies observed that fewer diagnoses were made in primary care settings than would have been expected during the initial stages of the pandemic. - Population data that examine the impact of COVID-19 on temporal trends of incident cases of common mental health disorders are lacking in Catalonia, Spain. What this study adds- This study has quantified the impact of the COVID-19 pandemic on trends of incidence of anxiety and depressive disorders among adults living in Catalonia. - Reductions in incident cases of anxiety and depressive disorders were higher for young adults and people living in most deprived areas. - Incident diagnoses of anxiety and depressive disorders have not been fully recovered to what would have been expected.

Thrombosis and thrombocytopenia after vaccination against and infection with SARS-CoV-2: a population-based cohort analysis (preprint)

Objectives To calculate the observed rates of thrombosis and thrombocytopenia following vaccination against SARS-CoV-2, infection with SARS-CoV-2, and to compare them to background (expected) rates in the general population. Design Cohort study using routinely collected primary care records. Setting Routine practice in the United Kingdom. Participants Two mutually exclusive vaccinated cohorts included people vaccinated with either ChAdOx1 or BNT162b2 between 8 December 2020 and 6 March 2021. A third cohort consisted of people newly infected with SARS-Cov-2 identified by a first positive RT-PCR test between 1 September 2020 and 28 February 2021. The fourth general population cohort for background rates included those people with a visit between 1 January 2017 and 31 December 2019. In total, we included 1,868,767 ChAdOx1 and 1,661,139 BNT162b2 vaccinees, 299,311 people infected with SARS-CoV-2, and 2,290,537 people from the general population. Interventions First-dose of either ChAdOx1 or BNT162b2 Main outcome measures Outcomes included venous thrombosis, arterial thrombosis, thrombocytopenia, and thrombosis with thrombocytopenia. Outcome rates were estimated for recipients of the ChAdOx1 or BNT162b2 vaccines, for people infected with SARS-CoV-2, and background rates in the general population. Indirectly standardized incidence ratios (SIR) were estimated. Results We included 1,868,767 ChAdOx1 and 1,661,139 BNT162b2 vaccinees, 299,311 people infected with SARS-CoV-2, and 2,290,537 people from the general population for background rates. The SIRs for pulmonary embolism were 1.23 [95% CI, 1.09-1.39] after vaccination with ChAdOx1, 1.21 [1.07-1.36] after vaccination with BNT162b2, and 15.31 [14.08 to 16.65] for infection with SARS-CoV-2. The SIRs for thrombocytopenia after vaccination were 1.25 [1.19 to 1.31] for ChAdOx1 and 0.99 (0.94 to 1.04) for BNT162b2. Rates of deep vein thrombosis and arterial thrombosis were similar among those vaccinated and the general population. Conclusions ChAdOx1 and BNT162b2 had broadly similar safety profiles. Thrombosis rates after either vaccine were mostly similar to those of the general population. Rates of pulmonary embolism increased 1.2-fold after either vaccine and 15-fold with SARS-CoV-2 infection. Thrombocytopenia was more common among recipients of ChAdOx1 but not of BNT162b2.

Thromboembolic Events and Thrombosis With Thrombocytopenia After COVID-19 Infection and Vaccination in Catalonia, Spain (preprint)

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).

Cancer and the risk of COVID-19 diagnosis, hospitalisation, and death: a population-based multi-state cohort study including 4,618,377 adults in Catalonia, Spain (preprint)

Objectives To investigate the associations between cancer and risk of outpatient COVID-19 diagnosis, hospitalisation, and COVID-19-related death, overall and by years since cancer diagnosis (<1-year, 1-5-years, >5-years), sex, age, and cancer type. Design Population-based cohort study Setting Primary care electronic health records including ∼80% of the population in Catalonia, Spain, linked to hospital and mortality records between 1 March and 6 May 2020. Participants Individuals aged ≥18 years with at least one year of prior medical history available from the general population. Cancer was defined as any prior diagnosis of a primary invasive malignancy excluding non-melanoma skin cancer. Main outcome measures Cause-specific hazard ratios (aHR) with 95% confidence intervals for each outcome. Estimates were adjusted by age, sex, deprivation, smoking status, and comorbidities. Results We included 4,618,377 adults, of which 260,667 (5.6%) had a history of cancer. Patients with cancer were older and had more comorbidities than cancer-free patients. A total of 98,951 individuals (5.5% with cancer) were diagnosed and 6,355 (16.4% with cancer) were directly hospitalised (no prior diagnosis) with COVID-19. Of those diagnosed, 6,851 were subsequently hospitalised (10.7% with cancer) and 3,227 died without being hospitalised (18.5% with cancer). Among those hospitalised, 1,963 (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 a COVID-19 hospitalisation (1.12 [1.01-1.25]). These associations were stronger for patients recently diagnosed with cancer, aged <70 years, and with haematological cancers. Conclusions Patients recently diagnosed with cancer, aged <70 years, or with haematological cancers are a high-risk population for COVID-19 diagnosis and severity. These patients should be prioritised in COVID-19 vaccination campaigns and continued non-pharmaceutical interventions. What is already known on this subject Prior studies addressing the relationship between cancer and COVID-19 infection and adverse outcomes have found conflicting results The majority of these studies had small sample sizes, were not population-based (i.e. restricted to hospitalised patients), thus increasing the risks of selection and collider bias. In addition, they used different definitions for cancer (i.e. some included only patients with active cancer, while others focused on specific cancer types, etc.), which limits the comparability of their findings, and only a few analysed the effect of cancer across different patient subgroups. What this study adds We conducted a population-based cohort study to analyse the associations between having a prior diagnosis of cancer and the risks of COVID-19 diagnosis, hospitalisation and COVID-19-related deaths from 1 March to 6 May 2020. In a population of 4,618,377 adults, we found that 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 a COVID-19 hospitalisation (1.12 [1.01-1.25]). These risks were higher for patients recently diagnosed with cancer (within the last year), younger than 70 years, or with haematological cancers. We also found a particularly high risk of COVID-19 hospitalisation and death among patients with lung and bladder cancer.

Background rates of five thrombosis with thrombocytopenia syndromes of special interest for COVID-19 vaccine safety surveillance: incidence between 2017 and 2019 and patient profiles from 25.4 million people in six European countries (preprint)

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).

Cancer and the Risk of COVID-19 Diagnosis, Hospitalisation, and Death: A Population-Based Multi-State Cohort Study Including 4,618,377 Adults in Catalonia, Spain (preprint)

Background: The relationship between cancer and COVID-19 infection and severity is poorly understood. We described the associations between cancer and risk of COVID-19 diagnosis, hospitalisation, and COVID-19-related death.Methods: Population-based cohort study between 1 March and 6 May 2020, using electronic health records from the SIDIAP database including ~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, >5-years), sex, age, and cancer type (haematological or solid); and adjusted for age, sex, smoking status, deprivation, and comorbidities.Findings: We included 4,618,377 adults, of which 260,667 (5.6%) had a history of cancer. Patients with cancer were older and had more comorbidities than cancer-free patients. A total of 98,951 individuals (5.5% with cancer) were diagnosed and 6,355 (16.4% with cancer) were directly hospitalised (no prior diagnosis) with COVID-19. Of those diagnosed, 6,851 were subsequently hospitalised (10.7% with cancer) and 3,227 died without being hospitalised (18.5% with cancer). Among those hospitalised, 1,963 (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 a COVID-19 hospitalisation (1.12 [1.01-1.25]). These associations were stronger for patients recently diagnosed with cancer, aged <70 years, and with haematological cancers.Interpretation: Patients recently diagnosed with cancer, aged <70 years, or with haematological cancers are a high-risk population for COVID-19 diagnosis and severity. These patients should be prioritised in COVID-19 vaccination campaigns and continued non-pharmaceutical interventions.Funding: This project was funded by the Health Department from the Generalitat de Catalunya with a grant for research projects on SARS-CoV-2 and COVID-19 disease organized by the Direcció General de Recerca i Innovació en Salut. This project has also received support from the European Health Data and Evidence Network (EHDEN) project. EHDEN received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 806968. The JU receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA. The University of Oxford received a grant related to this work from the Bill & Melinda Gates Foundation (Investment ID INV-016201), and partial support from the UK National Institute for Health Research (NIHR) Oxford Biomedical Research Centre. ER was supported by Instituto de Salud Carlos III (grant number CM20/00174). DPA is funded through a National Institute for Health Research (NIHR) Senior Research Fellowship (Grant number SRF-2018-11-ST2-004). The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health.Declaration of Interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: DPA reports grants and others from AMGEN; grants, non-financial support and other from UCB Biopharma; grants from Les Laboratoires Servier, outside the submitted work; and Janssen, on behalf of IMI-funded EHDEN and EMIF consortiums, and Synapse Management Partners have supported training programmes organised by DPA's department and open for external participants. No other relationships or activities that could appear to have influenced the submitted work.Ethics Approval Statement: This study was approved by the Clinical Research Ethics Committee of the IDIAPJGol (project code: 20/070-PCV)

Characterizing the incidence of adverse events of special interest for COVID-19 vaccines across eight countries: a multinational network cohort study (preprint)

BackgroundAs large-scale immunization programs against COVID-19 proceed around the world, safety signals will emerge that need rapid evaluation. We report population-based, age- and sex- specific background incidence rates of potential adverse events of special interest (AESI) in eight countries using thirteen databases. MethodsThis multi-national network cohort study included eight electronic medical record and five administrative claims databases from Australia, France, Germany, Japan, Netherlands, Spain, the United Kingdom, and the United States, mapped to a common data model. People observed for at least 365 days before 1 January 2017, 2018, or 2019 were included. We based study outcomes on lists published by regulators: acute myocardial infarction, anaphylaxis, appendicitis, Bells palsy, deep vein thrombosis, disseminated intravascular coagulation, encephalomyelitis, Guillain-Barre syndrome, hemorrhagic and non-hemorrhagic stroke, immune thrombocytopenia, myocarditis/pericarditis, narcolepsy, pulmonary embolism, and transverse myelitis. We calculated incidence rates stratified by age, sex, and database. We pooled rates across databases using random effects meta-analyses. We classified meta-analytic estimates into Council of International Organizations of Medical Sciences categories: very common, common, uncommon, rare, or very rare. FindingsWe analysed 126,661,070 people. Rates varied greatly between databases and by age and sex. Some AESI (e.g., myocardial infarction, Guillain-Barre syndrome) increased with age, while others (e.g., anaphylaxis, appendicitis) were more common in young people. As a result, AESI were classified differently according to age. For example, myocardial infarction was very rare in children, rare in women aged 35-54 years, uncommon in men and women aged 55-84 years, and common in those aged [≥]85 years. InterpretationWe report robust baseline rates of prioritised AESI across 13 databases. Age, sex, and variation between databases should be considered if background AESI rates are compared to event rates observed with COVID-19 vaccines.

A standardized analytics pipeline for reliable and rapid development and validation of prediction models using observational health data (preprint)

Background and Objective As a response to the ongoing COVID-19 pandemic, several prediction models have been rapidly developed, with the aim of providing evidence-based guidance. However, no COVID-19 prediction model in the existing literature has been found to be reliable. Models are commonly assessed to have a risk of bias, often due to insufficient reporting, use of non-representative data, and lack of large-scale external validation. In this paper, we present the Observational Health Data Sciences and Informatics (OHDSI) analytics pipeline for patient-level prediction as a standardized approach for rapid yet reliable development and validation of prediction models. We demonstrate how our analytics pipeline and open-source software can be used to answer important prediction questions while limiting potential causes of bias (e.g., by validating phenotypes, specifying the target population, performing large-scale external validation and publicly providing all analytical source code). Methods We show step-by-step how to implement the pipeline for the question: ‘In patients hospitalized with COVID-19, what is the risk of death 0 to 30 days after hospitalization’. We develop models using six different machine learning methods in a US claims database containing over 20,000 COVID-19 hospitalizations and externally validate the models using data containing over 45,000 COVID-19 hospitalizations from South Korea, Spain, and the US. Results Our open-source tools enabled us to efficiently go end-to-end from problem design to reliable model development and evaluation. When predicting death in patients hospitalized for COVID-19 adaBoost, random forest, gradient boosting machine, and decision tree yielded similar or lower internal and external validation discrimination performance compared to L1-regularized logistic regression, whereas the MLP neural network consistently resulted in lower discrimination. L1-regularized logistic regression models were well calibrated. Conclusion Our results show that following the OHDSI analytics pipeline for patient-level prediction can enable the rapid development towards reliable prediction models. The OHDSI tools and pipeline are open source and available to researchers around the world.

Alpha-1 blockers and susceptibility to COVID-19 in benign prostate hyperplasia patients : an international cohort study (preprint)

Alpha-1 blockers, often used to treat benign prostate hyperplasia (BPH), have been hypothesized to prevent COVID-19 complications by minimising cytokine storms release. We conducted a prevalent-user active-comparator cohort study to assess association between alpha-1 blocker use and risks of three COVID-19 outcomes: diagnosis, hospitalization, and hospitalization requiring intensive services. Our study included 2.6 and 0.46 million users of alpha-1 blockers and of alternative BPH therapy during the period between November 2019 and January 2020, found in electronic health records from Spain (SIDIAP) and the United States (Department of Veterans Affairs, Columbia University Irving Medical Center, IQVIA OpenClaims, Optum DOD, Optum EHR). We estimated hazard ratios using state-of-the-art techniques to minimize potential confounding, including large-scale propensity score matching/stratification and negative control calibration. We found no differential risk for any of COVID-19 outcome, pointing to the need for further research on potential COVID-19 therapies.

Unraveling COVID-19: a large-scale characterization of 4.5 million COVID-19 cases using CHARYBDIS (preprint)

Background: Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response [1,2]. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) [3] Characterizing Health Associated Risks, and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD.Methods: We conducted a descriptive cohort study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub [4]. Findings: We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts, and are available in an interactive website: https://data.ohdsi.org/Covid19CharacterizationCharybdis/. Interpretation: CHARYBDIS findings provide benchmarks that contribute to our understanding of COVID-19 progression, management and evolution over time. This can enable timely assessment of real-world outcomes of preventative and therapeutic options as they are introduced in clinical practice.

Characteristics and outcomes of 118,155 COVID-19 individuals with a history of cancer in the United States and Spain (preprint)

PurposeWe aimed to describe the demographics, cancer subtypes, comorbidities and outcomes of patients with a history of cancer with COVID-19 from March to June 2020. Secondly, we compared patients hospitalized with COVID-19 to patients diagnosed with COVID-19 and patients hospitalized with influenza. MethodsWe conducted a cohort study using eight routinely-collected healthcare databases from Spain and the US, standardized to the Observational Medical Outcome Partnership common data model. Three cohorts of patients with a history of cancer were included: i) diagnosed with COVID-19, ii) hospitalized with COVID-19, and iii) hospitalized with influenza in 2017-2018. Patients were followed from index date to 30 days or death. We reported demographics, cancer subtypes, comorbidities, and 30-day outcomes. ResultsWe included 118,155 patients with a cancer history in the COVID-19 diagnosed and 41,939 in the COVID-19 hospitalized cohorts. The most frequent cancer subtypes were prostate and breast cancer (range: 5-19% and 1-14% in the diagnosed cohort, respectively). Hematological malignancies were also frequent, with non-Hodgkins lymphoma being among the 5 most common cancer subtypes in the diagnosed cohort. Overall, patients were more frequently aged above 65 years and had multiple comorbidities. Occurrence of death ranged from 8% to 14% and from 18% to 26% in the diagnosed and hospitalized COVID-19 cohorts, respectively. Patients hospitalized with influenza (n=242,960) had a similar distribution of cancer subtypes, sex, age and comorbidities but lower occurrence of adverse events. ConclusionPatients with a history of cancer and COVID-19 have advanced age, multiple comorbidities, and a high occurence of COVID-19-related events. Additionaly, hematological malignancies were frequent in these patients.This observational study provides epidemiologic characteristics that can inform clinical care and future etiological studies.

Body mass index and risk of COVID-19 diagnosis, hospitalisation, and death: a population-based multi-state cohort analysis including 2,524,926 people in Catalonia, Spain (preprint)

Objective: To investigate associations between body mass index (BMI) and risk of COVID-19 diagnosis, hospitalisation with COVID-19, and COVID-19-related death, accounting for potential effect modification by age and sex. Design: Population-based cohort study. Setting: Primary care records covering >80% of the Catalonian population (Spain), linked to regionwide testing, hospital, and mortality records from March to May 2020. Participants: People aged [≥]18 years with at least one measurement of weight and height from the general population and with at least one year of prior medical history available. Main outcome measures: Cause-specific hazard ratios (HR) with 95% confidence intervals for each outcome. Results: Overall, 2,524,926 participants were followed up for a median of 67 days. A total of 57,443 individuals were diagnosed with COVID-19, 10,862 were hospitalised with COVID-19, and 2,467 had a COVID-19-related death. BMI was positively associated with being diagnosed as well as hospitalised with COVID-19. Compared to a BMI of 22kg/m2, the HR (95%CI) of a BMI of 31kg/m2 was 1.22 (1.19-1.24) for COVID-19 diagnosis, and 1.88 (1.75-2.03) and 2.01 (1.86-2.18) for hospitalisation without and with a prior outpatient diagnosis, respectively. The relation between BMI and risk of COVID-19 related death was J-shaped. There was a modestly higher risk of death among individuals with BMIs[≤]19 kg/m2 and a more pronounced increasing risk for BMIs [≥]37 kg/m2 and [≥]40kg/m2 among those who were previously hospitalised with COVID-19 and diagnosed with COVID-19 in outpatient settings, respectively. 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 infection and hospitalisation risks, but a J-shaped one with mortality. More research is needed to unravel the mechanisms underlying these relationships.

Use of dialysis, tracheostomy, and extracorporeal membrane oxygenation among 240,392 patients hospitalized with COVID-19 in the United States (preprint)

Objective To estimate the proportion of patients hospitalized with COVID-19 who undergo dialysis, tracheostomy, and extracorporeal membrane oxygenation (ECMO). Design A network cohort study. Setting Six databases from the United States containing routinely-collected patient data: HealthVerity, Premier, IQVIA Open Claims, Optum EHR, Optum SES, and VA-OMOP. Patients Patients hospitalized with a clinical diagnosis or a positive test result for COVID-19. Interventions Dialysis, tracheostomy, and ECMO. Measurements and Main Results 240,392 patients hospitalized with COVID-19 were included (22,887 from HealthVerity, 139,971 from IQVIA Open Claims, 29,061 from Optum EHR, 4,336 from OPTUM SES, 36,019 from Premier, and 8,118 from VA-OMOP). Across the six databases, 9,703 (4.04% [95% CI: 3.96% to 4.11%]) patients received dialysis, 1,681 (0.70% [0.67% to 0.73%]) had a tracheostomy, and 398 (0.17% [95% CI: 0.15% to 0.18%]) patients underwent ECMO over the 30 days following hospitalization. Use of ECMO was generally concentrated among patients who were younger, male, and with fewer comorbidities except for obesity. Tracheostomy was used for a similar proportion of patients regardless of age, sex, or comorbidity. While dialysis was used for a similar proportion among younger and older patients, it was more frequent among male patients and among those with chronic kidney disease. Conclusion Use of dialysis among those hospitalized with COVID-19 is high at around 4%. Although less than one percent of patients undergo tracheostomy and ECMO, the absolute numbers of patients who have undergone these interventions is substantial and can be expected to continue grow given the continuing spread of the COVID-19.