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BackgroundFew 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. MethodsWe 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. FindingsMapping 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. InterpretationWe 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. FundingGeneralitat de Catalunya and European Health Data and Evidence Network (EHDEN).
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OBJECTIVEWe aimed to study the association between COVID-19 vaccines, SARS-CoV-2 infection, and the risk of immune-mediated neurological events. METHODSO_ST_ABSDesignC_ST_ABSPopulation-based historical rate comparison study and self-controlled case series (SCCS) analysis. SettingPrimary care records from the United Kingdom. ParticipantsIndividuals 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 measuresOutcomes included Guillain-Barre syndrome (GBS), Bells 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. ResultsWe 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 Bells 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 Bells palsy due to limited statistical power. We found no association between either vaccine and Bells 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. ConclusionsWe 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.
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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.
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ObjectivesTo 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. DesignCohort study using routinely collected primary care records. SettingRoutine practice in the United Kingdom. ParticipantsTwo 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. InterventionsFirst-dose of either ChAdOx1 or BNT162b2 Main outcome measuresOutcomes 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. ResultsWe 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. ConclusionsChAdOx1 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. Summary boxO_ST_ABSWhat is already known on this topicC_ST_ABSO_LISpontaneous reports of unusual and severe thrombosis with thrombocytopenia syndrome (TTS) raised concerns regarding the safety of adenovirus-based vaccines against SARS-CoV-2 C_LIO_LIIn a cohort study including over 280,000 people aged 18-65 years vaccinated with ChAdOx1 in Denmark and Norway, Potteg[a]rd et al reported increased rates of venous thromboembolic events as well as thrombocytopenia among vaccine recipients. C_LI What this study addsO_LIIn this cohort study, ChAdOx1 and BNT162b2 were seen to have broadly similar safety profiles. C_LIO_LIRates of thrombosis after either vaccine were generally similar to those of the general population. Rates of pulmonary embolism were though 1.2-fold higher than background rates after either vaccine, which compared to 15-fold higher after SARS-CoV-2 infection. C_LIO_LIThrombocytopenia was more common among recipients of ChAdOx1 but not of BNT162b2. C_LI
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ObjectivesTo 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. DesignPopulation-based cohort study SettingPrimary 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. ParticipantsIndividuals 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 measuresCause-specific hazard ratios (aHR) with 95% confidence intervals for each outcome. Estimates were adjusted by age, sex, deprivation, smoking status, and comorbidities. ResultsWe 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. ConclusionsPatients 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 subjectO_LIPrior studies addressing the relationship between cancer and COVID-19 infection and adverse outcomes have found conflicting results C_LIO_LIThe 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. C_LIO_LIIn 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. C_LI What this study addsO_LIWe 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. C_LIO_LIIn 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]). C_LIO_LIThese 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. C_LI
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BackgroundThrombosis 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. MethodsElectronic 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. FindingsA 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. InterpretationAlthough 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. FundingThis study was funded by the European Medicines Agency (EMA/2017/09/PE Lot 3).
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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.
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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.
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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.
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ObjectiveTo 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. DesignPopulation-based cohort study. SettingPrimary care records covering >80% of the Catalonian population (Spain), linked to region-wide testing, hospital, and mortality records from March to May 2020. ParticipantsPeople 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 measuresCause-specific hazard ratios (HR) with 95% confidence intervals for each outcome. ResultsOverall, 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 [≥]40 kg/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. ConclusionsThere 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. Summary boxesO_ST_ABSSection 1: What is already known on this topicC_ST_ABSO_LIA high body mass index (BMI) has previously been associated in a linear and non-linear fashion with an increased risk of multiple health outcomes; these associations may vary by individual factors such as age and sex. C_LIO_LIObesity has been identified as a risk factor for COVID-19 severity and mortality. However, the role of general adiposity in relation to COVID-19 outcomes has mostly been studied by dichotomizing BMI (below or above 30 kg/m2) or by a diagnostic code indicating obesity. C_LIO_LITwo studies have investigated BMI (as a continuous variable) in relation to COVID-19 outcomes, accounting for non-linearity: one conducted in a tested population sample of the UK Biobank found BMI is related in a dose-response manner with the risk of testing positive for COVID-19; another conducted in a hospital setting in New York reported a J-shaped association between BMI and the risk of intubation or death. These studies were limited in sample size and were prone to collider bias due to the participants restriction to tested and hospitalised patients. No studies have described the association between BMI and COVID-19 outcomes across the natural history of the disease (from no disease to symptomatic disease, hospitalisation, and mortality) using data from diverse health settings. C_LI Section 2: What this study addsO_LIWe provide a comprehensive analysis of the association between BMI and the course of the COVID-19 disease in the general population of a Spanish region during the first wave of the pandemic, using linked data capturing outpatient clinical diagnoses, RT-PCR test results, hospitalisations, and mortality (inside and outside of the hospital setting). C_LIO_LIWe found that BMI is positively associated with being diagnosed as well as hospitalised with COVID-19, and is linked in a J-shaped fashion with the risk of COVID-19 related death. C_LIO_LIThe association between BMI and COVID-19 related outcomes is modified by age and sex; particularly, the risk of COVID-19 outcomes related to increased BMI is higher for those aged between 18 and 59 years, compared to those in older age groups. C_LI
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ObjectiveTo estimate the proportion of patients hospitalized with COVID-19 who undergo dialysis, tracheostomy, and extracorporeal membrane oxygenation (ECMO). DesignA network cohort study. SettingSix databases from the United States containing routinely-collected patient data: HealthVerity, Premier, IQVIA Open Claims, Optum EHR, Optum SES, and VA-OMOP. PatientsPatients hospitalized with a clinical diagnosis or a positive test result for COVID-19. InterventionsDialysis, tracheostomy, and ECMO. Measurements and Main Results240,392 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. ConclusionUse 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.
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ObjectivePatients with autoimmune diseases were advised to shield to avoid COVID-19, but information on their prognosis is lacking. We characterised 30-day outcomes and mortality after hospitalisation with COVID-19 among patients with prevalent autoimmune diseases, and compared outcomes after hospital admissions among similar patients with seasonal influenza. DesignMultinational network cohort study SettingElectronic health records data from Columbia University Irving Medical Center (CUIMC) (NYC, United States [US]), Optum [US], Department of Veterans Affairs (VA) (US), Information System for Research in Primary Care-Hospitalisation Linked Data (SIDIAP-H) (Spain), and claims data from IQVIA Open Claims (US) and Health Insurance and Review Assessment (HIRA) (South Korea). ParticipantsAll patients with prevalent autoimmune diseases, diagnosed and/or hospitalised between January and June 2020 with COVID-19, and similar patients hospitalised with influenza in 2017-2018 were included. Main outcome measures30-day complications during hospitalisation and death ResultsWe studied 133,589 patients diagnosed and 48,418 hospitalised with COVID-19 with prevalent autoimmune diseases. The majority of participants were female (60.5% to 65.9%) and aged [≥]50 years. The most prevalent autoimmune conditions were psoriasis (3.5 to 32.5%), rheumatoid arthritis (3.9 to 18.9%), and vasculitis (3.3 to 17.6%). Amongst hospitalised patients, Type 1 diabetes was the most common autoimmune condition (4.8% to 7.5%) in US databases, rheumatoid arthritis in HIRA (18.9%), and psoriasis in SIDIAP-H (26.4%). Compared to 70,660 hospitalised with influenza, those admitted with COVID-19 had more respiratory complications including pneumonia and acute respiratory distress syndrome, and higher 30-day mortality (2.2% to 4.3% versus 6.3% to 24.6%). ConclusionsPatients with autoimmune diseases had high rates of respiratory complications and 30-day mortality following a hospitalization with COVID-19. Compared to influenza, COVID-19 is a more severe disease, leading to more complications and higher mortality. Future studies should investigate predictors of poor outcomes in COVID-19 patients with autoimmune diseases. What is already known about this topicO_LIPatients with autoimmune conditions may be at increased risk of COVID-19 infection andcomplications. C_LIO_LIThere is a paucity of evidence characterising the outcomes of hospitalised COVID-19 patients with prevalent autoimmune conditions. C_LI What this study addsO_LIMost people with autoimmune diseases who required hospitalisation for COVID-19 were women, aged 50 years or older, and had substantial previous comorbidities. C_LIO_LIPatients who were hospitalised with COVID-19 and had prevalent autoimmune diseases had higher prevalence of hypertension, chronic kidney disease, heart disease, and Type 2 diabetes as compared to those with prevalent autoimmune diseases who were diagnosed with COVID-19. C_LIO_LIA variable proportion of 6% to 25% across data sources died within one month of hospitalisation with COVID-19 and prevalent autoimmune diseases. C_LIO_LIFor people with autoimmune diseases, COVID-19 hospitalisation was associated with worse outcomes and 30-day mortality compared to admission with influenza in the 2017-2018 season. C_LI
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ObjectiveMost patients severely affected by COVID-19 have been elderly and patients with underlying chronic disease such as diabetes, cardiovascular disease, or respiratory disease. People living with HIV (PLHIV) may have greater risk of contracting or developing severe COVID-19 due to the underlying HIV infection or higher prevalence of comorbidities. DesignThis is a cohort study, including PLHIV diagnosed, hospitalized, or requiring intensive services for COVID-19. MethodsData sources include routine electronic medical record or claims data from the U.S. and Spain. Patient demographics, comorbidities, and medication history are described. ResultFour data sources had a population of HIV/COVID-19 coinfected patients ranging from 288 to 4606 lives. PLHIV diagnosed with COVID-19 were younger than HIV-negative patients diagnosed with COVID-19. PLHIV diagnosed with COVID-19 diagnosis had similar comorbidities as HIV-negative COVID-19 patients with higher prevalence of those comorbidities and history of severe disease. Treatment regimens were similar between PLHIV diagnosed with COVID-19 or PLHIV requiring intensive services. ConclusionsOur study uses routine practice data to explore HIV impact on COVID-19, providing insight into patient history prior to COVID-19. We found that HIV and COVID-19 coinfected patients have higher prevalence of underlying comorbidities such as cardiovascular and respiratory disease as compared to HIV-negative COVID-19 infected patients. We also found that, across the care cascade, co-infected patients who received intensive services were more likely to have more serious underlying disease or a history of more serious events as compared to PLHIV who were diagnosed with COVID-19.
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ObjectivesTo characterize the demographics, comorbidities, symptoms, in-hospital treatments, and health outcomes among children/adolescents diagnosed or hospitalized with COVID-19. Secondly, to describe health outcomes amongst children/adolescents diagnosed with previous seasonal influenza. DesignInternational network cohort. SettingReal-world data from European primary care records (France/Germany/Spain), South Korean claims and US claims and hospital databases. ParticipantsDiagnosed and/or hospitalized children/adolescents with COVID-19 at age <18 between January and June 2020; diagnosed with influenza in 2017-2018. Main outcome measuresBaseline demographics and comorbidities, symptoms, 30-day in-hospital treatments and outcomes including hospitalization, pneumonia, acute respiratory distress syndrome (ARDS), multi-system inflammatory syndrome (MIS-C), and death. ResultsA total of 55,270 children/adolescents diagnosed and 3,693 hospitalized with COVID-19 and 1,952,693 diagnosed with influenza were studied. Comorbidities including neurodevelopmental disorders, heart disease, and cancer were all more common among those hospitalized vs diagnosed with COVID-19. The most common COVID-19 symptom was fever. Dyspnea, bronchiolitis, anosmia and gastrointestinal symptoms were more common in COVID-19 than influenza. In-hospital treatments for COVID-19 included repurposed medications (<10%), and adjunctive therapies: systemic corticosteroids (6.8% to 37.6%), famotidine (9.0% to 28.1%), and antithrombotics such as aspirin (2.0% to 21.4%), heparin (2.2% to 18.1%), and enoxaparin (2.8% to 14.8%). Hospitalization was observed in 0.3% to 1.3% of the COVID-19 diagnosed cohort, with undetectable (N<5 per database) 30-day fatality. Thirty-day outcomes including pneumonia, ARDS, and MIS-C were more frequent in COVID-19 than influenza. ConclusionsDespite negligible fatality, complications including pneumonia, ARDS and MIS-C were more frequent in children/adolescents with COVID-19 than with influenza. Dyspnea, anosmia and gastrointestinal symptoms could help differential diagnosis. A wide range of medications were used for the inpatient management of pediatric COVID-19. What is already known on this topic?O_LIMost of the early COVID-19 studies were targeted at adult patients, and data concerning children and adolescents are limited. C_LIO_LIClinical manifestations of COVID-19 are generally milder in the pediatric population compared with adults. C_LIO_LIHospitalization for COVID-19 affects mostly infants, toddlers, and children with pre-existing comorbidities. C_LI What this study adds This study comprehensively characterizes a large international cohort of pediatric COVID-19 patients, and almost 2 million with previous seasonal influenza across 5 countries. Although uncommon, pneumonia, acute respiratory distress syndrome (ARDS) and multi-system inflammatory syndrome (MIS-C) were more frequent in children and adolescents diagnosed with COVID-19 than in those with seasonal influenza. Dyspnea, bronchiolitis, anosmia and gastrointestinal symptoms were more frequent in COVID-19, and could help to differentiate pediatric COVID-19 from influenza. A plethora of medications were used during the management of COVID-19 in children and adolescents, with great heterogeneity in the use of antiviral therapies as well as of adjunctive therapies.
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Early identification of symptoms and comorbidities most predictive of COVID-19 is critical to identify infection, guide policies to effectively contain the pandemic, and improve health systems response. Here, we characterised socio-demographics and comorbidity in 3,316,107persons tested and 219,072 persons tested positive for SARS-CoV-2 since January 2020, and their key health outcomes in the month following the first positive test. Routine care data from primary care electronic health records (EHR) from Spain, hospital EHR from the United States (US), and claims data from South Korea and the US were used. The majority of study participants were women aged 18-65 years old. Positive/tested ratio varied greatly geographically (2.2:100 to 31.2:100) and over time (from 50:100 in February-April to 6.8:100 in May-June). Fever, cough and dyspnoea were the most common symptoms at presentation. Between 4%-38% required admission and 1-10.5% died within a month from their first positive test. Observed disparity in testing practices led to variable baseline characteristics and outcomes, both nationally (US) and internationally. Our findings highlight the importance of large scale characterization of COVID-19 international cohorts to inform planning and resource allocation including testing as countries face a second wave.
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OBJECTIVESTo describe comorbidities, symptoms at presentation, medication use, and 30-day outcomes after a diagnosis of COVID-19 in pregnant women, in comparison to pregnant women with influenza. DESIGNMultinational network cohort SETTINGA total of 6 databases consisting of electronic medical records and claims data from France, Spain, and the United States. PARTICIPANTSPregnant women with [≥] 1 year in contributing databases, diagnosed and/or tested positive, or hospitalized with COVID-19. The influenza cohort was derived from the 2017-2018 influenza season. OUTCOMESBaseline patient characteristics, comorbidities and presenting symptoms; 30-day inpatient drug utilization, maternal complications and pregnancy-related outcomes following diagnosis/hospitalization. RESULTS8,598 women diagnosed (2,031 hospitalized) with COVID-19 were included. Hospitalized women had, compared to those diagnosed, a higher prevalence sof pre-existing comorbidities including renal impairment (2.2% diagnosed vs 5.1% hospitalized) and anemia (15.5% diagnosed vs 21.3% hospitalized). The ten most common inpatient treatments were systemic corticosteroids (29.6%), enoxaparin (24.0%), immunoglobulins (21.4%), famotidine (20.9%), azithromycin (18.1%), heparin (15.8%), ceftriaxone (7.9%), aspirin (7.0%), hydroxychloroquine (5.4%) and amoxicillin (3.5%). Compared to 27,510 women with influenza, dyspnea and anosmia were more prevalent in those with COVID-19. Women with COVID-19 had higher frequency of cesarean-section (4.4% vs 3.1%), preterm delivery (0.9% vs 0.5%), and poorer maternal outcomes: pneumonia (12.0% vs 2.7%), ARDS (4.0% vs 0.3%) and sepsis (2.1% vs 0.7%). COVID-19 fatality was negligible (N<5 in each database respectively). CONCLUSIONSComorbidities that were more prevalent with COVID-19 hospitalization (compared to COVID-19 diagnosed) in pregnancy included renal impairment and anemia. Multiple medications were used to treat pregnant women hospitalized with COVID-19, some with little evidence of benefit. Anosmia and dyspnea were indicative symptoms of COVID-19 in pregnancy compared to influenza, and may aid differential diagnosis. Despite low fatality, pregnancy and maternal outcomes were worse in COVID-19 than influenza. WHAT IS ALREADY KNOWN ON THIS TOPICO_LICompared to non-pregnant women of reproductive age, pregnant women are less likely to experience typical COVID-19 symptoms, such as fever and myalgia. C_LIO_LIObesity, high maternal age, and comorbid hypertension and diabetes are risk factors for severe COVID-19 among pregnant women. C_LIO_LIDespite relatively high rates of pneumonia and need for oxygen supplementation, fatality rates in pregnant women with COVID-19 are generally low (<1%). C_LI WHAT THIS STUDY ADDSO_LIAlthough not often recorded, dyspnea and anosmia were more often seen in pregnant women with COVID-19 than in women with seasonal influenza, in 6 databases from 3 countries (US, France, Spain). C_LIO_LIRenal impairment and anemia were more common among hospitalized than diagnosed women with COVID-19 during pregnancy. C_LIO_LIDespite limited data on benefit-risk in pregnancy, a large number of medications were used for inpatient management of COVID-19 in pregnant women: approximately 1 in 3 received corticosteroids (some may have been given for a pregnancy-related indication rather than for COVID-19 treatment), 1 in 4 enoxaparin, and 1 in 5 immunoglobulin, famotidine and azithromycin. C_LIO_LICompared to influenza, there was a higher frequency of pregnancy-related complications (cesarean section and preterm deliveries), as well as poorer maternal outcomes (pneumonia, acute respiratory distress syndrome, sepsis, acute kidney injury, and cardiovascular and thromboembolic events) seen in pregnant women diagnosed with COVID-19. C_LI
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ObjectivesA plethora of medicines have been repurposed or used as adjunctive therapies for COVID-19. We characterized the utilization of medicines as prescribed in routine practice amongst patients hospitalized for COVID-19 in South Korea, China, Spain, and the USA. DesignInternational network cohort SettingHospital electronic health records from Columbia University Irving Medical Centre (NYC, USA), Stanford (CA, USA), Tufts (MA, USA), Premier (USA), Optum EHR (USA), department of veterans affairs (USA), NFHCRD (Honghu, China) and HM Hospitals (Spain); and nationwide claims from HIRA (South Korea) Participantspatients hospitalized for COVID-19 from January to June 2020 Main outcome measuresPrescription/dispensation of any medicine on or 30 days after hospital admission date AnalysesNumber and percentage of users overall and over time Results71,921 people were included: 304 from China, 2,089 from Spain, 7,599 from South Korea, and 61,929 from the USA. A total of 3,455 medicines were identified. Common repurposed medicines included hydroxychloroquine (<2% in NFHCRD to 85.4% in HM), azithromycin (4.9% in NFHCRD to 56.5% in HM), lopinavir/ritonavir (<3% in all US but 34.9% in HIRA and 56.5% in HM), and umifenovir (0% in all except 78.3% in NFHCRD). Adjunctive medicines were used with great variability, with the ten most used treatments being (in descending order): bemiparin, enoxaparin, heparin, ceftriaxone, aspirin, vitamin D, famotidine, vitamin C, dexamethasone, and metformin. Hydroxychloroquine and azithromycin increased rapidly in use in March-April but declined steeply in May-June. ConclusionsMultiple medicines were used in the first months of COVID-19 pandemic, with substantial geographic and temporal variation. Hydroxychloroquine, azithromycin, lopinavir-ritonavir, and umifenovir (in China only) were the most prescribed repurposed medicines. Antithrombotics, antibiotics, H2 receptor antagonists and corticosteroids were often used as adjunctive treatments. Research is needed on the comparative risk and benefit of these treatments in the management of COVID-19. O_TEXTBOXWhat is already known in this topicO_LIDrug repurposing is a common approach in the clinical management of novel diseases and conditions for which there are no available pharmacotherapies C_LIO_LIHydroxychloroquine was widely used in the management of COVID-19 patients during the early phases of the pandemic C_LIO_LIRecent NIH (and other) guidelines recommend the use of concomitant therapies including immune-based, antithrombotic, antibiotic and other treatments C_LI What this study addsO_LIThis study demonstrates great variability and extensive drug repurposing and utilization in the management of COVID-19 patients. C_LIO_LIA wide range of adjunctive treatments has been used, including antithrombotics, antibiotics, H2 receptor antagonists, and systemic corticosteroids. C_LIO_LIEmerging clinical data on the safety and efficacy of hydroxychloroquine and azithromycin impacted their rise and rapid decline in use internationally C_LIO_LIConversely, the use of corticosteroids grew only in more recent months, with little use in the early stages of the pandemic (January to April) C_LI C_TEXTBOX
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BackgroundCOVID-19 may differentially impact people with obesity. We aimed to describe and compare the demographics, comorbidities, and outcomes of obese patients with COVID-19 to those of non-obese patients with COVID-19, or obese patients with seasonal influenza. MethodsWe conducted a cohort study based on outpatient/inpatient care, and claims data from January to June 2020 from the US, Spain, and the UK. We used six databases standardized to the OMOP common data model. We defined two cohorts of patients diagnosed and/or hospitalized with COVID-19. We created corresponding cohorts for patients with influenza in 2017-2018. We followed patients from index date to 30 days or death. We report the frequency of socio-demographics, prior comorbidities, and 30-days outcomes (hospitalization, events, and death) by obesity status. FindingsWe included 627 044 COVID-19 (US: 502 650, Spain: 122 058, UK: 2336) and 4 549 568 influenza (US: 4 431 801, Spain: 115 224, UK: 2543) patients. The prevalence of obesity was higher among hospitalized COVID-19 (range: 38% to 54%) than diagnosed COVID-19 (30% to 47%), or diagnosed (15% to 47%) or hospitalized (27% to 48%) influenza patients. Obese hospitalized COVID-19 patients were more often female and younger than non-obese COVID-19 patients or obese influenza patients. Obese COVID-19 patients were more likely to have prior comorbidities, present with cardiovascular and respiratory events during hospitalization, require intensive services, or die compared to non-obese COVID-19 patients. Obese COVID-19 patients were more likely to require intensive services or die compared to obese influenza patients, despite presenting with fewer comorbidities. InterpretationWe show that obesity is more common amongst COVID-19 than influenza patients, and that obese patients present with more severe forms of COVID-19 with higher hospitalization, intensive services, and fatality than non-obese patients. These data are instrumental for guiding preventive strategies of COVID-19 infection and complications. FundingThe European Health Data & Evidence Network has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 806968. The JU receives support from the European Unions Horizon 2020 research and innovation programme and EFPIA. This research received partial support from the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), US National Institutes of Health, US Department of Veterans Affairs, Janssen Research & Development, and IQVIA. The University of Oxford received funding related to this work from the Bill & Melinda Gates Foundation (Investment ID INV-016201 and INV-019257). APU has received funding from the Medical Research Council (MRC) [MR/K501256/1, MR/N013468/1] and Fundacion Alfonso Martin Escudero (FAME) (APU). VINCI [VA HSR RES 13-457] (SLD, MEM, KEL). JCEL has received funding from the Medical Research Council (MR/K501256/1) and Versus Arthritis (21605). No funders had a direct role in this study. The views and opinions expressed are those of the authors and do not necessarily reflect those of the Clinician Scientist Award programme, NIHR, Department of Veterans Affairs or the United States Government, NHS, or the Department of Health, England. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSPrevious evidence suggests that obese individuals are a high risk population for COVID-19 infection and complications. We searched PubMed for articles published from December 2019 until June 2020, using terms referring to SARS-CoV-2 or COVID-19 combined with terms for obesity. Few studies reported obesity and most of them were limited by small sample sizes and restricted to hospitalized patients. Further, they used different definitions for obesity (i.e. some reported together overweight and obesity, others only reported obesity with BMI>40kg/m2). To date, no study has provided detailed information on the characteristics of obese COVID-19 patients, such as the prevalence of comorbidities or COVID-19 related outcomes. In addition, despite the fact that COVID-19 has been often compared to seasonal influenza, there are no studies assessing whether obese patients with COVID-19 differ from obese patients with seasonal influenza. Added value of this studyWe report the largest cohort of obese patients with COVID-19 and provide information on more than 29 000 aggregate characteristics publicly available. Our findings were consistent across the participating databases and countries. We found that the prevalence of obesity is higher among COVID-19 compared to seasonal influenza patients. Obese patients with COVID-19 are more commonly female and have worse outcomes than non-obese patients. Further, they have worse outcomes than obese patients with influenza, despite presenting with fewer comorbidities. Implications of all the available evidenceOur results show that individuals with obesity present more comorbidities and worse outcomes for COVID-19 than non-obese patients. These findings may be useful in guiding clinical practice and future preventative strategies for obese individuals, as well as provide useful data to support subsequent association studies focussed on obesity and COVID-19.
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BackgroundThe natural history of Coronavirus Disease 2019 (COVID-19) has yet to be fully described, with most previous reports focusing on hospitalised patients. Using linked patient-level data, we set out to describe the associations between age, gender, and comorbidities and the risk of outpatient COVID-19 diagnosis, hospitalisation, and/or related mortality. MethodsA population-based cohort study including all individuals registered in Information System for Research in Primary Care (SIDIAP). SIDIAP includes primary care records covering > 80% of the population of Catalonia, Spain, and was linked to region-wide testing, hospital and mortality records. Outpatient diagnoses of COVID-19, hospitalisations with COVID-19, and deaths with COVID-19 were identified between 1st March and 6th May 2020. A multi-state model was used, with cause-specific Cox survival models estimated for each transition. FindingsA total of 5,627,520 individuals were included. Of these, 109,367 had an outpatient diagnosis of COVID-19, 18,019 were hospitalised with COVID-19, and 5,585 died after either being diagnosed or hospitalised with COVID-19. Half of those who died were not admitted to hospital prior to their death. Risk of a diagnosis with COVID-19 peaked first in middle-age and then again for oldest ages, risk for hospitalisation after diagnosis peaked around 70 years old, with all other risks highest at oldest ages. Male gender was associated with an increased risk for all outcomes other than outpatient diagnosis. The comorbidities studied (autoimmune condition, chronic kidney disease, chronic obstructive pulmonary disease, dementia, heart disease, hyperlipidemia, hypertension, malignant neoplasm, obesity, and type 2 diabetes) were all associated with worse outcomes. InterpretationThere is a continued need to protect those at high risk of poor outcomes, particularly the elderly, from COVID-19 and provide appropriate care for those who develop symptomatic disease. While risks of hospitalisation and death are lower for younger populations, there is a need to limit their role in community transmission. These findings should inform public health strategies, including future vaccination campaigns.
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BackgroundSARS-CoV-2 is straining healthcare systems globally. The burden on hospitals during the pandemic could be reduced by implementing prediction models that can discriminate between patients requiring hospitalization and those who do not. The COVID-19 vulnerability (C-19) index, a model that predicts which patients will be admitted to hospital for treatment of pneumonia or pneumonia proxies, has been developed and proposed as a valuable tool for decision making during the pandemic. However, the model is at high risk of bias according to the Prediction model Risk Of Bias ASsessment Tool and has not been externally validated. MethodsWe followed the OHDSI framework for external validation to assess the reliability of the C-19 model. We evaluated the model on two different target populations: i) 41,381 patients that have SARS-CoV-2 at an outpatient or emergency room visit and ii) 9,429,285 patients that have influenza or related symptoms during an outpatient or emergency room visit, to predict their risk of hospitalization with pneumonia during the following 0 to 30 days. In total we validated the model across a network of 14 databases spanning the US, Europe, Australia and Asia. FindingsThe internal validation performance of the C-19 index was a c-statistic of 0.73 and calibration was not reported by the authors. When we externally validated it by transporting it to SARS-CoV-2 data the model obtained c-statistics of 0.36, 0.53 (0.473-0.584) and 0.56 (0.488-0.636) on Spanish, US and South Korean datasets respectively. The calibration was poor with the model under-estimating risk. When validated on 12 datasets containing influenza patients across the OHDSI network the c-statistics ranged between 0.40-0.68. InterpretationThe results show that the discriminative performance of the C-19 model is low for influenza cohorts, and even worse amongst COVID-19 patients in the US, Spain and South Korea. These results suggest that C-19 should not be used to aid decision making during the COVID-19 pandemic. Our findings highlight the importance of performing external validation across a range of settings, especially when a prediction model is being extrapolated to a different population. In the field of prediction, extensive validation is required to create appropriate trust in a model.
