Contribution of genetics and lifestyle to the risk of major cardiovascular and thromboembolic complications following COVID-19

Clinical determinants for cardiovascular and thromboembolic (CVE) complications of COVID-19 are well-understood, but the roles of genetics and lifestyle remain unknown. We performed a prospective cohort study using UK Biobank, including 25,335 participants with confirmed SARS-CoV-2 infection between March 1, 2020, and September 3, 2021. Outcomes were hospital-diagnosed atrial fibrillation (AF), coronary artery disease (CAD), ischemic stroke (ISS), and venous thromboembolism (VTE) within 90 days post-infection. Heritable risk was represented by validated polygenic risk scores (PRSs). Lifestyle was defined by a composite of nine variables. We estimated adjusted hazard ratios (aHR) and confidence intervals (CI) using Cox proportional hazards models. In the COVID-19 acute phase, PRSs linearly predicted a higher risk of AF (aHR 1.52 per standard deviation increase, 95% CI 1.39 to 1.67), CAD (1.59, 1.40 to 1.81), and VTE (1.30, 1.11 to 1.53), but not ISS (0.92, 0.64 to 1.33). A healthy lifestyle was associated with a substantially lower risk of post-COVID-19 AF (0.70, 0.53 to 0.92), CAD (0.64, 0.44 to 0.91), and ISS (0.28, 0.12 to0.64), but not VTE (0.82, 0.48 to 1.39), compared with an unhealthy lifestyle. No evidence for interactions between genetics and lifestyle was found. Our results demonstrated that population genetics and lifestyle considerably influence cardiovascular complications following COVID-19, with implications for future personalised thromboprophylaxis and healthy lifestyle campaigns to offset the elevated cardiovascular disease burden imposed by the ongoing pandemic.

Genetic risk and incident venous thromboembolism in middle-aged and older adults following 1 Covid-19 vaccination

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

Venous Thromboembolism in Ambulatory Covid-19 patients: Clinical and Genetic Determinants

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

The impact of COVID passport mandates on the number of cases of and hospitalizations with COVID-19 in the UK: a difference-in-differences analysis

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

Comparative effectiveness of the BNT162b2 vs ChAdOx1 vaccine against Covid-19

Although pivotal trials with varying populations and study methods suggest higher efficacy for mRNA than adenoviral Covid-19 vaccines, no direct evidence is available. Here, we conducted a head-to-head comparison of BNT162b2 versus ChAdOx1 against Covid-19. We analysed 235,181 UK Biobank participants aged 50 years or older and vaccinated with one or two doses of BNT162b2 or ChAdOx1. People were followed from the vaccination date until 18/10/2021. Inverse probability weighting was used to minimise confounding and the Cox models to derive hazard ratio. We found that, compared with two doses of ChAdOx1, vaccination with BNT162b2 was associated with 30% lower risks of both SARS-CoV-2 infection and related hospitalisation during the period dominated by the delta variant. Also, this comparative effectiveness was consistent across several subgroups and persisted for at least six months, suggesting no differential waning between the two vaccines. Our findings can inform evidence-based Covid-19 vaccination campaigns and booster strategies.

Characterization of long-term patient-reported symptoms of COVID-19: an analysis of social media data

As the SARS-CoV-2 virus (COVID-19) continues to affect people across the globe, there is limited understanding of the long term implications for infected patients1-3. While some of these patients have documented follow-ups on clinical records, or participate in longitudinal surveys, these datasets are usually designed by clinicians, and not granular enough to understand the natural history or patient experiences of long COVID. In order to get a complete picture, there is a need to use patient generated data to track the long-term impact of COVID-19 on recovered patients in real time. There is a growing need to meticulously characterize these patients experiences, from infection to months post-infection, and with highly granular patient generated data rather than clinician narratives. In this work, we present a longitudinal characterization of post-COVID-19 symptoms using social media data from Twitter. Using a combination of machine learning, natural language processing techniques, and clinician reviews, we mined 296,154 tweets to characterize the post-acute infection course of the disease, creating detailed timelines of symptoms and conditions, and analyzing their symptomatology during a period of over 150 days.

Timing of elective tracheotomy and duration of mechanical ventilation amongst patients admitted to intensive care with severe COVID-19: a multicentre prospective cohort study

BackgroundThe COVID-19 pandemic has strained intensive care unit (ICU) resources. Tracheotomy is the most frequent surgery performed on ICU patients and can affect the duration of ICU care. We studied the association between when tracheotomy occurs and weaning from mechanical ventilation, mortality, and intraoperative and postoperative complications. MethodsMulticentre prospective cohort including all COVID-19 patients admitted to ICUs in 36 hospitals in Spain who received invasive mechanical ventilation and tracheotomy between 11 March and 20 July 2020. We used a target emulation trial framework to study the causal effects of early (7 to 10 days post-intubation) versus late (>10 days) tracheotomy on time from tracheotomy to weaning, postoperative mortality, and tracheotomy complications. Cause-specific Cox models were used for the first two outcomes and Poisson regression for the third, all adjusted for potential confounders. FindingsWe included 696 patients, of whom 142 (20{middle dot}4%) received early tracheotomy. Using late tracheotomy as the reference group, multivariable cause-specific analysis showed that early tracheotomy was associated with faster post-tracheotomy weaning (fully adjusted hazard ratio (HR) [95% confidence interval (CI)]: 1{middle dot}31 [1{middle dot}02 to 1{middle dot}81]) without differences in mortality (fully adjusted HR [95% CI]: 0{middle dot}91 [0{middle dot}56 to 1{middle dot}47]) or intraoperative or postoperative complications (adjusted rate ratio [95% CI]: 0{middle dot}21 [0{middle dot}03 to 1{middle dot}57] and 1{middle dot}49 [0{middle dot}99 to 2{middle dot}24], respectively). InterpretationEarly tracheotomy reduced post-tracheotomy weaning time, resulting in fewer mechanical ventilation days and shorter ICU stays, without changing complication or mortality rates. These results support early tracheotomy for COVID-19 patients when clinically indicated. FundingSupported by the NIHR, FAME, and MRC. Research in contextO_TEXTBOXEvidence before this studyThe optimal timing of tracheotomy for critically ill COVID-19 patients remains controversial. Existing guidelines and recommendations are based on limited experiences with SARS-CoV-1 and expert opinions derived from situations that differ from a pandemic outbreak. Most of the available guidance recommends late tracheotomy (>14 days), mainly due to the potential risk of infection for the surgical team and the high patient mortality rate observed early in the first wave of the COVID-19 pandemic. Recent publications have shown that surgical teams can safely perform tracheotomies for COVID-19 patients if they use adequate personal protective equipment. Early tracheotomy seems to reduce the length of invasive mechanical ventilation without increasing complications, which may release crucial intensive care unit (ICU) beds sooner. The current recommendations do not suggest an optimal time for tracheotomy for COVID-19 patients, and no study has provided conclusions based on objective clinical parameters. Added value of this studyThis is the first study aiming to establish the optimal timing for tracheotomy for critically ill COVID-19 patients requiring invasive mechanical ventilation (IMV). The study prospectively recruited a large multicentre cohort of 696 patients under IMV due to COVID-19 and collected data about the severity of respiratory failure, clinical and ventilatory parameters, and whether patients need to be laid flat during their ICU stay (proned). The analysis focused on the duration of IMV, mortality, and complication rates. We used a prospective cohort study design to compare the exposures of early (performed at day 7 to 10 after starting IMV) versus late (performed after day 10) tracheotomy and set the treatment decision time on the 7th day after orotracheal intubation. Implications of all the available evidenceThe evidence suggests that tracheotomy within 10 days of starting COVID-19 patients on mechanical ventilation allows these patients to be removed from ventilation and discharged from ICU quicker than later tracheotomy, without added complications or increased mortality. This evidence may help to release ventilators and ICU beds more quickly during the pandemic. C_TEXTBOX

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

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.

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

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.

Characteristics, outcomes, and mortality amongst 133,589 patients with prevalent autoimmune diseases diagnosed with, and 48,418 hospitalised for COVID-19: a multinational distributed network cohort analysis

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

Baseline characteristics, management, and outcomes of 55,270 children and adolescents diagnosed with COVID-19 and 1,952,693 with influenza in France, Germany, Spain, South Korea and the United States: an international network cohort study

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.

Baseline phenotype and 30-day outcomes of people tested for COVID-19: an international network cohort including >3.32 million people tested with real-time PCR and >219,000 tested positive for SARS-CoV-2 in South Korea, Spain and the United States

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.

Clinical characteristics, symptoms, management and health outcomes in 8,598 pregnant women diagnosed with COVID-19 compared to 27,510 with seasonal influenza in France, Spain and the US: a network cohort analysis

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

Heterogeneity and temporal variation in the management of COVID-19: a multinational drug utilization study including 71,921 hospitalized patients from China, South Korea, Spain, and the United States of America

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

Characteristics and outcomes of 627 044 COVID-19 patients with and without obesity in the United States, Spain, and the United Kingdom

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.

The natural history of symptomatic COVID-19 in Catalonia, Spain: a multi-state model including 109,367 outpatient diagnoses, 18,019 hospitalisations, and 5,585 COVID-19 deaths among 5,627,520 people

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.

Renin-angiotensin system blockers and susceptibility to COVID-19: a multinational open science cohort study

IntroductionAngiotensin converting enzyme inhibitors (ACEs) and angiotensin receptor blockers (ARBs) could influence infection risk of coronavirus disease (COVID-19). Observational studies to date lack pre-specification, transparency, rigorous ascertainment adjustment and international generalizability, with contradictory results. MethodsUsing electronic health records from Spain (SIDIAP) and the United States (Columbia University Irving Medical Center and Department of Veterans Affairs), we conducted a systematic cohort study with prevalent ACE, ARB, calcium channel blocker (CCB) and thiazide diuretic (THZ) users to determine relative risk of COVID-19 diagnosis and related hospitalization outcomes. The study addressed confounding through large-scale propensity score adjustment and negative control experiments. ResultsFollowing over 1.1 million antihypertensive users identified between November 2019 and January 2020, we observed no significant difference in relative COVID-19 diagnosis risk comparing ACE/ARB vs CCB/THZ monotherapy (hazard ratio: 0.98; 95% CI 0.84 - 1.14), nor any difference for mono/combination use (1.01; 0.90 - 1.15). ACE alone and ARB alone similarly showed no relative risk difference when compared to CCB/THZ monotherapy or mono/combination use. Directly comparing ACE vs. ARB demonstrated a moderately lower risk with ACE, non-significant for monotherapy (0.85; 0.69 - 1.05) and marginally significant for mono/combination users (0.88; 0.79 - 0.99). We observed, however, no significant difference between drug-classes for COVID-19 hospitalization or pneumonia risk across all comparisons. ConclusionThere is no clinically significant increased risk of COVID-19 diagnosis or hospitalization with ACE or ARB use. Users should not discontinue or change their treatment to avoid COVID-19.

Hospitalization and 30-day fatality in 121,263 COVID-19 outpatient cases

BackgroundTo date, characterisation studies of COVID-19 have focussed on hospitalised or intensive care patients. We report for the first time on the natural history of COVID-19 disease from first diagnosis, including both outpatient and hospital care. MethodsData was obtained from SIDIAP, a primary care records database covering >6 million people (>80% of the population of Catalonia), linked to COVID-19 RT-PCR tests, hospital emergency and inpatient, and mortality registers. All participants >=15 years, diagnosed with COVID-19 in outpatient between 15th March and 24th April 2020 (10th April for outcome studies) were included. Baseline characteristics, testing, and 30-day outcomes (hospitalisation for COVID-19 and all-cause fatality) were analysed. ResultsA total of 121,263 and 95,467 COVID-19 patients were identified for characterisation and outcome studies, respectively. Women (57.8%) and age 45-54 (20.2%) were predominant. 44,709 were tested, with 32,976 (73.8%) PCR+. From 95,467 cases, a 14.6% [14.4-14.9] were hospitalised in the month after diagnosis, with male predominance (19.2% vs 11.3%), peaking at age 75-84. Overall 30-day fatality was 4.0% [95%CI 3.9%-4.2%], higher in men (4.8%) than women (3.4%), increasing with age, and highest in those residing in nursing homes (25.3% [24.2% to 26.4%]). ConclusionsCOVID-19 is seen in all age-sex strata, but severe forms of disease cluster in older men and nursing home residents. Although initially managed in primary care, 15% of cases require hospitalization within a month, with overall fatality of 4%.

Ethnicity, comorbidity, socioeconomic status, and their associations with COVID-19 infection in England: a cohort analysis of UK Biobank data

ObjectivesRecent data suggest higher COVID-19 rates and severity in Black, Asian, and minority ethnic (BAME) communities. The mechanisms underlying such associations remain unclear. We aimed to study the association between ethnicity and risk of COVID-19 infection and disentangle any correlation with socioeconomic deprivation or previous comorbidity. DesignProspective cohort. SettingUK Biobank linked to Hospital Episode Statistics (HES) and COVID-19 tests until 14 April 2020. ParticipantsUK Biobank participants from England, excluding drop-outs and deaths. Main measuresCOVID-19 infection based on a positive PCR test. Ethnicity was self-reported and classified using Office of National Statistics groups. Socioeconomic status was based on index of multiple deprivation quintiles. Comorbidities were self-reported and completed from HES. AnalysesMultivariable Poisson analysis to estimate incidence rate ratios of COVID-19 infection according to ethnicity, adjusted for socioeconomic status, alcohol drinking, smoking, body mass index, age, sex, and comorbidity. Results415,582 participants were included, with 1,416 tested and 651 positive for COVID-19. The incidence of COVID-19 was 0.61% (95% CI: 0.46%-0.82%) in Black/Black British participants, 0.32% (0.19%-0.56%) in other ethnicities, 0.32% (0.23%-0.47%) in Asian/Asian British, 0.30% (0.11%-0.80%) in Chinese, 0.16% (0.06%-0.41%) in mixed, and 0.14% (0.13%-0.15%) in White. Compared with White participants, Black/Black British participants had an adjusted relative risk (RR) of 3.30 (2.39-4.55), Chinese participants 3.00 (1.11-8.06), Asian/Asian British participants 2.04 (1.36-3.07), other ethnicities 1.93 (1.08-3.45), and mixed ethnicities 1.07 (0.40-2.86). Socioeconomic status (adjusted RR 1.93 (1.51-2.46) for the most deprived), obesity (adjusted RR 1.04 (1.02-1.05) per kg/m2) and comorbid hypertension, chronic obstructive pulmonary disease, asthma, and specific renal diseases were also associated with increased risk of COVID-19. ConclusionsCOVID-19 rates in the UK are higher in BAME communities, those living in deprived areas, obese patients, and patients with previous comorbidity. Public health strategies are needed to reduce COVID-19 infections among the most susceptible groups.

Seek COVER: Development and validation of a personalized risk calculator for COVID-19 outcomes in an international network

ObjectiveTo develop and externally validate COVID-19 Estimated Risk (COVER) scores that quantify a patients risk of hospital admission (COVER-H), requiring intensive services (COVER-I), or fatality (COVER-F) in the 30-days following COVID-19 diagnosis. MethodsWe analyzed a federated network of electronic medical records and administrative claims data from 14 data sources and 6 countries. We developed and validated 3 scores using 6,869,127 patients with a general practice, emergency room, or outpatient visit with diagnosed influenza or flu-like symptoms any time prior to 2020. The scores were validated on patients with confirmed or suspected COVID-19 diagnosis across five databases from South Korea, Spain and the United States. Outcomes included i) hospitalization with pneumonia, ii) hospitalization with pneumonia requiring intensive services or death iii) death in the 30 days after index date. ResultsOverall, 44,507 COVID-19 patients were included for model validation. We identified 7 predictors (history of cancer, chronic obstructive pulmonary disease, diabetes, heart disease, hypertension, hyperlipidemia, kidney disease) which combined with age and sex discriminated which patients would experience any of our three outcomes. The models achieved high performance in influenza. When transported to COVID-19 cohorts, the AUC ranges were, COVER-H: 0.69-0.81, COVER-I: 0.73-0.91, and COVER-F: 0.72-0.90. Calibration was overall acceptable. ConclusionsA 9-predictor model performs well for COVID-19 patients for predicting hospitalization, intensive services and fatality. The models could aid in providing reassurance for low risk patients and shield high risk patients from COVID-19 during de-confinement to reduce the virus impact on morbidity and mortality.