For example, the Chinese Center for Disease Control and Prevention reported in a study of 44,672 individuals (1,023 deaths) that cardiovascular disease, hypertension, diabetes, respiratory disease and cancers were associated with an increased risk of death 5 however, correction for relationships with age was not possible. Various pre-existing conditions have also been associated with increased risk. On the same day in the UK, there had been 206,715 confirmed cases of COVID-19, and 30,615 COVID-19-related deaths 3.Īge and gender are well-established risk factors for severe COVID-19 outcomes: over 90% of the COVID-19-related deaths in the UK have been in people over 60, and 60% in men 4. As of (the date of latest data availability for this study), cases had reached over 3.5 million globally, with more than 240,000 deaths attributed to the virus 1. On 11 March 2020, the World Health Organization (WHO) characterized COVID-19-which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-as a pandemic, after 118,000 cases and 4,291 deaths were reported in 114 countries 2.
#CAUSE OF DEATH EA UPDATE#
More patient records are rapidly being added to OpenSAFELY, we will update and extend our results regularly. We have quantified a range of clinical factors associated with COVID-19-related death in one of the largest cohort studies on this topic so far.
Compared with people of white ethnicity, Black and South Asian people were at higher risk, even after adjustment for other factors (HR 1.48 (1.29–1.69) and 1.45 (1.32–1.58), respectively). COVID-19-related death was associated with: being male (hazard ratio (HR) 1.59 (95% confidence interval 1.53–1.65)) greater age and deprivation (both with a strong gradient) diabetes severe asthma and various other medical conditions. Primary care records of 17,278,392 adults were pseudonymously linked to 10,926 COVID-19-related deaths. Here we used OpenSAFELY to examine factors associated with COVID-19-related death. Working on behalf of NHS England, we created OpenSAFELY-a secure health analytics platform that covers 40% of all patients in England and holds patient data within the existing data centre of a major vendor of primary care electronic health records.
There is unprecedented urgency to understand who is most at risk of severe outcomes, and this requires new approaches for the timely analysis of large datasets. Nature volume 584, pages 430–436 ( 2020) Cite this articleĬoronavirus disease 2019 (COVID-19) has rapidly affected mortality worldwide 1. Key clinical SD predictors identified can aid in risk stratification and potentially guide primary prevention ICD implantation.Factors associated with COVID-19-related death using OpenSAFELY Patients with EA are at significant risk for SD.
#CAUSE OF DEATH EA TV#
In a similar subgroup analysis of patients who underwent TV surgery, all of the above factors except syncope were significantly associated with post-operative SD on multivariable analysis. Prior ventricular tachycardia [hazard ratio (HR) 6.37, P 15 g/dL (HR 2.05, P = 0.026) were multivariable predictors of SD. The 10-, 50-, and 70-year cumulative incidences of SD from birth were 0.8%, 8.3%, and 14.6%, respectively. Cox regression analysis was used to identify clinical and surgical predictors of SD. Sudden death incidence from birth and following tricuspid valve (TV) surgery were estimated using the Kaplan-Meier method. Clinical variables, cardiovascular surgical procedure(s), and cause of death were recorded. We therefore sought to characterize the incidence and risk factors of SD among a large cohort of patients with EA.Īll EA patients who underwent evaluation at a high-volume institution over a 4-decade period were retrospectively reviewed. Ebstein anomaly (EA) can present with both right and left heart abnormalities however, predictors of SD have not been described. Ventricular dysfunction or structural alteration of either ventricle is a well-established risk factor for sudden death (SD).
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