CVD-COVID-UK/COVID-IMPACT

Healthcare Utilisation of 282,080 Individuals with Long COVID Over Two Years: A Multiple Matched Control Cohort Analysis

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A nationwide study of 331 rare diseases among 58 million individuals: prevalence, demographics, and COVID-19 outcomes

section { background: white; color: black; border-radius: 1em; padding: 1em; left: 50% } #inner { display: inline-block; display: flex; align-items: center; justify-content: center } 📺 BHF Data Science Centre seminar by Dr Honghan Wu

Towards mitigating health inequity via machine learning: a nationwide cohort study to develop and validate ethnicity-specific models for prediction of cardiovascular disease risk in COVID-19 patients

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Hospital admissions linked to SARS-CoV-2 infection in children and adolescents: cohort study of 3.2 million first ascertained infections in England

For July's BHF Data Science Centre webinar we were joined by Professor Kate Brown from Great Ormond Street Hospital (GOSH) and Dr Chris Tomlinson from University College London (UCL). They speak about findings from a recent paper, published on 5th July 2023, outlining the impact of COVID-19 on children across England. This study - undertaken as part of the BHF Data Science Centre CVD-COVID-UK/COVID-IMPACT Consortium – looked at 12 million childhood health records across England during the height of the pandemic, and analysed 3.2 million cases of coronavirus infection. The study reveals the extent of severe outcomes in children during the pandemic and could inform public health policies.

Hospital admissions linked to SARS-CoV-2 infection in children and adolescents: cohort study of 3.2 million first ascertained infections in England

section { background: white; color: black; border-radius: 1em; padding: 1em; left: 50% } #inner { display: inline-block; display: flex; align-items: center; justify-content: center } 📺 BHF Data Science Centre seminar by Prof Kate Brown & Dr Chris Tomlinson Twitter thread by Christina Pagel summarising key results

The impact of the COVID-19 pandemic on cardiovascular disease prevention and management

section { background: white; color: black; border-radius: 1em; padding: 1em; left: 50% } #inner { display: inline-block; display: flex; align-items: center; justify-content: center } Twitter thread summarising key results

Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19–a data-driven retrospective cohort study

section { background: white; color: black; border-radius: 1em; padding: 1em; left: 50% } #inner { display: inline-block; display: flex; align-items: center; justify-content: center } Twitter thread by Prof Ami Banerjee summarising key results

Digital ethnicity data in population-wide electronic health records in England: a description of completeness, coverage, and granularity of diversity

section { background: white; color: black; border-radius: 1em; padding: 1em; left: 50% } #inner { display: inline-block; display: flex; align-items: center; justify-content: center } 📺 BHF Data Science Centre seminar by Dr Sara Khalid

Association of COVID-19 With Major Arterial and Venous Thrombotic Diseases: A Population-Wide Cohort Study of 48 Million Adults in England and Wales

section { background: white; color: black; border-radius: 1em; padding: 1em; left: 50% } #inner { display: inline-block; display: flex; align-items: center; justify-content: center } 📺 BHF Data Science Centre seminar by Dr Samantha Ip & Dr Hoda Abbasizanjani

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

section { background: white; color: black; border-radius: 1em; padding: 1em; left: 50% } #inner { display: inline-block; display: flex; align-items: center; justify-content: center } Twitter thread summarising key results