preprint

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

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

Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort

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

Using national electronic health records for pandemic preparedness: validation of a parsimonious model for predicting excess deaths among those with COVID-19

section { background: white; color: black; border-radius: 1em; padding: 1em; left: 50% } #inner { display: inline-block; display: flex; align-items: center; justify-content: center } ❗ Now published in Journal of the Royal Society of Medicine

The adverse impact of COVID-19 pandemic on cardiovascular disease prevention and management in England, Scotland and Wales: A population-scale descriptive analysis of trends in medication data

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 Reecha Sofat and Dr Caroline Dale

A nationwide deep learning pipeline to predict stroke and COVID-19 death in atrial fibrillation

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

Association of COVID-19 with arterial and venous vascular 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

Understanding COVID-19 trajectories from a nationwide linked electronic health record cohort of 56 million people: phenotypes, severity, waves & vaccination

❗ Now published in The Lancet Digital Health Johan H Thygesen, Chris Tomlinson, Sam Hollings, Mehrdad Mizani, Alex Handy, Ashley Akbari, Amitava Banerjee, Jennifer Cooper, Alvina Lai, Ken Li, Bilal Mateen, Naveed Sattar, Reecha Sofat, Ana Torralbo, Honghan Wu, Angela Wood, Jonathan A C Sterne, Christina Pagel, William Whiteley, Cathie Sudlow, Harry Hemingway, Spiros Denaxas, on behalf of the CVD-COVID-UK Consortium (2022).

Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort

❗ Now published in Heart Alex Handy, Amitava Banerjee, Angela Wood, Caroline Dale, Cathie Sudlow, Chris Tomlinson, Daniel Bean, Johan H Thygesen, Mehrdad A Mizani, Michail Katsoulis, Rohan Takhar, Sam Hollings, Spiros Denaxas, Venexia Walker, Richard Dobson, Reecha Sofat & CVD-COVID-UK Consortium (2022).