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<h4>Background</h4> Patients with COVID-19 are thought to be at higher risk of cardiometabolic and pulmonary complications, but quantification of that risk is limited. We aimed to describe the overall burden of these complications in survivors of severe COVID-19. <h4>Methods</h4> Working on behalf of NHS England we used data from the OpenSAFELY platform linking primary care records to death certificate and hospital data. We constructed two cohorts: a COVID-19 cohort consisting of patients discharged following hospitalisation with COVID-19, and a comparison population of patients discharged following hospitalisation with pneumonia in 2019. Outcomes included DVT, PE, ischaemic stroke, MI, heart failure, AKI and new type 2 diabetes diagnosis. Outcome rates from hospital discharge were measured in each cohort, stratified by patient demographics and 30-day period. We fitted Cox regression models to estimate crude and age/sex adjusted hazard ratios comparing outcome rates between the two cohorts. <h4>Results</h4> Amongst the population of 31,569 patients discharged following hospitalisation with COVID-19, the highest rates were observed for heart failure (199.3; 95% CI: 191.8 - 207.1) and AKI (154.5; 95% CI: 147.9 - 161.4). Rates of DVT, heart failure, ischaemic stroke, MI, PE and diabetes were high over the four months post discharge, especially in the first month. Patterns were broadly similar to those seen in patients discharged with pneumonia but somewhat higher in the COVID-19 population for stroke (adj-HR 1.78; 95% CI: 1.53 - 2.08), PE (adj-HR 1.38; 95% CI: 1.21 - 1.58), MI (adj-HR 1.46; 95% CI: 1.20 - 1.76), AKI (adj-HR 1.27; 95% CI: 1.19 - 1.36) and T2DM (adj-HR 1.28; 95% CI: 1.08 - 1.50). <h4>Conclusions</h4> In this descriptive study of survivors of severe COVID-19, rates of the measured outcomes are at least as high, though in some cases slightly higher, than in patients discharged after hospitalisation with pneumonia. Further work is needed to identify what characteristics of COVID-19 patients put them at highest risk of adverse events.

Original publication

DOI

10.1101/2021.01.22.21250304

Type

Journal article

Publication Date

25/01/2021

Keywords

The OpenSAFELY Collaborative