Illness trajectory in the longer term after hospitalisation for COVID-19: a prospective, multicentre cohort study
Anna Kamdar, Andrew J. Morrow, Robert Sykes, Alasdair McIntosh, Catherine Bagot, Hannah K. Bayes, Kevin G. Blyth, Colin Church, Lynsey Gillespie, Giles Roditi, David Stobo, Sarah Weeden, Paul Welsh, Kenneth Mangion, Alex McConnachie, Colin Berry

TL;DR
This study tracks health outcomes for over a year after hospitalization for COVID-19, finding that factors like comorbidities and smoking predict long-term illness.
Contribution
The study identifies long-term predictors of illness trajectory after hospitalization for COVID-19, independent of initial disease severity.
Findings
43.1% of participants experienced at least one event (death or unplanned hospitalization) during a median follow-up of 1028 days.
Multivariable predictors included comorbidity index, current smoking, and haemoglobin levels, but not initial illness severity.
Healthcare worker status was associated with a lower risk of events.
Abstract
There are few data on the longer-term illness trajectory of patients following hospitalisation for COVID-19. We prospectively enrolled 267 adults hospitalised for COVID-19. Longer-term follow up was available for 260 participants. Event rates for death or unplanned hospitalisation were calculated using a Poisson model. Univariate and multivariable analyses identified baseline predictors, with a backward selection process for the best fitting model. The mean age of COVID-19 participants was 54.9±12.1 years, and 41% were female. During median follow-up of 1028 days (IQR:1000,1085), 112 individuals (43.1%) had at least one event including 6 deaths (2.3%). There were 252 events in total. The first event rate was 18.9 per 100 person-years (95%CI: 15.7, 22.8). Multivariable predictors included healthcare worker status (HR 0.59, 95%CI: 0.34, 1.02, p=0.046), Charlson Comorbidity Index (HR…
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Taxonomy
TopicsCOVID-19 Clinical Research Studies · Long-Term Effects of COVID-19 · COVID-19 and healthcare impacts
