Illness trajectory in the longer term after hospitalisation for COVID-19: a prospective, multicentre cohort study

Abstract Background There are few data on the longer-term illness trajectory of patients following hospitalisation for COVID-19. Methods 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. Results 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 1.13, 95%CI: 1.02, 1.24, p=0.020), current smoking (HR 2.49, 95%CI: 1.21, 5.11, p=0.010), and haemoglobin (HR 0.93, 95%CI: 0.88, 0.99, p=0.020). The WHO Clinical Severity Score was not a significant predictor (p=0.187). Conclusion Comorbidity, current smoking status and haemoglobin predict illness trajectory following hospitalisation for COVID-19, rather than illness severity during hospitalisation. Further research is needed to explore interventions targeting these factors to improve prognosis. Trial registration CISCO-19; http://NCT04403607. Registration date; 23/05/2020