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

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 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). 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. CISCO-19; http://NCT04403607. Registration date; 23/05/2020

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Journal
BMC Infectious Diseases
Published
2026-01-20
DOI
https://doi.org/10.1186/s12879-025-12487-w
Primary Topic
COVID-19 Clinical Research Studies
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article
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article

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

Anna Kamdar, Lynsey Gillespie, Robert Sykes, Alasdair McIntosh et al.
BMC Infectious Diseases
COVID-19 Clinical Research Studies
article

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

Anna Kamdar, Lynsey Gillespie, Robert Sykes, Alasdair McIntosh, Andrew Morrow, Catherine Bagot, David Stobo, Colin Church, Kevin G. Blyth, Paul Welsh, Sarah Weeden, Alex McConnachie, Colin Berry, Giles Roditi, Kenneth Mangion, Hannah K. Bayes
article en

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 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). 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. CISCO-19; http://NCT04403607. Registration date; 23/05/2020

BMC Infectious DiseasesVol. 26(1)
NHS Greater Glasgow and Clyde (GB), Glasgow Royal Infirmary (GB), Queen Elizabeth University Hospital (GB), University of Glasgow (GB)
Good health and well-being
Openalex Percentile: Top 82%
COVID-19 Clinical Research Studies
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