Residual Lung Abnormalities Following COVID-19 Hospitalization: Interim Analysis of the UKILD Post-COVID-19 Study

Iain Stewart, Joseph Jacob, Peter M George, Philip L Molyneaux, Joanna C Porter, Richard J Allen, Shahab Aslani, J Kenneth Baillie, Shaney L Barratt, Paul Beirne, Stephen M Bianchi, John F Blaikley, James D Chalmers, Rachel C Chambers, Nazia Chaudhuri, Christopher Coleman, Guilhem Collier, Emma K Denneny, Annemarie Docherty, Omer ElneimaRachel A Evans, Laura Fabbri, Michael A Gibbons, Fergus V Gleeson, Bibek Gooptu, Neil J Greening, Beatriz Guillen Guio, Ian P Hall, Neil A Hanley, Victoria Harris, Ewen M Harrison, Melissa Heightman, Toby E Hillman, Alex Horsley, Linzy Houchen-Wolloff, Ian Jarrold, Simon R Johnson, Mark G Jones, Fasihul Khan, Rod Lawson, Olivia Leavy, Nazir Lone, Michael Marks, Hamish McAuley, Puja Mehta, Dhruv Parekh, Karen Piper Hanley, Manuela Platé, John Pearl, Krisnah Poinasamy, Jennifer K Quint, Betty Raman, Matthew Richardson, Pilar Rivera-Ortega, Laura Saunders, Ruth Saunders, Malcolm G Semple, Marco Sereno, Aarti Shikotra, A John Simpson, Amisha Singapuri, David Jf Smith, Mark Spears, Lisa G Spencer, Stefan Stanel, David Thickett, A A Roger Thompson, Mathew Thorpe, Simon Lf Walsh, Samantha Walker, Nicholas David Weatherley, Mark Weeks, Jim M Wild, Dan G Wootton, Chris E Brightling, Ling-Pei Ho, Louise V Wain, R Gisli Jenkins

Research output: Contribution to journalArticlepeer-review


RATIONALE: Shared symptoms and genetic architecture between COVID-19 and lung fibrosis suggests SARS-CoV-2 infection may lead to progressive lung damage.

OBJECTIVES: The UKILD Post-COVID study interim analysis was planned to estimate the prevalence of residual lung abnormalities in people hospitalized with COVID-19 based on risk strata.

METHODS: The Post-HOSPitalisation COVID Study (PHOSP-COVID) was used for capture of routine and research follow-up within 240 days from discharge. Thoracic CTs linked by PHOSP-COVID identifiers were scored for percentage of residual lung abnormalities (ground glass opacities and reticulations). Risk factors in linked CT were estimated with Bayesian binomial regression and risk strata were generated. Numbers within strata were used to estimate post-hospitalization prevalence using Bayesian binomial distributions. Sensitivity analysis was restricted to participants with protocol driven research follow-up.

MEASUREMENTS AND MAIN RESULTS: The interim cohort comprised 3700 people. Of 209 subjects with linked CTs (median 119 days, interquartile range 83-155), 166 people (79.4%) had >10% involvement of residual lung abnormalities. Risk factors included abnormal chest X-ray (RR 1·21 95%CrI 1·05; 1·40), percent predicted DLco<80% (RR 1·25 95%CrI 1·00; 1·56) and severe admission requiring ventilation support (RR 1·27 95%CrI 1·07; 1·55). In the remaining 3491 people, moderate to very-high risk of residual lung abnormalities was classified in 7·8%, post-hospitalization prevalence was estimated at 8.5% (95%CrI 7.6%; 9.5%) rising to 11.7% (95%CrI 10.3%; 13.1%) in sensitivity analysis.

CONCLUSIONS: Residual lung abnormalities were estimated in up to 11% of people discharged following COVID-19 related hospitalization. Health services should monitor at-risk individuals to elucidate long-term functional implications. This article is open access and distributed under the terms of the Creative Commons Attribution 4.0 International License (

Original languageEnglish
Pages (from-to)693-703
Number of pages11
JournalAmerican Journal of Respiratory and Critical Care Medicine
Issue number6
Early online date1 Dec 2022
Publication statusPublished - 15 Mar 2023


  • Bayes Theorem
  • COVID-19/epidemiology
  • Hospitalization
  • Humans
  • Lung Diseases, Interstitial
  • Lung/diagnostic imaging
  • SARS-CoV-2


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