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

PHOSP-COVID Collaborative Group, Iain Stewart (Lead / Corresponding author), 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 DochertyOmer Elneima, Rachel 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, Mark Spears

Research output: Contribution to journalArticlepeer-review

42 Citations (Scopus)
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Rationale: Shared symptoms and genetic architecture between coronavirus disease (COVID-19) and lung fibrosis suggest severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may lead to progressive lung damage.

Objectives: The UK Interstitial Lung Disease Consortium (UKILD) post-COVID-19 study interim analysis was planned to estimate the prevalence of residual lung abnormalities in people hospitalized with COVID-19 on the basis of risk strata.

Methods: The PHOSP-COVID-19 (Post-Hospitalization COVID-19) study was used to capture routine and research follow-up within 240 days from discharge. Thoracic computed tomography linked by PHOSP-COVID-19 identifiers was scored for the percentage of residual lung abnormalities (ground-glass opacities and reticulations). Risk factors in linked computed tomography were estimated with Bayesian binomial regression, and risk strata were generated. Numbers within strata were used to estimate posthospitalization 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 3,700 people. Of 209 subjects with linked computed tomography (median, 119 d; interquartile range, 83-155), 166 people (79.4%) had more than 10% involvement of residual lung abnormalities. Risk factors included abnormal chest X-ray (risk ratio [RR], 1.21; 95% credible interval [CrI], 1.05-1.40), percent predicted DlCO less than 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 3,491 people, moderate to very high risk of residual lung abnormalities was classified at 7.8%, and posthospitalization prevalence was estimated at 8.5% (95% CrI, 7.6-9.5), rising to 11.7% (95% CrI, 10.3-13.1) in the sensitivity analysis.

Conclusions: Residual lung abnormalities were estimated in up to 11% of people discharged after COVID-19-related hospitalization. Health services should monitor at-risk individuals to elucidate long-term functional implications.

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


  • COVID-19
  • HRCT
  • hospitalization
  • lung abnormalities
  • lung damage

ASJC Scopus subject areas

  • Critical Care and Intensive Care Medicine
  • Pulmonary and Respiratory Medicine


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