Interstitial lung damage following COVID-19 hospitalisation: an interim analysis of the UKILD Post-COVID study

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Abstract

Introduction

Shared characteristics between COVID-19 and pulmonary fibrosis, including symptoms, genetic architecture, and circulating biomarkers, suggests interstitial lung disease (ILD) development may be associated with SARS-CoV-2 infection.

Methods

The UKILD Post-COVID study planned interim analysis was designed to stratify risk groups and estimate the prevalence of Post-COVID Interstitial Lung Damage (ILDam) using the Post-HOSPitalisation COVID-19 (PHOSP-COVID) Study. Demographics, radiological patterns and missing data were assessed descriptively. Bayes binomial regression was used to estimate the risk ratio of persistent lung damage >10% involvement in linked, clinically indicated CT scans. Indexing thresholds of percent predicted DLco, chest X-ray findings and severity of admission were used to generate risk strata. Number of cases within strata were used to estimate the amount of suspected Post-COVID ILDam.

Results

A total 3702 people were included in the UKILD interim cohort, 2406 completed an early follow-up research visit within 240 days of discharge and 1296 had follow-up through routine clinical review. We linked the cohort to 87 clinically indicated CTs with visually scored radiological patterns (median 119 days from discharge; interquartile range 83 to 155, max 240), of which 74 people had ILDam. ILDam was associated with 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 (RR 1.27 95%CrI 1.07; 1.55). A risk index based on these features suggested 6.9% of the interim cohort had moderate to very-high risk of Post-COVID ILDam. Comparable radiological patterns were observed in repeat scans >90 days in a subset of participants.

Conclusion

These interim data highlight that ILDam was not uncommon in clinically indicated thoracic CT up to 8 months following SARS-CoV-2 hospitalisation. Whether the ILDam will progress to ILD is currently unknown, however health services should radiologically and physiologically monitor individuals who have Post-COVID ILDam risk factors.

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  1. SciScore for 10.1101/2022.03.10.22272081: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsConsent: Individuals withdrawing consent from PHOSP-COVID were excluded.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Strengths and Limitations: This interim analysis of the UKILD Post-COVID study is the largest assessment of ILDam in patients hospitalised for COVID-19 to date, and the findings are consistent with findings from a number of smaller studies that demonstrate persistent radiological patterns and impaired gas transfer during extended follow-up of patients with COVID-19.[20-24] For participants in receipt of a clinically indicated but unscored CT, we observed that 67/335 (20.0%) people were in moderate to very-high risk strata (sensitivity 57/238, 24.0%), which was similar to the percentage of CT scans with radiological patterns suggestive of fibrosis within the first year post-hospitalisation estimated in meta-analysis (29%; 95%CI 22% to 37%).[25] The UKILD long-COVID cohort excluded participants with any evidence of ILD prior to hospitalisation, and we used informative sceptical priors and power priors for more conservative estimates, which continued to suggest a substantial burden of Post-COVID ILDam. The approach we report can be reasonably applied to later follow-up, with current findings used as informative priors for updating Bayesian inference. Whilst included CTs were assumed to be representative of clinically indicated radiology, this is limited by local management protocols and timing of services, which increases chances of selection and ascertainment bias. Furthermore, individuals with linked CT may have unrecorded pre-existing disease or present with radiological patt...

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.


    About SciScore

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