Chest radiographs may assist in predicting the outcome in the early phase of Covid-19. UK district general hospital experience of Covid-19 first wave

ABSTRACT

Objectives: Severe Acute Respiratory Syndrome coronavirus-2 (SARS-CoV-2) has caused enormous strain on health-care systems worldwide. Early recognition of prognostic markers and appropriate management of patients with coronavirus disease 2019 (Covid-19) remains a major global health concern, particularly when resources are limited. We undertook a study to see if basic tests can inform frontline clinicians of disease trajectory in individual patients with COVID-19.

Methods: We retrospectively assessed characteristics of the first 50 consecutive patients admitted to district general hospital in the United Kingdom with positive SARS-Cov-2 RNA swabs.

Results: Our patient cohort shared broad similarities with previously published data on comorbidities and presenting features. We have found that chest radiographic assessment differed between survivors and non-survivors. Air space shadowing in middle zones were more prevalent in non-survivors (73.3% vs. 35.5% [p = 0.027]). Chest radiograph severity score was also found to be higher in non-survivors compared to survivors (3 vs. 1.5 [p = 0.007]).

Conclusions: In this small retrospective study, our results suggest features of chest radiographs at presentation may provide a helpful tool for prognostication. In environments with constrained computed tomography (CT) imaging with serial chest radiographs could be a cost-effective tool in the assessment of Covid-19 patients.

KEYWORDS:

• Covid-19
• CXR
• radiograph: coronavirus
• United Kingdom

Author contributions

Max Berrill: Conceptualization, methodology, investigation, project administration, curation, supervision, writing – original draft, writing – review. Jola Karaj: conceptualization, investigation, writing – review. Georgiana Zamfir: conceptualization, investigation, writing – review. Jordan Coleman: investigation. Felicity Saltissi: investigation, conceptualization, writing – review. Rachel Mason: investigation. Saeed Akbar: investigation. Frances Sheehan – conceptualization, investigation, writing – review. Kanchan Dhamija: conceptualization, investigation, writing – review. Aigul Baltabaeva: conceptualization, methodology, investigation, writing – review. Sujoy Saikia: conceptualization, methodology, project administration, supervision

Acknowledgments

The authors would like to acknowledge David Crook for his help throughout with statistical expertise and analysis. There are no declarations of interests. There are no affiliated organizations or entities relevant to the work reported.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.