Predicting the risk of chest radiograph abnormality 12-weeks post hospitalisation with SARS CoV-2 PCR confirmed COVID-19
Predicting the risk of chest radiograph abnormality 12-weeks post hospitalisation with SARS CoV-2 PCR confirmed COVID-19
Background
Routine follow-up of patients hospitalised with COVID-19 is recommended, however due to the ongoing high number of infections this is not without significant health resource and economic burden. In a previous study we investigated the prevalence of, and risk factors for, persistent chest radiograph (CXR) abnormalities post-hospitalisation with COVID-19 and identified a 5-point composite score that strongly predicted risk of persistent CXR abnormality at 12-weeks. Here we sought to validate and refine our findings in an independent cohort of patients.
Methodology
A single-centre prospective study of consecutive patients attending a virtual post-hospitalisation COVID-19 clinic and CXR as part of their standard clinical care between 2nd March – 22nd June 2021. Inpatient and follow-up CXRs were scored by the assessing clinician for extent of pulmonary infiltrates (0–4 in each lung) with complete resolution defined as a follow-up score of zero.
Results
182 consecutive patients were identified of which 31% had persistent CXR abnormality at 12-weeks. Patients with persistent CXR abnormality were significantly older (p < 0.001), had a longer hospital length of stay (p = 0.005), and had a higher incidence of both level 2 or 3 facility admission (level 2/3 care) (p = 0.003) and ever-smoking history (p = 0.038). Testing our composite score in the present cohort we found it predicted persistent CXR abnormality with reasonable accuracy (area under the receiver operator curve [AUROC 0.64]). Refining this score replacing obesity with Age ≥ 50 years, we identify the SHADE-750 score (1-point each for; Smoking history, Higher-level care (level 2/3 admission), Age ≥ 50 years, Duration of admission ≥ 15 days and Enzyme-lactate dehydrogenase (LDH ≥ 750U/L), that accurately predicted risk of persistent CXR abnormality, both in the present cohort (AUROC 0.73) and when retrospectively applied to our 1st cohort (AUROC 0.79). Applied to both cohorts combined (n = 213) it again performed strongly (AUROC 0.75) with all patients with a score of zero (n = 18) having complete CXR resolution at 12-weeks.
Conclusions
In two independent cohorts of patients hospitalised with COVID-19, we identify a 5-point score which accurately predicts patients at risk of persistent CXR abnormality at 12-weeks. This tool could be used by clinicians to identify patients in which radiological follow-up may not be required.
Wallis, Tim Jm
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Welham, Benjamin
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Kong, Alex
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Morelli, Tommaso
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Azim, Adnan
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Horno, Jose
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Wilkinson, Miranda
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Burke, Hannah
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Freeman, Anna
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Wilkinson, Thomas Ma
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Jones, Mark G
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Marshall, Benjamin G
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31 October 2022
Wallis, Tim Jm
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Welham, Benjamin
2606c253-7562-45e6-a284-26a9915d35bf
Kong, Alex
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Morelli, Tommaso
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Azim, Adnan
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Horno, Jose
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Wilkinson, Miranda
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Burke, Hannah
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Freeman, Anna
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Wilkinson, Thomas Ma
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Jones, Mark G
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Marshall, Benjamin G
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Wallis, Tim Jm, Welham, Benjamin, Kong, Alex, Morelli, Tommaso, Azim, Adnan, Horno, Jose, Wilkinson, Miranda, Burke, Hannah, Freeman, Anna, Wilkinson, Thomas Ma, Jones, Mark G and Marshall, Benjamin G
(2022)
Predicting the risk of chest radiograph abnormality 12-weeks post hospitalisation with SARS CoV-2 PCR confirmed COVID-19.
Respiratory Research, 23 (297), [297 (2022)].
(doi:10.1186/s12931-022-02217-0).
Abstract
Background
Routine follow-up of patients hospitalised with COVID-19 is recommended, however due to the ongoing high number of infections this is not without significant health resource and economic burden. In a previous study we investigated the prevalence of, and risk factors for, persistent chest radiograph (CXR) abnormalities post-hospitalisation with COVID-19 and identified a 5-point composite score that strongly predicted risk of persistent CXR abnormality at 12-weeks. Here we sought to validate and refine our findings in an independent cohort of patients.
Methodology
A single-centre prospective study of consecutive patients attending a virtual post-hospitalisation COVID-19 clinic and CXR as part of their standard clinical care between 2nd March – 22nd June 2021. Inpatient and follow-up CXRs were scored by the assessing clinician for extent of pulmonary infiltrates (0–4 in each lung) with complete resolution defined as a follow-up score of zero.
Results
182 consecutive patients were identified of which 31% had persistent CXR abnormality at 12-weeks. Patients with persistent CXR abnormality were significantly older (p < 0.001), had a longer hospital length of stay (p = 0.005), and had a higher incidence of both level 2 or 3 facility admission (level 2/3 care) (p = 0.003) and ever-smoking history (p = 0.038). Testing our composite score in the present cohort we found it predicted persistent CXR abnormality with reasonable accuracy (area under the receiver operator curve [AUROC 0.64]). Refining this score replacing obesity with Age ≥ 50 years, we identify the SHADE-750 score (1-point each for; Smoking history, Higher-level care (level 2/3 admission), Age ≥ 50 years, Duration of admission ≥ 15 days and Enzyme-lactate dehydrogenase (LDH ≥ 750U/L), that accurately predicted risk of persistent CXR abnormality, both in the present cohort (AUROC 0.73) and when retrospectively applied to our 1st cohort (AUROC 0.79). Applied to both cohorts combined (n = 213) it again performed strongly (AUROC 0.75) with all patients with a score of zero (n = 18) having complete CXR resolution at 12-weeks.
Conclusions
In two independent cohorts of patients hospitalised with COVID-19, we identify a 5-point score which accurately predicts patients at risk of persistent CXR abnormality at 12-weeks. This tool could be used by clinicians to identify patients in which radiological follow-up may not be required.
Text
s12931-022-02217-0
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Accepted/In Press date: 9 October 2022
Published date: 31 October 2022
Identifiers
Local EPrints ID: 473260
URI: http://eprints.soton.ac.uk/id/eprint/473260
ISSN: 1465-9921
PURE UUID: 03aac705-acfa-4146-a727-948adc5d7589
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Date deposited: 12 Jan 2023 18:29
Last modified: 17 Mar 2024 04:06
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Contributors
Author:
Tim Jm Wallis
Author:
Benjamin Welham
Author:
Alex Kong
Author:
Tommaso Morelli
Author:
Adnan Azim
Author:
Jose Horno
Author:
Miranda Wilkinson
Author:
Hannah Burke
Author:
Anna Freeman
Author:
Mark G Jones
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