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Original research
Predicting outcomes of COVID-19 from admission biomarkers: a prospective UK cohort study
  1. David T Arnold1,
  2. Marie Attwood2,
  3. Shaney Barratt1,
  4. Anna Morley1,
  5. Karen T Elvers3,
  6. Jorgen McKernon4,
  7. Charmaine Donald5,
  8. Adrian Oates4,
  9. Alan Noel2,
  10. Alasdair MacGowan2,
  11. Nick A Maskell1,
  12. Fergus W Hamilton6
  1. 1 Academic Respiratory Unit, University of Bristol, Bristol, UK
  2. 2 Bristol Centre for Antimicrobial Research, North Bristol NHS Trust, Bristol, UK
  3. 3 Medicines Discovery Institute Cardiff, Cardiff University, Cardiff, UK
  4. 4 Biochemistry, North Bristol NHS Trust, Bristol, UK
  5. 5 Immunology, North Bristol NHS Trust, Bristol, UK
  6. 6 Infection Sciences, North Bristol NHS Trust, Bristol, UK
  1. Correspondence to Dr David T Arnold, Academic Respiratory Unit, University of Bristol, Bristol BS10 5NB, UK; arnold.dta{at}gmail.com

Abstract

Introduction COVID-19 has an unpredictable clinical course, so prognostic biomarkers would be invaluable when triaging patients on admission to hospital. Many biomarkers have been suggested using large observational datasets but sample timing is crucial to ensure prognostic relevance. The DISCOVER study prospectively recruited patients with COVID-19 admitted to a UK hospital and analysed a panel of putative prognostic biomarkers on the admission blood sample to identify markers of poor outcome.

Methods Consecutive patients admitted to hospital with proven or clinicoradiological suspected COVID-19 were consented. Admission bloods were extracted from the clinical laboratory. A panel of biomarkers (interleukin-6 (IL-6), soluble urokinase plasminogen activator receptor (suPAR), Krebs von den Lungen 6, troponin, ferritin, lactate dehydrogenase, B-type natriuretic peptide, procalcitonin) were performed in addition to routinely performed markers (C reactive protein (CRP), neutrophils, lymphocytes, neutrophil:lymphocyte ratio). Age, National Early Warning Score (NEWS2), CURB-65 and radiographic severity score on initial chest radiograph were included as comparators. All biomarkers were tested in logistic regression against a composite outcome of non-invasive ventilation, intensive care admission or death, with area under the curve (AUC) (figures calculated).

Results 187 patients had 28-day outcomes at the time of analysis. CRP (AUC: 0.69, 95% CI: 0.59 to 0.78), lymphocyte count (AUC: 0.62, 95% CI: 0.53 to 0.72) and other routine markers did not predict the primary outcome. IL-6 (AUC: 0.77, 0.65 to 0.88) and suPAR (AUC: 0.81, 0.72 to 0.88) showed some promise, but simple clinical features alone such as NEWS2 score (AUC: 0.70, 0.60 to 0.79) or age (AUC: 0.70, 0.62 to 0.77) performed nearly as well.

Discussion Admission blood biomarkers have only moderate predictive value for predicting COVID-19 outcomes, while simple clinical features such as age and NEWS2 score outperform many biomarkers. IL-6 and suPAR had the best performance, and further studies should focus on the additive value of these biomarkers to routine care.

  • infectious diseases
  • SARS
  • respiratory
  • pneumonia/infections

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information. Although we are unable to share raw data, the analytic code is available at https://github.com/gushamilton/discover_prediction/

This article is made freely available for use in accordance with BMJ’s website terms and conditions for the duration of the covid-19 pandemic or until otherwise determined by BMJ. You may use, download and print the article for any lawful, non-commercial purpose (including text and data mining) provided that all copyright notices and trade marks are retained.

https://bmj.com/coronavirus/usage

https://doi.org/10.1136/emermed-2020-210380

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    Data availability statement

    All data relevant to the study are included in the article or uploaded as supplementary information. Although we are unable to share raw data, the analytic code is available at https://github.com/gushamilton/discover_prediction/

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    Footnotes

    • Handling editor Richard Body

    • Twitter @DavidT_Arnold, @ree19872

    • Contributors DTA and FWH had the idea for the study. SB, AMG and NAM have a supervisory role. AM led the collection of samples. KTE, JMK, CD, AO and AN were involved in the analysis of samples. FWH led the data analysis. All authors were involved in the writing of the manuscript.

    • Funding The DISCOVER study was supported by grants from the Southmead Hospital Charity and Elizabeth Blackwell Institute (Grant number: not applicable/ NA). DTA is funded by a National Institute for Health Research (NIHR) Doctoral Research Fellowship (DRF-2018-11-ST2-065). FH is funded via the National Institute for Health Academic Clinical Fellowship scheme.The suPARnostic ELISA kits and IL-6/KL-6 assays were gifts from ViroGates (Birkeroed, Denmark) and Fujirebio Europe, respectively, for unrestricted research activity (Grant number: not applicable/NA).

    • Disclaimer The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.