A robust COVID-19 mortality prediction calculator based on Lymphocyte count, Urea, C-Reactive Protein, Age and Sex (LUCAS) with chest x-rays

Ray, S. , Banerjee, A., Swift, A., Fanstone, J. W., Mamalakis, M., Vorselaars, B., Wilkie, C., Cole, J., Mackenzie, L. S. and Weeks, S. (2022) A robust COVID-19 mortality prediction calculator based on Lymphocyte count, Urea, C-Reactive Protein, Age and Sex (LUCAS) with chest x-rays. Scientific Reports, 12, 18220. (doi: 10.1038/s41598-022-21803-2) (PMID:36309547) (PMCID:PMC9617052)

Abstract

There have been numerous risk tools developed to enable triaging of SARS-CoV-2 positive patients with diverse levels of complexity. Here we presented a simplified risk-tool based on minimal parameters and chest X-ray (CXR) image data that predicts the survival of adult SARS-CoV-2 positive patients at hospital admission. We analysed the NCCID database of patient blood variables and CXR images from 19 hospitals across the UK using multivariable logistic regression. The initial dataset was non-randomly split between development and internal validation dataset with 1434 and 310 SARS-CoV-2 positive patients, respectively. External validation of the final model was conducted on 741 Accident and Emergency (A&E) admissions with suspected SARS-CoV-2 infection from a separate NHS Trust. The LUCAS mortality score included five strongest predictors (Lymphocyte count, Urea, C-reactive protein, Age, Sex), which are available at any point of care with rapid turnaround of results. Our simple multivariable logistic model showed high discrimination for fatal outcome with the area under the receiving operating characteristics curve (AUC-ROC) in development cohort 0.765 (95% confidence interval (CI): 0.738–0.790), in internal validation cohort 0.744 (CI: 0.673–0.808), and in external validation cohort 0.752 (CI: 0.713–0.787). The discriminatory power of LUCAS increased slightly when including the CXR image data. LUCAS can be used to obtain valid predictions of mortality in patients within 60 days of SARS-CoV-2 RT-PCR results into low, moderate, high, or very high risk of fatality.

• Item Type: Articles
• Additional Information: EPSRC Impact Acceleration account fund EP/R511705/1; University of Brighton COVID-19 Research Urgency Fund. AS is funded by the Wellcome Trust fellowship 205188/Z/16/Z; AB is a Royal Society University Research Fellow and is supported by the Royal Society (Grant No. URF\R1\221314).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Wilkie, Dr Craig and Ray, Professor Surajit

Creator Roles

Ray, S.: Conceptualization, Project administration, Supervision, Visualization, Writing – original draft, Writing – review and editing
Wilkie, C.: Writing – review and editing

• Authors: Ray, S., Banerjee, A., Swift, A., Fanstone, J. W., Mamalakis, M., Vorselaars, B., Wilkie, C., Cole, J., Mackenzie, L. S., and Weeks, S.
• College/School: College of Science and Engineering > School of Mathematics and Statistics > Statistics
• Journal Name: Scientific Reports
• Publisher: Nature Research
• ISSN: 2045-2322
• ISSN (Online): 2045-2322
• Copyright Holders: Copyright © 2022 The Authors
• First Published: First published in Scientific Reports 12: 18220
• Publisher Policy: Reproduced under a Creative Commons License

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
300137		Impact Acceleration Account - University of Glasgow 2017	Jonathan Cooper	Engineering and Physical Sciences Research Council (EPSRC)	EP/R511705/1	Research and Innovation Services