Comparison of Lymphocyte-CRP ratio to conventional inflammatory markers for predicting clinical outcomes in COVID-19
MetadataShow full item record
Background : In COVID-19 patients, lymphocyte–CRP ratio (LCR) is a promising biomarker for predicting adverse clinical outcomes. How well LCR performs compared to conventional inflammatory markers for prognosticating COVID-19 patients remains unclear, which hinders the clinical translation of this novel biomarker. Methods : In a cohort of COVID-19 inpatients, we characterised the clinical applicability of LCR by comparing its prognostic value against conventional inflammatory markers for predicting inpatient mortality and a composite of mortality, invasive/non-invasive ventilation and intensive care unit admissions. Results : Of the 413 COVID-19 patients, 100 (24%) patients suffered inpatient mortality. On Receiver Operating Characteristics analysis, LCR performed similarly to CRP for predicting mortality (AUC 0.74 vs. 0.71, p = 0.049) and the composite endpoint (AUC 0.76 vs. 0.76, p = 0.812). LCR outperformed lymphocyte counts (AUC 0.74 vs. 0.66, p = 0.002), platelet counts (AUC 0.74 vs. 0.61, p = 0.003) and white cell counts (AUC 0.74 vs. 0.54, p < 0.001) for predicting mortality. On Kaplan–Meier analysis, patients with a low LCR (below a 58 cut-off) had worse inpatient survival than patients with other LCR values (p < 0.001). Conclusion : LCR appears comparable to CRP, but outperformed other inflammatory markers, for prognosticating COVID-19 patients. Further studies are required to improve the diagnostic value of LCR to facilitate clinical translation.
Liu , A Q , Hammond , R , Chan , K , Chukwuenweniwe , C , Johnson , R , Khair , D , Duck , E , Olubodun , O , Barwick , K , Banya , W , Stirrup , J , Donnelly , P D , Kaski , J C & Coates , A R 2023 , ' Comparison of Lymphocyte-CRP ratio to conventional inflammatory markers for predicting clinical outcomes in COVID-19 ' , Journal of Personalized Medicine , vol. 13 , no. 6 , 909 . https://doi.org/10.3390/jpm13060909
Journal of Personalized Medicine
Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/4.0/).
Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.