Laure Abensur Vuillaume1, Pierrick Le Borgne2,3, Karine Alamé2, François Lefebvre4, Lise Bérard5, Nicolas Delmas6, Lauriane Cipolat1, Stéphane Gennai7, Pascal Bilbault2,3, Charles-Eric Lavoignet8. 1. Emergency Department, Regional Hospital of Metz-Thionville, 57000 Metz, France. 2. Emergency Department, Hôpitaux Universitaires de Strasbourg, 67000 Strasbourg, France. 3. INSERM (French National Institute of Health and Medical Research), UMR 1260, Regenerative NanoMedicine (RNM), Fédération de Médecine Translationnelle (FMTS), University of Strasbourg, 67000 Strasbourg, France. 4. Department of Public Health, University Hospital of Strasbourg, 67000 Strasbourg, France. 5. Emergency Department, Haguenau Hospital, 67500 Haguenau, France. 6. Emergency Department, Colmar Hospital, 68000 Colmar, France. 7. Emergency Department, Reims University Hospital, 51000 Reims, France. 8. Emergency Department, Hôpital Nord Franche Comté, 90400 Trévenans, France.
Abstract
(1) Introduction: The neutrophil-to lymphocyte ratio is valued as a predictive marker in several inflammatory diseases. For example, an increasing NLR is a risk factor of mortality in sepsis. It also appears to be helpful in other settings such as cancer. The aim of our work was to study the prognostic value of NLR for disease severity and mortality in patients infected with SARS-CoV-2 upon their admission to the Emergency Department (ED) and its early variation (ΔNLR) in the first 24 h of management (H-24). (2) Methods: Between 1 March and 30 April 2020, we conducted a multicenter and retrospective cohort study of patients with moderate or severe coronavirus disease 19 (COVID-19), who were all hospitalized after presenting to the ED. (3) Results: A total of 1035 patients were included in our study. Factors associated with infection severity were C-reactive protein level (OR: 1.007, CI 95%: [1.005-1.010], p < 0.001), NLR at H-24 (OR: 1.117, CI 95%: [1.060-1.176], p < 0.001), and ΔNLR (OR: 1.877, CI 95%: [1.160-3.036], p: 0.01). The best threshold of ΔNLR to predict the severity of infection was 0.222 (sensitivity 56.1%, specificity 68.3%). In multivariate analysis, the only biochemical factor significantly associated with mortality was again ΔNLR (OR: 2.142, CI 95%: ([1.132-4.056], p: 0.019). The best threshold of ΔNLR to predict mortality was 0.411 (sensitivity 53.3%; specificity 67.3%). (4) Conclusion: The NLR and its early variation (ΔNLR) could help physicians predict both severity and mortality associated with SARS-CoV-2 infection, hence contributing to optimized patient management (accurate triage and treatment).
(1) Introduction: The neutrophil-to lymphocyte ratio is valued as a predictive marker in several inflammatory diseases. For example, an increasing NLR is a risk factor of mortality in sepsis. It also appears to be helpful in other settings such as cancer. The aim of our work was to study the prognostic value of NLR for disease severity and mortality in patientsinfected with SARS-CoV-2 upon their admission to the Emergency Department (ED) and its early variation (ΔNLR) in the first 24 h of management (H-24). (2) Methods: Between 1 March and 30 April 2020, we conducted a multicenter and retrospective cohort study of patients with moderate or severe coronavirus disease 19 (COVID-19), who were all hospitalized after presenting to the ED. (3) Results: A total of 1035 patients were included in our study. Factors associated with infection severity were C-reactive protein level (OR: 1.007, CI 95%: [1.005-1.010], p < 0.001), NLR at H-24 (OR: 1.117, CI 95%: [1.060-1.176], p < 0.001), and ΔNLR (OR: 1.877, CI 95%: [1.160-3.036], p: 0.01). The best threshold of ΔNLR to predict the severity of infection was 0.222 (sensitivity 56.1%, specificity 68.3%). In multivariate analysis, the only biochemical factor significantly associated with mortality was again ΔNLR (OR: 2.142, CI 95%: ([1.132-4.056], p: 0.019). The best threshold of ΔNLR to predict mortality was 0.411 (sensitivity 53.3%; specificity 67.3%). (4) Conclusion: The NLR and its early variation (ΔNLR) could help physicians predict both severity and mortality associated with SARS-CoV-2 infection, hence contributing to optimized patient management (accurate triage and treatment).
Authors: Daniela Cihakova; Michael B Streiff; Steven P Menez; Teresa K Chen; Nisha A Gilotra; Erin D Michos; Kieren A Marr; Andrew H Karaba; Matthew L Robinson; Paul W Blair; Maria V Dioverti; Wendy S Post; Andrea L Cox; Annukka A R Antar Journal: Future Virol Date: 2021-09-21 Impact factor: 3.015