Lisa Pilgram1, Lukas Eberwein2, Lukas Tometten3, Sebastian Dolff4, Kai Wille5, Felix C Koehler6,7,8, Melanie Stecher9,10, Siegbert Rieg11, Jan T Kielstein12, Carolin E M Jakob9,10, Maria Rüthrich13, Volker Burst6,8, Fabian Prasser14,15, Stefan Borgmann16, Roman-Ulrich Müller6,7,17, Julia Lanznaster18, Nora Isberner19. 1. Department of Internal Medicine, Hematology and Oncology, Goethe University Frankfurt, Frankfurt, Germany. 2. 4th Department of Internal Medicine, Klinikum Leverkusen gGmbH, Leverkusen, Germany. 3. Department of Gastroenterology and Infectiology, Klinikum Ernst-von-Bergmann, Potsdam, Germany. 4. Department of Infectious Diseases, West German Centre of Infectious Diseases, University Hospital Essen, University Duisburg-Essen, Hufelandstr. 55, 45122, Essen, Germany. Sebastian.Dolff@uk-essen.de. 5. University Clinic for Haematology, Oncology, Haemostaseology and Palliative Care, Johannes Wesling Klinikum, University of Bochum, Minden, Germany. 6. Department II of Internal Medicine and Center for Molecular Medicine Cologne, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany. 7. Faculty of Medicine and University Hospital Cologne, CECAD, University of Cologne, Cologne, Germany. 8. Emergency Department, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany. 9. Department I of Internal Medicine, University Hospital of Cologne, University of Cologne, Cologne, Germany. 10. German Center for Infection Research (DZIF), Partner Site Bonn-Cologne, Cologne, Germany. 11. Division of Infectious Diseases, Department of Medicine II, Medical Centre - University of Freiburg, Faculty of Medicine, Freiburg, Germany. 12. Medical Clinic V, Academic Teaching Hospital Braunschweig, Brunswick, Germany. 13. Department of Internal Medicine II, University Hospital Jena, Jena, Germany. 14. Charite, University Hospital Berlin, Berlin Institute of Health (BIH), Anna-Louisa-Karsch-Str. 2, 10178, Berlin, Germany. 15. Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin Institute of Health, Berlin, Germany. 16. Department of Infectious Diseases and Infection Control, Ingolstadt Hospital, Ingolstadt, Germany. 17. Systems Biology of Ageing Cologne (Sybacol), University of Cologne, Cologne, Germany. 18. Department of Internal Medicine 2, Klinikum Passau, Passau, Germany. 19. Division of Infectious Diseases, Department of Medicine II, University of Würzburg Medical Center, Würzburg, Germany.
Abstract
PURPOSE: The ongoing pandemic caused by the novel severe acute respiratory coronavirus 2 (SARS-CoV-2) has stressed health systems worldwide. Patients with chronic kidney disease (CKD) seem to be more prone to a severe course of coronavirus disease (COVID-19) due to comorbidities and an altered immune system. The study's aim was to identify factors predicting mortality among SARS-CoV-2-infected patients with CKD. METHODS: We analyzed 2817 SARS-CoV-2-infected patients enrolled in the Lean European Open Survey on SARS-CoV-2-infected patients and identified 426 patients with pre-existing CKD. Group comparisons were performed via Chi-squared test. Using univariate and multivariable logistic regression, predictive factors for mortality were identified. RESULTS: Comparative analyses to patients without CKD revealed a higher mortality (140/426, 32.9% versus 354/2391, 14.8%). Higher age could be confirmed as a demographic predictor for mortality in CKD patients (> 85 years compared to 15-65 years, adjusted odds ratio (aOR) 6.49, 95% CI 1.27-33.20, p = 0.025). We further identified markedly elevated lactate dehydrogenase (> 2 × upper limit of normal, aOR 23.21, 95% CI 3.66-147.11, p < 0.001), thrombocytopenia (< 120,000/µl, aOR 11.66, 95% CI 2.49-54.70, p = 0.002), anemia (Hb < 10 g/dl, aOR 3.21, 95% CI 1.17-8.82, p = 0.024), and C-reactive protein (≥ 30 mg/l, aOR 3.44, 95% CI 1.13-10.45, p = 0.029) as predictors, while renal replacement therapy was not related to mortality (aOR 1.15, 95% CI 0.68-1.93, p = 0.611). CONCLUSION: The identified predictors include routinely measured and universally available parameters. Their assessment might facilitate risk stratification in this highly vulnerable cohort as early as at initial medical evaluation for SARS-CoV-2.
PURPOSE: The ongoing pandemic caused by the novel severe acute respiratory coronavirus 2 (SARS-CoV-2) has stressed health systems worldwide. Patients with chronic kidney disease (CKD) seem to be more prone to a severe course of coronavirus disease (COVID-19) due to comorbidities and an altered immune system. The study's aim was to identify factors predicting mortality among SARS-CoV-2-infectedpatients with CKD. METHODS: We analyzed 2817 SARS-CoV-2-infectedpatients enrolled in the Lean European Open Survey on SARS-CoV-2-infectedpatients and identified 426 patients with pre-existing CKD. Group comparisons were performed via Chi-squared test. Using univariate and multivariable logistic regression, predictive factors for mortality were identified. RESULTS: Comparative analyses to patients without CKD revealed a higher mortality (140/426, 32.9% versus 354/2391, 14.8%). Higher age could be confirmed as a demographic predictor for mortality in CKDpatients (> 85 years compared to 15-65 years, adjusted odds ratio (aOR) 6.49, 95% CI 1.27-33.20, p = 0.025). We further identified markedly elevated lactate dehydrogenase (> 2 × upper limit of normal, aOR 23.21, 95% CI 3.66-147.11, p < 0.001), thrombocytopenia (< 120,000/µl, aOR 11.66, 95% CI 2.49-54.70, p = 0.002), anemia (Hb < 10 g/dl, aOR 3.21, 95% CI 1.17-8.82, p = 0.024), and C-reactive protein (≥ 30 mg/l, aOR 3.44, 95% CI 1.13-10.45, p = 0.029) as predictors, while renal replacement therapy was not related to mortality (aOR 1.15, 95% CI 0.68-1.93, p = 0.611). CONCLUSION: The identified predictors include routinely measured and universally available parameters. Their assessment might facilitate risk stratification in this highly vulnerable cohort as early as at initial medical evaluation for SARS-CoV-2.
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