Gerine Nijman1,2, Maike Wientjes3, Jordache Ramjith4, Nico Janssen2,5, Jacobien Hoogerwerf1,2, Evertine Abbink1, Marc Blaauw6, Ton Dofferhoff7, Marjan van Apeldoorn8, Karin Veerman9, Quirijn de Mast1,2, Jaap Ten Oever1,2, Wouter Hoefsloot2,10, Monique H Reijers2,10, Reinout van Crevel1,2, Josephine S van de Maat1,2. 1. Department of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands. 2. Radboud Centre for Infectious Diseases (RCI), Radboud University Medical Centre, Nijmegen, The Netherlands. 3. Department of Research, Sint Maartenskliniek, Nijmegen, The Netherlands. 4. Department of Health Evidence, Section Biostatistics, Radboud University Medical Centre, Nijmegen, The Netherlands. 5. Centre of Expertise in Mycology, Radboud University Medical Centre, Canisius Wilhelmina Hospital, Nijmegen, The Netherlands. 6. Department of Internal Medicine, Bernhoven Hospital, Uden, The Netherlands. 7. Department of Internal Medicine, Canisius Wilhelmina Hospital, Nijmegen, The Netherlands. 8. Department of Internal Medicine, Jeroen Bosch Hospital, Den Bosch, The Netherlands. 9. Department of Internal Medicine, Sint Maartenskliniek, Nijmegen, The Netherlands. 10. Department of Pulmonary Diseases, Radboud University Medical Centre, Nijmegen, The Netherlands.
Abstract
BACKGROUND: To date, survival data on risk factors for COVID-19 mortality in western Europe is limited, and none of the published survival studies have used a competing risk approach. This study aims to identify risk factors for in-hospital mortality in COVID-19 patients in the Netherlands, considering recovery as a competing risk. METHODS: In this observational multicenter cohort study we included adults with PCR-confirmed SARS-CoV-2 infection that were admitted to one of five hospitals in the Netherlands (March to May 2020). We performed a competing risk survival analysis, presenting cause-specific hazard ratios (HRCS) for the effect of preselected factors on the absolute risk of death and recovery. RESULTS: 1,006 patients were included (63.9% male; median age 69 years, IQR: 58-77). Patients were hospitalized for a median duration of 6 days (IQR: 3-13); 243 (24.6%) of them died, 689 (69.9%) recovered, and 74 (7.4%) were censored. Patients with higher age (HRCS 1.10, 95% CI 1.08-1.12), immunocompromised state (HRCS 1.46, 95% CI 1.08-1.98), who used anticoagulants or antiplatelet medication (HRCS 1.38, 95% CI 1.01-1.88), with higher modified early warning score (MEWS) (HRCS 1.09, 95% CI 1.01-1.18), and higher blood LDH at time of admission (HRCS 6.68, 95% CI 1.95-22.8) had increased risk of death, whereas fever (HRCS 0.70, 95% CI 0.52-0.95) decreased risk of death. We found no increased mortality risk in male patients, high BMI or diabetes. CONCLUSION: Our competing risk survival analysis confirms specific risk factors for COVID-19 mortality in a the Netherlands, which can be used for prediction research, more intense in-hospital monitoring or prioritizing particular patients for new treatments or vaccination.
BACKGROUND: To date, survival data on risk factors for COVID-19mortality in western Europe is limited, and none of the published survival studies have used a competing risk approach. This study aims to identify risk factors for in-hospital mortality in COVID-19patients in the Netherlands, considering recovery as a competing risk. METHODS: In this observational multicenter cohort study we included adults with PCR-confirmed SARS-CoV-2 infection that were admitted to one of five hospitals in the Netherlands (March to May 2020). We performed a competing risk survival analysis, presenting cause-specific hazard ratios (HRCS) for the effect of preselected factors on the absolute risk of death and recovery. RESULTS: 1,006 patients were included (63.9% male; median age 69 years, IQR: 58-77). Patients were hospitalized for a median duration of 6 days (IQR: 3-13); 243 (24.6%) of them died, 689 (69.9%) recovered, and 74 (7.4%) were censored. Patients with higher age (HRCS 1.10, 95% CI 1.08-1.12), immunocompromised state (HRCS 1.46, 95% CI 1.08-1.98), who used anticoagulants or antiplatelet medication (HRCS 1.38, 95% CI 1.01-1.88), with higher modified early warning score (MEWS) (HRCS 1.09, 95% CI 1.01-1.18), and higher blood LDH at time of admission (HRCS 6.68, 95% CI 1.95-22.8) had increased risk of death, whereas fever (HRCS 0.70, 95% CI 0.52-0.95) decreased risk of death. We found no increased mortality risk in male patients, high BMI or diabetes. CONCLUSION: Our competing risk survival analysis confirms specific risk factors for COVID-19mortality in a the Netherlands, which can be used for prediction research, more intense in-hospital monitoring or prioritizing particular patients for new treatments or vaccination.
Authors: Brandon Michael Henry; Gaurav Aggarwal; Johnny Wong; Stefanie Benoit; Jens Vikse; Mario Plebani; Giuseppe Lippi Journal: Am J Emerg Med Date: 2020-05-27 Impact factor: 2.469
Authors: Martin Dres; David Hajage; Said Lebbah; Antoine Kimmoun; Tai Pham; Gaëtan Béduneau; Alain Combes; Alain Mercat; Bertrand Guidet; Alexandre Demoule; Matthieu Schmidt Journal: Ann Intensive Care Date: 2021-05-14 Impact factor: 6.925