Risk factors for in-hospital mortality in laboratory-confirmed COVID-19 patients in the Netherlands: A competing risk survival analysis
Gerine Nijman, Maike H M Wientjes, Jordache Ramjith, Nico Janssen, Jacobien J. Hoogerwerf, Evertine J. Abbink, Marc J. T. Blaauw, Ton Dofferhoff, Marjan van Apeldoorn, Karin Veerman, Quirijn de Mast, Jaap ten Oever, Wouter Hoefsloot, Monique H. Reijers, Reinout van Crevel, Josephine van de Maat
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.