Predictors of mortality in COVID-19 patients at Kinshasa University Hospital, Democratic Republic of the Congo, from March to June 2020

Bepouka, Ben Izizag; Mandina, Madone; Makulo, Jean Robert; Longokolo, Murielle; Odio, Ossam; Mayasi, Nadine; Pata, Tresor; Nsangana, Godelive; Tshikangu, Felly; Mangala, Donatien; Maheshe, Dupont; Nkarnkwin, Serge; Muamba, Jonathan; Ndaie, Gorby; Ngwizani, Rodrigue; Yanga, Yves; Nkodila, Aliocha; Keke, Hervé; Kokusa, Yamin; Lepira, Francois; Kashongwe, Innocent; Mbula, Marcel; Kayembe, Jean Marie; Situakibanza, Hippolyte

INTRODUCTION: since the 1(st) case of coronavirus disease 2019 (COVID-19) in Kinshasa on March 10(th)2020, mortality risk factors have not yet been reported. The objectives of the present study were to assess survival and to identify predictors of mortality in COVID-19 patients at Kinshasa University Hospital. METHODS: a retrospective cohort study was conducted, 141 COVID-19 patients admitted at the Kinshasa University Hospital from March 23 to June 15, 2020 were included in the study. Kaplan Meier's method was used to described survival. Predictors of mortality were identified by COX regression models. RESULTS: of the 141 patients admitted with COVID-19, 67.4 % were men (sex ratio 2H: 1F); their average age was 49.6±16.5 years. The mortality rate in hospitalized patients with COVID-19 was 29% during the study period with 70% deceased within 24 hours of admission. Survival was decreased with the presence of hypertension, diabetes mellitus, low blood oxygen saturation (BOS), severe or critical stage disease. In multivariate analysis, age between 40 and 59 years [adjusted Hazard Ratio (aHR): 4.07; 95% CI: 1.16 - 8.30], age at least 60 years (aHR: 6.65; 95% CI: 1.48-8.88), severe or critical COVID-19 (aHR: 14.05; 95% CI: 6.3-15.67) and presence of dyspnea (aHR: 5.67; 95% CI: 1.46-21.98) were independently and significantly associated with the risk of death. CONCLUSION: older age, severe or critical COVID-19 and dyspnea on admission were potential predictors of mortality in patients with COVID-19. These predictors may help clinicians identify patients with a poor prognosis.