SARS-CoV2 infection in symptomatic patients: interest of serological tests and predictors of mortality: experience of DR Congo.

BACKGROUND: In symptomatic patients, the diagnostic approach of COVID-19 should be holistic. We aimed to evaluate the concordance between RT-PCR and serological tests (IgM/IgG), and identify the factors that best predict mortality (clinical stages or viral load). METHODS: The study included 242 patients referred to the University hospital of Kinshasa for suspected COVID-19, dyspnea or ARDS between June 1st, 2020 and August 02, 2020. Both antibody-SARS-CoV2 IgM/IgG and RT-PCR method were performed on the day of admission to hospital. The clinical stages were established according to the COVID-19 WHO classification. The viral load was expressed by the CtN2 (cycle threshold value of the nucleoproteins) and the CtE (envelope) genes of SARS- CoV-2 detected using GeneXpert. Kappa test and Cox regression were used as appropriate. RESULTS: The GeneXpert was positive in 74 patients (30.6%). Seventy two patients (29.8%) had positive IgM and 34 patients (14.0%) had positive IgG. The combination of RT-PCR and serological tests made it possible to treat 104 patients as having COVID-19, which represented an increase in cases of around 41% compared to the result based on GeneXpert alone. The comparison between the two tests has shown that 57 patients (23.5%) had discordant results. The Kappa coefficient was 0.451 (p < 0.001). We recorded 23 deaths (22.1%) among the COVID-19 patients vs 8 deaths (5.8%) among other patients. The severe-critical clinical stage increased the risk of mortality vs. mild-moderate stage (aHR: 26.8, p < 0.001). The values of CtE and CtN2 did not influence mortality significantly. CONCLUSION: In symptomatic patients, serological tests are a support which makes it possible to refer patients to the dedicated COVID-19 units and treat a greater number of COVID-19 patients. WHO Clinical classification seems to predict mortality better than SARS-Cov2 viral load.

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

INTRODUCTION: since the 1st case of coronavirus disease 2019 (COVID-19) in Kinshasa on March 10th2020, 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.

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

Introduction: since the 1st case of coronavirus disease 2019 (COVID-19) in Kinshasa on March 10th 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