Prediction of COVID-19 mortality among hospitalized patients in Sudan

BackgroundCOVID-19 was primarily reported in China. The mortality rate across countries had ranged from 1% up to more than 10% and it is underestimated in some countries. Advanced age is the most frequently reported factor associated to mortality. Other factors were the presence of comorbidities such as diabetes mellitus, hypertension and obesity. Several models for mortality prediction had been developed to assist in improving the prognosis. The aim of our study was to assess the factors related to mortality among COVID-19 patients and develop a prediction model based on these factors. MethodsA retrospective cohort study assessed the factors related to the mortality among COVID-19 patients who attended Imperial Hospital isolation centre on November-December, 2020, Khartoum, Sudan. Statistical tests performed were chi-square test, odds ratio and regression to develop the prediction model. Tests were considered statistically significant when p < 0.05. Results105 patients were studied. 29% of the patients were deceased, while, 71% were discharged alive. A statistically significant association was found between the age and severity with regards to mortality rate (p=0.034, 0.018 respectively). The model equation for mortality prediction: Mortality = -14.724+ (1.387* Age) + (-0.323* Gender) + (1.814* Admission) + (0.193* Ischemic Heart Disease) + (-0.369* Fever) + (1.595* Cough) + (1.953* Complications) + (0.149* Duration of hospitalization) + (0.999* Enoxaparin dose). ConclusionsAge, admission ward, cough and enoxaparin dose were statistically significant predictors for COVID-19 mortality (p= 0.014, 0.011, 0.015, 0.006 respectively).