Developing a mortality risk prediction model using data of 3663 hospitalized COVID-19 patients: a retrospective cohort study in an Egyptian University Hospital.

PURPOSE: Since the declaration of COVID-19 as a pandemic, a wide between-country variation was observed regarding in-hospital mortality and its predictors. Given the scarcity of local research and the need to prioritize the provision of care, this study was conducted aiming to measure the incidence of in-hospital COVID-19 mortality and to develop a simple and clinically applicable model for its prediction. METHODS: COVID-19-confirmed patients admitted to the designated isolation areas of Ain-Shams University Hospitals (April 2020-February 2021) were included in this retrospective cohort study (n = 3663). Data were retrieved from patients' records. Kaplan-Meier survival and Cox proportional hazard regression were used. Binary logistic regression was used for creating mortality prediction models. RESULTS: Patients were 53.6% males, 4.6% current smokers, and their median age was 58 (IQR 41-68) years. Admission to intensive care units was 41.1% and mortality was 26.5% (972/3663, 95% CI 25.1-28.0%). Independent mortality predictors-with rapid mortality onset-were age ≥ 75 years, patients' admission in critical condition, and being symptomatic. Current smoking and presence of comorbidities particularly, obesity, malignancy, and chronic haematological disorders predicted mortality too. Some biomarkers were also recognized. Two prediction models exhibited the best performance: a basic model including age, presence/absence of comorbidities, and the severity level of the condition on admission (Area Under Receiver Operating Characteristic Curve (AUC) = 0.832, 95% CI 0.816-0.847) and another model with added International Normalized Ratio (INR) value (AUC = 0.842, 95% CI 0.812-0.873). CONCLUSION: Patients with the identified mortality risk factors are to be prioritized for preventive and rapid treatment measures. With the provided prediction models, clinicians can calculate mortality probability for their patients. Presenting multiple and very generic models can enable clinicians to choose the one containing the parameters available in their specific clinical setting, and also to test the applicability of such models in a non-COVID-19 respiratory infection.

Incidence and Prognosis of Acute Kidney Injury with COVID-19 in Hospitalized Egyptian Patients

Background: The recent worldwide pandemic of COVID-19 has been a serious, multidimensional problem that has left a detrimental worldwide impact on individuals of all ages and several organ systems. The typical manifestation of kidney involvement is acute kidney injury (AKI);however, there is a lack of consensus data regarding AKI epidemiology in COVID-19. Objective: The aim of the current work was to study the incidence and prognosis of acute kidney injury among patients hospitalized with COVID-19. Subjects and methods: This retrospective, observational cohort study was conducted on 163 COVID19 patients diagnosed by RT-PCR and carried in Inpatient and ICU of Geriatric Isolation Hospital, Ain Shams University hospitals for COVID19. Results: As regard predictors for AKI;each of presence of chronic kidney disease, mechanical ventilation, CRP > 74, and TLC >13 had high predictive value for occurrence of AKI among hospitalized COVID 19 patients. Conclusion: It could be concluded that AKI in COVID-19 patients is associated with a high mortality rate in ICUCOVID-19 patients. Our findings suggest that COVID-19 patients, particularly ICU COVID-19 patients, should be closely monitored for the development of AKI. Early identification of AKI, as well as prompt intervention, can improve COVID-19 patient outcomes. [ FROM AUTHOR] Copyright of Egyptian Journal of Hospital Medicine is the property of Egyptian Journal of Hospital Medicine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)