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.

Investigation of a COVID-19 outbreak in a University Cardio-Thoracic Hospital in Cairo: exploration of the risk to healthcare workers and patients.

Background: Corona virus Disease 2019 (COVID-19) pandemic has posed a challenge to health sectors all over the world. The pandemic arrived in Egypt a few weeks after Europe and Asia, with rapidly rising numbers. Health care workers (HCWs) are front liners sustaining a major risk of acquiring the infection. Aim: In this work, we analyse an outbreak of COVID-19 in a University hospital in Cairo involving HCWs of different categories, patients and patients' accompanying relatives. Methods: Following the reporting of the first COVID-19 confirmed case; a 55-year-old nurse at the hospital, a total of 645 healthcare workers, patients and patients' accompanying relatives were tested for SARS-CoV-2 by real-time reverse transcription polymerase chain reaction (rRT-PCR) assay. Results: Twenty-four out of 589 HCWs, 3 out of 42 patient and 4 out of 14 patients' accompanying relatives tested positive for COVID-19. No physicians, pharmacists or technicians were infected. Nursing staff and housekeeping staff were the most at risk of contracting the infection with a risk ratio of 4.99 (95% CI: 1.4-17.6) and 5.08 (95% CI: 1.4-18.4) respectively. Clustering of infected HCWs was observed in paediatrics' ICU and in the 6th floor of the hospital. Conclusions: Nursing and housekeeping staff sustain a significantly higher risk of COVID-19 infection compared to other staff categories. The nature of their duties and the frequent unprotected contact between members of these categories may play a role in increasing their risk.

SARS-CoV-2 PCR positivity rate and seroprevalence of related antibodies among a sample of patients in Cairo: Pre-wave 2 results of a screening program in a university hospital.

BACKGROUND: Research has revealed that asymptomatic and pre-symptomatic infections are important contributors to the transmission of SARS-CoV-2 in populations. In Egypt, the true prevalence of infections is veiled due to the low number of screening tests. The aim of this study was to determine the SARS-CoV-2 PCR positivity rate as well the seroprevalence of the SARS-CoV-2 antibodies before the ultimate development of a second wave of the epidemic in Cairo, Egypt. METHODS: Our study was carried out between May 5 and the end of October 2020. It included all patients requiring admission to Ain Shams University hospitals. An interview questionnaire was used to collect demographic and clinical data. Laboratory tests for all participants included RT-PCR and total antibody assay for SARS-CoV-2. RESULTS: A total of 4,313 subjects were enrolled in our study, with females representing 56% of the sample. Adults and middle-aged individuals represented around 60% of the study sample. The positivity rate of SARS-CoV-2 PCR was 3.84% (95% CI 3.29-4.48), and the SARS-CoV-2 antibody seroprevalence was 29.82% (95% CI: 28.16-31.51). Males showed a higher risk for getting the COVID-19 infection, while middle-age group had significantly higher antibody seroprevalence rates. CONCLUSION: SARS-CoV-2 infection imposes a high burden on the community as detected by high seroprevalence rates.