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BACKGROUND:Egypt is among the world top 10 countries in diabetes prevalence. It is the first country among the MENA region. Healthy lifestyle education and support help people with diabetes to improve health outcomes. Many physical and psychological barriers can hinder patients from following a healthy lifestyle.AIM:This study aimed to examine the effect of lifestyle modification educational sessions in helping Egyptian patients to overcome main barriers of diabetes self-management through improving nutritional behaviours, physical activity, medication compliance, and blood glucose monitoring.METHODS:A cohort study included 205 patients with type 2 diabetes. Baseline assessment of patients’ lifestyle behaviours and barriers using personal diabetes questionnaire of Louisville University, with both anthropometric and blood glucose assessment. Interventional lifestyle health education was provided weekly through multiple integrated techniques, followed by a post-intervention assessment to evaluate the effect of the health education sessions. Statistical analysis was done to identify any statistically significant difference before and after the health education intervention.RESULTS:There was a significant improvement of the post-education mean scores of the studied behaviours when compared with the pre-education scores of the participants’ behaviours (p < 0.001). There was also a significant reduction in the barriers facing patients to diabetes self-management including nutritional barriers (P < 0.001), medication compliance barriers (P < 0.001) with a percent change (43%), physical activity barriers (p < 0.001), and blood glucose monitoring (p < 0.001) with a percent change (44%).There was a statistically significant positive correlation between improvement of medication compliance (P = 0.027), blood glucose monitoring(P = 0.045), and glycated haemoglobin of the study participantsCONCLUSION:lifestyle modification education of type 2 diabetic patients can overcome the main barriers of following a healthy lifestyle and improve their anthropometric measures and blood glucose level.

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The Egy-Score is a promising, accurate, easily calculated, cost-effective score in the prediction of hepatic fibrosis in chronic HCV patients with superiority over APRI, FIB-4 and Forns' index in advanced hepatic fibrosis and cirrhosis.

Introduction: The recently discovered novel coronavirus disease (COVID-19) has emerged in Wuhan, China, since January 2020. Egypt reported a low incidence of infection when compared with other countries. The aim of the study was to assess the characterization of COVID-19 infection among the Egyptian population. Methodology: Data were collected from a single COVID-19 quarantine hospital in Cairo. A total number of 195 cases were included with their clinical, laboratory, and radiological data. Results: Three different age groups behaved differently for COVD-19 infection. The pediatric age group was asymptomatic entirely, the middle age group (18-50 years) were asymptomatic in 53.3% of cases, while 77.9% of those above 50 years were symptomatic (p ≤ 0.001). The latter group had a high incidence of COVID-pneumonia in (83.1%), and moderate to critical presentations were encountered in 66.3% of them. Neutrophil to lymphocyte (N/L) ratio correlated directly with the age and case severity. C-reactive protein (CRP) and computed tomography scan chest (CT-chest) had added value on COVID-19 diagnosis in suspected cases. Conclusions: In Egypt, patients above 50 years are at a higher risk for symptomatic COVID-19 infection and leaner for moderate to critical COVID-19 presentation. The triad of CT-chest, CRP, and N/L ratio could be an integrated panel for assessing disease severity.

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Background This work aimed to identify the mathematical model and ecological pattern of COVID-19 infection and mortality across different countries during the first six months of the pandemic. Methodology In this pilot study, authors used the online available data sources of randomly selected 18 countries to collect ecological predictors of COVID-19 transmissibility and mortality. The studied determinants were environmental factors (daily average temperature, daily humidity) and socioeconomic attributes (population age structure, count and density, human development index, per capita income (PCI), gross domestic product, internet coverage, mobility trends, chronic diseases). Researchers used the linear and exponential time series analysis, and further utilize multivariate techniques to explain the variance in the monthly exponential growth rates of new cases and deaths. Result In the first two months, the R 2 of linear models for the cases and deaths were higher than that of the corresponding R 2 of the exponential model. Later one, R 2 of the exponential model was occasionally relatively higher than that of the linear models. The exponential growth rate of new cases was significantly associated with mobility trends (β=0.00398, P =0.002), temperature (β=0.000679, P =0.011), humidity (β=0.000249, P =0.000), and the proportion of patients aged above 65 years (β=-0.000959, P =0.012). Similarly, the exponential growth rate of deaths was significantly associated with mobility trends (β=0.0027, P =0.049), temperature (β=0.0014, P<0.001), humidity (β=-0.0026, P=0.000), and PCI of countries. During this period, COVID-19 transmissibility was evident to be controlled as soon as social mobility is decreased by about 40% of the baseline over 3 months controlling for the other predictors. Conclusion Controlling of COVID-19 pandemic is based mainly on controlling social mobility. Role of environmental determinants like temperature and humidity was well noticed on disease fatality and transmissibility. COVID-19 contagiousness and fatality were additionally affected by human modifiable risk factors like income and non-modifiable risk factors (ageing) affected.

Serum levels of alpha-fetoprotein (AFP) were reported to increase in patients with significant or advanced hepatic fibrosis. Combination of non-invasive tests decreases the use of liver biopsy in large proportion of chronic HCV patients. The aim of the study was to compare and combine AFP with commonly used non-invasive fibrosis tests in novel scores for prediction of different stages of hepatic fibrosis. Six hundred and fifty two treatment naïve chronic hepatitis C patients were enrolled. Demographic data, basic pre-treatment laboratory tests including complete blood count (CBC), liver biochemical profile and renal functions test, international normalized ratio (INR) in addition to AFP, liver stiffness measurement (LSM) by Fibroscan and liver biopsies were retrospectively analyzed. AST to Platelet Ratio Index (APRI) and FIB-4 scores were calculated. Different predictive models using multivariate logistic regression analysis were generated and presented in equations (scores) composed of a combination of AFP, LSM plus FIB-4/APRI scores. AFP was correlating significantly with LSM, FIB-4, and APRI scores. Areas under receiver operating characteristic curves (AUROCs) for predicting significant hepatic fibrosis, advanced hepatic fibrosis, and cirrhosis were 0.897, 0.931, and 0.955, respectively, for equations (scores) containing AFP, LSM, and FIB-4. AUROCs for predicting significant hepatic fibrosis, advanced hepatic fibrosis and cirrhosis were 0.897, 0.929, and 0.959, respectively, for equations (scores) containing AFP, LSM, and APRI. The study shows that combining AFP to serum biomarkers and LSM increases their diagnostic performance for prediction of different stages of liver fibrosis.