Understanding the Knowledge, Attitude and Behaviour (Practice) of Saudi Arabian Patients with Diabetes Type 2

This qualitative study explored knowledge, attitude and practices of male T2DM patients in rural and urban populations of Riyadh, Saudi Arabia. Participants included 40 male patients aged 35 to 65 years with T2DM and 20 health care providers from rural and urban areas. Using a Grounded Theory approach three models were developed to describe the influences of T2DM management for rural patients; for urban patients and the perspectives of health care providers on T2DM management

COVID-19 pandemic’s impact on eating habits in Saudi Arabia

Background: COVID-19 virus has been reported as a pandemic in March 2020 by the WHO. Having a balanced and healthy diet routine can help boost the immune system, which is essential in fighting viruses. Public Health officials enforced lockdown for residents resulting in dietary habits change to combat sudden changes. Design and Methods: A cross-sectional study was conducted through an online survey to describe the impact of the COVID-19 pandemic on the eating habits, quality and quantity of food intake among adults in Saudi Arabia. SPSS version 24 was used to analyze the data. Comparison between general dietary habits before and during COVID-19 for ordinal variables was performed by Wilcoxon Signed Rank test, while McNemar test was performed for nominal variables. The paired samples t-test was used to compare the total scores for food quality and quantity before and during COVID-19 periods.Results: 2706 adults residing in Riyadh completed the survey. The majority (85.6%) of the respondents reported eating home-cooked meals on a daily basis during COVID-19 as compared to 35.6% before (p<0.001). The mean score for the quality of food intake was slightly higher (p=0.002) before the COVID-19 period (16.46±2.84) as compared to the during period (16.39±2.79). The quantity of food mean score was higher (p<0.001) during the COVID-19 period (15.70±2.66) as compared to the before period (14.62±2.71).Conclusion: Dietary habits have changed significantly during the COVID-19 pandemic among Riyadh residents. Although some good habits increased, the quality and the quantity of the food was compromised. Public Health officials must focus on increased awareness on healthy eating during pandemics to avoid negative consequences. Future research is recommended to better understand the change in dietary habits during pandemics using a detailed food frequency questionnaire

Radiomics-based machine learning approach for the prediction of grade and stage in upper urinary tract urothelial carcinoma:a step towards virtual biopsy

Objectives: Upper tract urothelial carcinoma (UTUC) is a rare, aggressive lesion, with early detection a key to its management. This study aimed to utilise computed tomographic urogram data to develop machine learning models for predicting tumour grading and staging in upper urothelial tract carcinoma patients and to compare these predictions with histopathological diagnosis used as reference standards.Methods: Protocol-based computed tomographic urogram data from 106 patients were obtained and visualised in 3D. Digital segmentation of the tumours was conducted by extracting textural radiomics features. They were further classified using 11 predictive models. The predicted grades and stages were compared to the histopathology of radical nephroureterectomy specimens.Results: Classifier models worked well in mining the radiomics data and delivered satisfactory predictive machine learning models. The multilayer panel showed 84% sensitivity and 93% specificity while predicting UTUC grades. The Logistic Regression model showed a sensitivity of 83% and a specificity of 76% while staging. Similarly, other classifier algorithms [e.g. Support Vector classifier (SVC)] provided a highly accurate prediction while grading UTUC compared to clinical features alone or ureteroscopic biopsy histopathology.Conclusion: Data mining tools could handle medical imaging datasets from small (<2 cm) tumours for UTUC. The radiomics-based machine learning algorithms provide a potential tool to model tumour grading and staging with implications for clinical practice and the upgradation of current paradigms in cancer diagnostics.Clinical Relevance: Machine learning based on radiomics features can predict upper tract urothelial cancer grading and staging with significant improvement over ureteroscopic histopathology. The study showcased the prowess of such emerging tools in the set objectives with implications towards virtual biopsy

Radiomics-based machine learning approach for the prediction of grade and stage in upper urinary tract urothelial carcinoma:a step towards virtual biopsy

Objectives: Upper tract urothelial carcinoma (UTUC) is a rare, aggressive lesion, with early detection a key to its management. This study aimed to utilise computed tomographic urogram data to develop machine learning models for predicting tumour grading and staging in upper urothelial tract carcinoma patients and to compare these predictions with histopathological diagnosis used as reference standards.Methods: Protocol-based computed tomographic urogram data from 106 patients were obtained and visualised in 3D. Digital segmentation of the tumours was conducted by extracting textural radiomics features. They were further classified using 11 predictive models. The predicted grades and stages were compared to the histopathology of radical nephroureterectomy specimens.Results: Classifier models worked well in mining the radiomics data and delivered satisfactory predictive machine learning models. The multilayer panel showed 84% sensitivity and 93% specificity while predicting UTUC grades. The Logistic Regression model showed a sensitivity of 83% and a specificity of 76% while staging. Similarly, other classifier algorithms [e.g. Support Vector classifier (SVC)] provided a highly accurate prediction while grading UTUC compared to clinical features alone or ureteroscopic biopsy histopathology.Conclusion: Data mining tools could handle medical imaging datasets from small (<2 cm) tumours for UTUC. The radiomics-based machine learning algorithms provide a potential tool to model tumour grading and staging with implications for clinical practice and the upgradation of current paradigms in cancer diagnostics.Clinical Relevance: Machine learning based on radiomics features can predict upper tract urothelial cancer grading and staging with significant improvement over ureteroscopic histopathology. The study showcased the prowess of such emerging tools in the set objectives with implications towards virtual biopsy

Kuwaiti EFL Students’ Perceptions of the Effectiveness of the Remedial English Course 099 at the College of Technological Studies

The study aims to evaluate the English remedial course 099 taught in the College of Technological Studies (PAAET) as part of the English program which disseminates English Language Skills to EFL students studying at this college. This study is expected to provide sufficient information to policymakers and educators involved with this program at all levels, with the intention to help them evaluate this course and make useful decisions to improve English Language Teaching in order to combat the deficiency in the English language suffered by college students in Kuwait. A number of 155 students participated in a questionnaire of 15 statements divided into four areas: reading, grammar, writing, and speaking skills. The findings of the study showed that most EFL students benefited from the English course 099, and their language skills were improved. However, there were some drawbacks and weaknesses of the program in terms of learners’ assessments and follow up. The significance of the study arises from the fact that it would enable decision-makers and course evaluators to pinpoint the strengths and weaknesses of the course and hence find ways to improve it

The Effects of Global Commodity Prices on Domestic Prices in Saudi Arabia

This paper evaluates the impacts of global commodity prices on domestic prices in Saudi Arabia with aid of econometric techniques and monthly data over the period 2000:01-2016:09. We find evidence suggesting the influential role of global commodity prices on Saudi domestic prices over long run. In particular, we find that non-fuel commodity prices have more impacts on domestic prices than energy prices. Likewise, we find evidence, based on Granger causality analysis, suggesting that global commodity prices are useful indicators in capturing the movements in domestic prices. Keywords: Global commodity prices, Domestic Prices, Saudi Arabia. JEL Classifications: C13, C22, C50, E31, Q4

Impact of tobacco smoking on oral microbiota – a case-control study.

Oral microbiota is a vital part of human microbiota, including bacterial, protozoa, viral and fungal species. Beneficial microbes form biofilms to form a first-line defense against harmful microorganisms. Tobacco smoking is considered a major environmental factor affecting the orodental microbiota. Smokers harbor more pathogenic microbes than non-smokers. In fact, cigarette smoking exposes the oral cavity to a large number of toxicants, perturbing the oral microbial ecology through various mechanisms. In Saudi Arabia, research on the impact of tobacco smoking on oral microbiota is still lacking. Therefore, this case-control study is an important addition to the literature in terms of tobacco use and its effects on oral microbiota and oral hygiene. 130 men were recruited for this study, including 65 smokers and 65 non-smokers. The following parameters were recorded for all 130 participants – age, weight, height and education. The aim of this study was to investigate and compare the effect of tobacco smoking on the oral microbiome of smokers and non-smokers. The majority of the smokers were young adults between the ages of 21 and 30 inclusive (n=27). The results show that excessive microorganism growth was seen in smokers to a greater degree than non-smokers (38.5% of smokers vs. 8.8% of non-smokers). Not surprisingly, a significant majority (85.3%) of non-smokers had moderate microorganism growth compared to only 53.8% of smokers. cigarette smoking facilitates excessive growth of oral microorganisms, predisposing smokers to various periodontal diseases. In fact, smoking perturbs the balance of oral microbiota, producing a viable environment for microbes to cause diseases. Further large scale prospective studies are required to determine the exact mechanism that causes tobacco to affect oral microbiota

The incidence of venous thromboembolism and practice of deep venous thrombosis prophylaxis in hospitalized cirrhotic patients

<p>Abstract</p> <p>Background</p> <p>Cirrhotic patients are characterized by a decreased synthesis of coagulation and anticoagulation factors. The coagulopathy of cirrhotic patients is considered to be auto-anticoagulation. Our aim was to determine the incidence and predictors of venous thromboembolism (VTE) and examine the practice of deep venous thrombosis (DVT) prophylaxis among hospitalized cirrhotic patients.</p> <p>Methods</p> <p>A retrospective cohort study was performed in a tertiary teaching hospital. We included all adult patients admitted to the hospital with a diagnosis of liver cirrhosis from January 1, 2009 to December 31, 2009. We grouped our cohort patients in two groups, cirrhotic patients without VTE and cirrhotic with VTE.</p> <p>Results</p> <p>Over one year, we included 226 cirrhotic patients, and the characteristics of both groups were similar regarding their clinical and laboratory parameters and their outcomes. Six patients (2.7%) developed VTE, and all of the VTEs were DVT. Hepatitis C was the most common (51%) underlying cause of liver cirrhosis, followed by hepatitis B (22%); 76% of the cirrhotic patients received neither pharmacological nor mechanical DVT prophylaxis.</p> <p>Conclusion</p> <p>Cirrhotic patients are at risk for developing VTE. The utilization of DVT prophylaxis was suboptimal.</p

Updates In Diagnosis And Management Of Genital Herpes

Herpes genitalia is mainly caused by herpes simplex virus type 2 and can appear as a primary or recurring infection. It is among the most prevalent sexually transmitted illnesses. This review article provides a comprehensive overview of the diagnosis, management, treatment, and prophylaxis of herpes genitalis, caused by herpes simplex virus type 2. It addresses critical areas of concern and aims to improve the often inadequate counseling and utilization of lab diagnoses, as well as provide updated information on treatment and management of the infection. This is a valuable resource for healthcare professionals and individuals seeking information on the pathogen and clinical manifestations of herpes genitalis

Impact of tobacco smoking on oral microbiota – a case-control study.

Oral microbiota is a vital part of human microbiota, including bacterial, protozoa, viral and fungal species. Beneficial microbes form biofilms to form a first-line defense against harmful microorganisms. Tobacco smoking is considered a major environmental factor affecting the orodental microbiota. Smokers harbor more pathogenic microbes than non-smokers. In fact, cigarette smoking exposes the oral cavity to a large number of toxicants, perturbing the oral microbial ecology through various mechanisms. In Saudi Arabia, research on the impact of tobacco smoking on oral microbiota is still lacking. Therefore, this case-control study is an important addition to the literature in terms of tobacco use and its effects on oral microbiota and oral hygiene. 130 men were recruited for this study, including 65 smokers and 65 non-smokers. The following parameters were recorded for all 130 participants – age, weight, height and education. The aim of this study was to investigate and compare the effect of tobacco smoking on the oral microbiome of smokers and non-smokers. The majority of the smokers were young adults between the ages of 21 and 30 inclusive (n=27). The results show that excessive microorganism growth was seen in smokers to a greater degree than non-smokers (38.5% of smokers vs. 8.8% of non-smokers). Not surprisingly, a significant majority (85.3%) of non-smokers had moderate microorganism growth compared to only 53.8% of smokers. cigarette smoking facilitates excessive growth of oral microorganisms, predisposing smokers to various periodontal diseases. In fact, smoking perturbs the balance of oral microbiota, producing a viable environment for microbes to cause diseases. Further large scale prospective studies are required to determine the exact mechanism that causes tobacco to affect oral microbiota