Journal of King Abdulaziz University: Medical Sciences

Prevalence, Clinical Features, and Management of Hydatid Disease in Saudi Arabia: Systematic Review

2024-09-07T14:32:51+00:00

Hydatidosis, caused by Echinococcus granulosus, is an endemic parasitic disease worldwide. The most frequent anatomic locations are the liver and lung. This systematic review examined the prevalence, clinical features, diagnosis, and management of hydatid disease in Saudi Arabia. Six databases (PubMed, Medline, Ovid, Scopus, Web of Science, and Cochrane) were searched using the keywords “Hydatid AND Saudi Arabia” in the title and abstract. All papers investigating the hydatid diseases in Saudi Arabia were included in the systematic review. Eight articles were considered suitable for the systematic review of 82 papers that were extracted through the database search. The studies enrolled 835 patients, of whom 440 cases were diagnosed with hydatid disease. The prevalence of hydatid disease among patients with liver diseases ranged between 3.9 and 5.6% during the period from 1978 to 2014. In addition, the liver was the most reported infected organ with hydatid diseases, followed by the lungs among patients. Some studies diagnosed hydatid disease among asymptomatic patients, while others reported gastrointestinal, respiratory, and musculoskeletal symptoms. The most commonly reported diagnostic methods were indirect hemagglutination (IHA), ultrasonography, and Computed Tomography (CT) scans for locating cysts. A combined approach of surgical interventions such as endocystectomy and cystoperiocystectomy with medical therapy has shown greater effectiveness despite some associated complications like anaphylaxis, mild hypernatremia, biliary leakage, and bronchopleural fistula.

Improving treatment outcomes and minimizing complications requires a multidisciplinary approach that combines surgical expertise with medical therapy, increased public awareness, and early diagnosis promotion.

Site-Directed Mutagenesis in Viral Glycoprotein and Its Role in Viral Diagnostics and Therapy

2024-11-17T05:47:45+00:00

Site-directed mutagenesis introduces precise mutations into viral glycoprotein genes, allowing the study of their structural and functional roles and interactions with host cells. By modifying specific amino acids, researchers can assess the impact on viral entry, replication, and immune evasion. Engineered glycoproteins improve diagnostic assays sensitivity and specificity and facilitate the development of better vaccine antigens. Therapeutically, site-directed mutagenesis aids in designing antiviral drugs targeting specific glycoprotein regions and developing attenuated viral strains for vaccines. Additionally, this approach enhances understanding of viral evolution and adaptation, offering insights into future pandemic threats and aiding preparedness efforts.

The prevalence Regarding the Use of Glucagon-like Peptide-1 (GLP-1) Agonists as an Obesity Treatment among Adult Patients at King Abdulaziz University Medical Services Center, Jeddah, Saudi Arabia: a Descriptive Cross-Sectional Study

2024-09-26T13:36:15+00:00

Background: Glucagon-like peptide-1 (GLP-1) receptor agonists are effective to achieve and sustain body weight reductions in obese individuals.

Objectives: To assess the prevalence of GLP-1 agonists used for weight management and associated adverse effects among adult populations at King Abdulaziz University Medical Services Center, Saudi Arabia.

Methods: A cross-sectional study was done at on 188 participants using GLP-1. A questionnaire was used to collect data about participants’ demographics, chronic diseases, smoking, weight, height, family support to lose weight, obesity causes, weight loss attempts, pattern of GLP-1 agonists use, the negative side effects GLP-1 agonists use and patients' satisfaction.

Results: The mean age was 46.24 ± 12.78 years, the mean BMI was 34.78 ± 5.3 kg/m², and 80.9% were obese. The most commonly used GLP-1 agonists were semaglutide (66%), for 86.2% the medication was recommended by a physician and the mean medication use duration was 12.43 ± 14.73 months. The mean number of kilograms lost during treatment was 10.11 ± 6.53 kg, 70.2% had negative side effects with nausea (51.1%) the most common. Of them 65.5% were satisfied and 78.7% would recommend others to use GLP-1. Absence of negative effects was significantly higher among those using the medication for diabetes and weight reduction.

Conclusion: GLP-1 receptor agonists are promising agents for the treatment of obesity as the mean weight reduction during the drug use among participants was about 10 kilograms. Despite the side effects, the majority were satisfied with the drug and would recommend others to use it.

The association between playing video games and thumb/wrist pain among medical students

2024-08-19T22:40:15+00:00

De Quervain’s disease is characterized by stennosing tenosynovitis in the first extensor wrist compartment. With the growing popularity of video gaming, the incidence of de Quervain’s disease has continued to rise among teenagers and youths. There is a need to determine the correlation between gaming and de Quervain’s disease. To assess the association between playing video games and thumb and wrist pain among medical students in the King Abdulaziz University.

This cross-sectional survey study was conducted among medical students at the King Abdulaziz University between July 2020 and October 2020. Statistical analyses were performed using SPSS version 23.

Most medical students (82%) played video games; among them, 36% and 59% reported using PlayStations and mobile phones, respectively. The mean ± SD pain severity was 1.63 ± 2.65, with 1.4% and 62.9% reported experiencing the most severe pain and no pain, respectively. Further, 12.9%, 15.1%, and 10.1% of the participants reported stretching their fingers before playing, having problems carrying things, and the pain affecting their daily activities, respectively.

Most of our participants played video games mainly using mobile phones and PlayStations. However, a majority of them did not experience any pain; moreover, we observed an association of pain episodes and severity with the playing duration and devices used

Recombination Dynamics Divergent of the RGD Region of Penton, Hexon and Fiber Genes for Adenovirus

2024-10-27T17:52:49+00:00

Most recent adenovirus research has focused on using the virus as a vector, with limited attention paid to its evolution and genome stability. Traditional serological typing methods are insufficient for adenoviruses, leading to the use of sequencing limited regions of hexon and fiber genes. However, multiple recombination events have been identified within the adenovirus genome, suggesting that this limited typing approach may be unreliable.

This study sequenced the penton gene of nine adenoviruses with previously agreed-upon hexon and fiber types. Six of these isolates exhibited a penton type different from their hexon and fiber types, indicating recombination between different viral types. Additionally, four of these six isolates had penton sequences with significant divergence from known adenovirus types. Further analysis revealed potential recombination events within the penton gene itself, between the hypervariable region the RGD loop.

These findings highlight the prevalence of recombination in species D adenoviruses, not only between hexon and fiber genes but also between penton and hexon/fiber genes. Furthermore, intra-penton recombination events are common. This emphasizes the limitations of limited hexon/fiber typing and underscores the need for full genome sequencing for accurate adenovirus typing. These considerations are crucial for the development of adenovirus-based vectors.

Modeling Discrete-Event Simulations Using Natural Language Processing: A Healthcare Application

2024-11-30T03:31:16+00:00

Discrete-event simulation (DES) is widely used to model complex healthcare systems; however, manually developing these simulation models often requires extensive effort and specialized expertise. This study explored how natural language processing (NLP) techniques can automate DES model generation from text descriptions and optimize resource allocation in the healthcare domain. We used GPT-4o large language model to demonstrate that DES models can be automatically generated from natural language prompts with accuracy comparable to traditional simulation software. The GPT-4o model successfully simulated a skin care clinic and a complex medical care facility, producing results aligned with Arena software for metrics such as average queue times and patient throughput. Additionally, GPT-4o determined the optimal resource allocation to minimize costs while satisfying the patient waiting time constraints. The automated generation of simulations shows the potential to combine NLP with DES to accelerate healthcare system modeling and optimization.