Suchergebnisse

BACKGROUND: Familial Hypercholesterolemia (FH) is an inherited and complex multifactorial disease that can lead to early onset of coronary artery disease (CAD). Diagnosis, treatment, and management of FH require a well-trained physician with high awareness of the disease and different risk factors to avoid complications. MATERIALS AND METHODS: This cross-sectional study evaluated family physicians' awareness and knowledge of FH using self-administered questionnaires in governmental hospitals in Riyadh, Saudi Arabia, during 2018. RESULTS: A total of 225 family physicians completed the questionnaire, with a response rate of 58.4%. The mean age of respondents was 31.3 years and more than 59.1% were men. Although 72.4% of physicians rated their familiarity with FH as average and above, 48.4% of all participants had poor FH knowledge, while only 51.6% had acceptable FH knowledge. About 65.8% of physicians reported that they routinely take a detailed family history, perform a physical examination, and screen close relatives. Awareness of various clinical algorithms for diagnosis of patients with FH was very low at 52.0%. The mean FH knowledge and familiarity scores were significantly higher (P < 0.001) among participants who were older, had higher training levels, or longer years in practice. CONCLUSIONS: The current study revealed significant deficits in FH familiarity, awareness, knowledge, and practice among Saudi physicians. FH educational programs directed at all physicians involved in FH patients' management are necessary to improve physicians' knowledge of all aspects of FH management, including the importance of a mechanism for identifying people at risk for a genetic condition by a process of systematic family tracing.

Background: Self-medication is a global phenomenon that is common in developing countries where people can buy prescription medicines without a physician's advice. Irresponsible self-medication may have an effect at the individual level as well as the community level. At the individual level, self-medication may cause potential health risks including wrong diagnosis, incorrect medication prescriptions, adverse events, failure to recognize pharmaceutical risks and contraindications, and prolonged use of drugs resulting in potential physical harm. At the community level, self-medication may promote drug-induced diseases, leading to wasteful public expenditure. Methodology: A substantial sample size of 2979 patients was collated from August 2016. The questionnaire was promulgated through electronic means to patients from all over Saudi Arabia. Informed consent was taken from all patients prior to the questions within the questionnaire. The privacy of the respondents was respected, and all data was analysed anonymously. Results: the majority of participants (74.4%) were young adults between the ages of 21 – 40. 81.4% of respondents had used a prescription drug without first obtaining a physician's advice. The drugs used without prescription were analgesics (84.1%), antipyretics (70.9%), antitussive syrups (46.9%). Conclusions: The frequency of self-medication in KSA is alarmingly high, where the most common type of drug used without a prescription is analgesics. There is a need for larger studies to evaluate the cause and outcome of self-medication in KSA, so that proper legislation and policies can be implemented to provide a better and safer healthcare system that is easy for every Saudi individual to access.

Background: Ciprofloxacin, a fluoroquinolone antibiotic patented in 1983 and FDA-approved in 1987, is widely used for bacterial infections. It treats urinary tract infections (UTIs), pneumonia, and more, including off-label uses like Crohn's disease and cancer cell suppression. Aim: To provide an overview of ciprofloxacin's uses, mechanism of action, pharmacokinetics, administration, and associated adverse effects. Methods: A comprehensive review of literature and guidelines examined ciprofloxacin's therapeutic applications, effectiveness, resistance patterns, and patient-specific considerations. Results: Ciprofloxacin demonstrates a broad antimicrobial spectrum, primarily by inhibiting DNA replication via DNA gyrase and topoisomerase. It exhibits high tissue penetration, reaching therapeutic levels in various fluids and tissues, including CSF under inflammation. Resistance mechanisms include DNA gyrase mutations and efflux pump activity, limiting efficacy in some settings. Ciprofloxacin is effective in oral, intravenous, and topical formulations, with renal excretion as the primary elimination pathway. However, adverse effects like tendonitis, QT prolongation, neuropsychiatric events, and rare severe dermatological reactions are reported. Use in neonates, pregnancy, and breastfeeding is restricted to specific indications. Conclusion: Ciprofloxacin remains a valuable antimicrobial agent despite resistance concerns and adverse effects. Its targeted use based on infection severity, patient comorbidities, and resistance patterns ensures optimized outcomes. Further research into resistance mitigation and alternative therapies is critical to preserve its efficacy.

EMS is an important link in the chain of disaster management and outlines the approach to emergency healthcare and the number of people saved during large-scale disasters. Here, the preparedness, implementation, and issues connected with EMS in regard to disasters will be critiqued in this paper. The current paper is an exploratory study that looks at how efficient EMS systems are in disaster areas: training, coordination, resource management, and technological integration through the review of literature and analysis of recent global disasters. The study indicates that although EMS is central to disaster management, factors like lack of resources, inadequate communication channels, and pressure on personnel limit the effectiveness of disaster response. Given this, the paper recommends improvement in the personnel training about technology as well as in the area of communication. Moreover, it suggests introducing psychological traumatization for the staff of the EMs and pledging for better apparatus. The outcomes presented here are written as recommendations that practitioners may use to enhance the functioning of EMS systems, increase organizational coherence, improve system cooperation, improve professional care, facilitate material coordination, and improve communication aid.

Over the last decade, healthcare organizations worldwide have faced many challenges mainly concerned with their services' efficiency, effectiveness, and quality. There has been a pressing need for healthcare organizations to embrace or adopt new approaches to managing the quality of services to enhance patient satisfaction. Quality management plays a role in determining healthcare outcomes and patient satisfaction in hospitals. Aim: to examine the connection between total quality management (TQM) and patient satisfaction (PSAT). Methodology: a quantitative cross-sectional correlational study, a convenience sample of 320 in-patients receiving treatment at a governmental hospital, Alnoor Hospital in Saudi Arabia. Data was collected using two questionnaires: total quality management (TQM) and patient satisfaction (PSAT) with data analysis conducted using SPSS26. Conclusion: The findings revealed that total quality management positively influenced patient satisfaction. Limitation: Since there are fewer studies on total quality management in the healthcare sector than in manufacturing industries, this research makes a substantial contribution to the body of literature already in existence and merits additional study. Furthermore, this research offers significant perspectives for managers in the healthcare industry about strategic planning and decision-making procedures.

Radiation therapy is crucial in cancer treatment, yet access remains limited due to inadequate infrastructure and workforce shortages. The integration of artificial intelligence (AI) in radiological workflows holds the potential to enhance efficiency and improve patient outcomes.This review analyzes the current landscape of AI applications in radiation oncology, focusing on various stages of the treatment process, including decision-making, treatment planning, and quality assurance. We evaluated the capabilities of AI techniques, particularly deep learning algorithms, in automating tasks such as image segmentation and dose optimization. The findings indicate that AI can significantly improve the accuracy and consistency of treatment planning by facilitating automated tumor delineation and enhancing image registration processes. Moreover, AI-driven predictive models have shown promise in forecasting treatment responses and optimizing radiation doses tailored to individual patient anatomies. However, the clinical adoption of these technologies is hindered by challenges, including the black-box nature of AI algorithms, the need for extensive validation, and concerns regarding data privacy.While the potential of AI to revolutionize radiation oncology is evident, significant barriers must be addressed before widespread implementation can occur. Future efforts should focus on developing interpretable AI systems, establishing robust validation frameworks, and integrating AI tools into existing clinical workflows to enhance the quality of cancer care globally.