Hyperlipidemia is a lipid metabolism disorder that refers to increased levels of total triglycerides (TGs), cholesterol (TC), and low-density lipoprotein-cholesterol (LDL-C) and decreased levels of high-density lipoprotein-cholesterol (HDL-C). It is a major public health issue with increased prevalence and incidence worldwide. The ability to identify individuals at risk of this disorder before symptoms manifest will facilitate timely intervention and management to avert potential complications. This can be achieved by employing metabolomics as an early detection method for the diagnostic biomarkers of hyperlipidemia. Metabolomics is an analytical approach used to detect and quantify metabolites. This provides the ability to explain the metabolic processes involved in the development and progression of certain diseases. In recent years, interest in the use of metabolomics to identify disease biomarkers has increased, and several biomarkers have been discovered, such as docosahexaenoic acid, glycocholic acid, citric acid, betaine, and carnitine. This review discusses the primary metabolic alterations in the context of hyperlipidemia. Furthermore, we provide an overview of recent studies on the application of metabolomics to the assessment of the efficacy of traditional herbal products and common lipid-lowering medications.

Objectives: This study aimed to evaluate the performance of four AI models, (GPT-5, GPT-4, Microsoft Copilot, and Google Gemini), in detecting medication errors through pediatric case scenarios. Methods: A total of 60 pediatric cases were analyzed for the presence of medication errors, of which only half contained errors. The cases covered four therapeutic systems (respiratory, endocrine, neurology, and infectious). The four models were exposed to the cases in both English and Arabic using a unified prompt. The responses for each model were used to calculate various performance metric cover accuracy, sensitivity, specificity and reproducibility. Analysis was carried out using SPSS version 22. Results: Microsoft Copilot demonstrated relatively higher accuracy (86.7% in English, 85.0% in Arabic) compared to other models in this dataset, followed by GPT-5 (81.7% in English, 75.0% in Arabic). GPT-4 and Google Gemini had less accuracy, with Gemini having the lowest accuracy across all languages (76.7% in English, and 73.3% in Arabic). Microsoft Copilot showed comparatively higher sensitivity and specificity, particularly in cases of respiratory and infectious diseases. The accuracy in Arabic was lower compared to that of English for the majority of models. Microsoft Copilot exhibited relatively higher reproducibility and inter-run agreement (Cohen’s Kappa = 0.836 English, 0.815 Arabic, p < 0.001 for both), while Gemini showed the lowest reproducibility. For inter-language agreement in general, Copilot showed the highest Cohen’s Kappa of 0.701 for English and Arabic (p < 0.001). Conclusions: In our evaluation, Microsoft Copilot demonstrated relatively higher performance in pediatric drug error detection compared to the other AI models. The decreased performance in Arabic points toward the requirement of improved multilingual training for supporting equal AI aid across languages. This study highlights the importance of human oversight and domain-based training for AI tools in pediatric pharmacotherapy.

Background/Objectives: Collaboration between physicians and community pharmacists (CPs) is important for ensuring high-quality healthcare delivery. However, evidence on physician–CP collaboration in Jordan remains limited, and no studies have specifically examined physicians’ perspectives on collaboration with CPs. This study aimed to explore physicians’ experiences and attitudes towards collaboration with CPs, their views on the impact of such collaboration on patient care, and their perceptions of CPs’ professional roles. Methods: Between January and March 2025, a cross-sectional survey was conducted among 380 physicians in Amman, Jordan, using convenience sampling. A five-section self-administered questionnaire was used to collect the data. Data were analysed using descriptive and inferential methods in SPSS version 28. Results: Of the 380 physicians directly invited to participate, 209 completed the questionnaire. All participants reported previous collaboration with CPs, although the frequency varied. Nearly half of the participants reported that collaboration occurred sometimes (47.4%, n = 99). Physicians perceived that CPs only sometimes had adequate clinical skills (59.3%, n = 124), confidence (61.2%, n = 128), or knowledge (65.6%, n = 137) to deliver effective patient care. Most physicians (>74%) demonstrated positive attitudes towards collaboration with CPs, particularly regarding communication, mutual respect, and shared goals in patient care. Nevertheless, neutral attitudes were reported towards trust in CPs’ professional decisions (42.1%, n = 88), meeting professional expectations (33.0%, n = 69), and therapeutic expertise (46.9%, n = 98). Almost all physicians agreed that collaboration with CPs could improve patient outcomes (98.1%, n = 205) and continuity of care (89.0%, n = 186). Physicians also expressed positive perceptions of CPs’ professional roles, mainly in improving medication adherence (91.9%, n = 192). Significant overall differences in attitude (p = 0.035) and perception (p = 0.025) scores were observed according to physicians’ job description; however, post hoc analysis identified a significant pairwise difference only for perception scores between general practitioners and specialists. Conclusions: This study found that the majority of physicians reported previous collaboration with CPs and generally held positive views and attitudes towards collaborative practice. However, uncertainty regarding CPs’ expertise and decision-making abilities suggests the necessity of professional role clarification and trust-building. These findings should be interpreted in the context of a convenience sample of physicians practising in Amman, predominantly in the private sector, and should not be generalised to all physicians in Jordan. Future research exploring CPs’ perspectives on collaboration with physicians is needed to support the findings of this study.