Dr. Mohammed Sallam - Profile on Academia.edu (original) (raw)

Papers by Dr. Mohammed Sallam

Preprint, 2025

Generative Artificial Intelligence (genAI) tools, such as ChatGPT, hold promise for higher educat... more Generative Artificial Intelligence (genAI) tools, such as ChatGPT, hold promise for higher education but also raise valid concerns. Critical questions arise regarding university educators' attitudes toward the growing use of genAI in education. This multinational study aimed to examine the determinants of genAI Perceived Usefulness and Effectiveness among educators in Arab universities. The study applied the validated Technology Acceptance Model (TAM)-based theoretical framework using the Ed-TAME-ChatGPT survey instrument. Data were collected using a selfadministered structured online questionnaire distributed in November-December 2024 via SurveyMonkey platform. The final sample comprised 685 academics across the Gulf Cooperation Council countries, Levant/Iraq, Egypt/Sudan, and the Maghreb countries. In multivariate analyses, Social Influence (β = 0.445 and 0.531, p < 0.001) and Technology Readiness (β = 0.325 and 0.314, p < 0.001) positively predicted Perceived Usefulness and Effectiveness, respectively, while Anxiety was a negative predictor (β =-0.154 and-0.088, p < 0.001 and p = 0.007, respectively). Across demographic and academic factors, Perceived Effectiveness varied by nationality and university location, whereas Perceived Usefulness was associated with academic qualification. This study showed the ubiquitous use of genAI tools especially ChatGPT among university educators in Arab universities and confirmed the validity of the Ed-TAME-ChatGPT instrument. The findings highlighted that effective genAI integration in higher education requires specific policies that enhance technology readiness, promote a culture of peer and institutional support, and address genAI concerns. To compete in the Disclaimer/Publisher's Note: The statements, opinions, and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions, or products referred to in the content.

Diabetes, Metabolic Syndrome and Obesity, 2025

Glucagon-like peptide-1 (GLP-1) receptor agonists including Mounjaro and Ozempic, are increasingl... more Glucagon-like peptide-1 (GLP-1) receptor agonists including Mounjaro and Ozempic, are increasingly used for weight management. Assessing the attitudes and beliefs of current and future healthcare professionals is important considering their roles in recommending and prescribing these drugs. This study aimed to investigate the attitudes toward Mounjaro and Ozempic and its correlation with obesity/overweight bias among healthcare professionals and students in medicine and pharmacy in Arab countries. Methods: This cross-sectional study was based on a self-administered online questionnaire with participants recruited via a convenient snowball sampling approach. Attitudes towards Mounjaro and Ozempic were evaluated using a newly developed construct termed Mini Health Beliefs and Attitudes toward GLP-1 Drugs Scale (mini-HBAGS), alongside a novel scale to assess obesity/overweight bias (OOB). The new constructs' validity was assessed via content validity, principal component analysis (PCA), and Cronbach's α. Results: The study included 413 participants predominantly from Kuwait (32.8%), Egypt (20.9%), Saudi Arabia (18.8%), and Jordan (15.4%). Familiarity with Mounjaro and Ozempic was high (83.6%), with 17.2% recommending them. Weight management drug use was 14.0%, including 5.9% for Mounjaro and Ozempic. Among participants familiar with Mounjaro and Ozempic, the mean OOB score was 3.83±0.62 (range: 1.00-5.00), indicating agreement, while the mean score for the mini-H-BAGS was 2.70±0.716 (range: 1.00-5.00), indicating a slightly unfavorable attitude. PCA identified perceived benefits and barriers, and subjective norms and attitudes, as key determinants of attitudes toward Mounjaro and Ozempic. Conclusion: This study revealed slightly negative attitudes toward Mounjaro and Ozempic among healthcare professionals and students in Arab countries. The negative attitudes observed likely reflect concerns about side effects, cost, and accessibility of these medications. The findings highlighted the need for targeted education in Arab countries to address obesity bias and encourage a balanced evaluation of the benefits and risks of GLP-1 drugs for weight management.

Obesities, 2025

Obesity represents a global health challenge, with a critical and urgent need for long-term, sust... more Obesity represents a global health challenge, with a critical and urgent need for long-term, sustainable management strategies. Tirzepatide is a novel dual glucosedependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) receptor agonist. At first approved for the treatment of type 2 diabetes mellitus, tirzepatide represents one of the latest clinically approved and commercially available pharmacological options for obesity management. This narrative review aimed to synthesize existing clinical evidence on the efficacy and safety of tirzepatide in non-diabetic obese individuals. A comprehensive literature search was conducted using the PubMed, Scopus, Web of Science, ClinicalTrials.gov, and Google Scholar databases to identify relevant clinical trials, metaanalyses, and original studies assessing the weight-loss impact of tirzepatide from 2022 onwards. Synthesized evidence indicated that tirzepatide achieved up to 20.9% weight loss over 72 weeks (SURMOUNT-1), 18.4% after lifestyle intervention (SURMOUNT-3), 17.5% in Chinese adults (SURMOUNT-CN), and 25.3% with continued treatment over 88 weeks (SURMOUNT-4). Meta-analyses confirmed higher odds of ≥5-20% weight loss versus semaglutide and liraglutide, significantly reducing body mass index, waist circumference, blood pressure, and atherosclerotic cardiovascular disease risk. Health-related quality of life improved with greater weight loss, and gastrointestinal side effects (nausea, diarrhea, constipation) were common but mild to moderate, with <5% treatment discontinuation. Tirzepatide achieved significant weight loss, cardiometabolic benefits, and improved quality of life in non-diabetic obese individuals, but further research is needed on long-term efficacy, safety, and clinical application.

Narra J, 2025

The rapid evolution of generative artificial intelligence (genAI) has ushered in a new era of dig... more The rapid evolution of generative artificial intelligence (genAI) has ushered in a new era of digital medical consultations, with patients turning to AI-driven tools for guidance. The emergence of Chinese-developed genAI models such as DeepSeek-R1 and Qwen-2.5 presented a challenge to the dominance of OpenAI's ChatGPT. The aim of this study was to benchmark the performance of Chinese genAI models against ChatGPT-4o and to assess disparities in performance across English and Arabic. Following the METRICS checklist for genAI evaluation, Qwen-2.5, DeepSeek-R1, and ChatGPT-4o were assessed for completeness, accuracy, and relevance using the CLEAR tool in common patient ophthalmology queries. In English, Qwen-2.5 demonstrated the highest overall performance (CLEAR score: 4.43±0.28), outperforming both DeepSeek-R1 (4.31±0.43) and ChatGPT-4o (4.14±0.41), with p=0.002. A similar hierarchy emerged in Arabic, with Qwen-2.5 again leading (4.40±0.29), followed by DeepSeek-R1 (4.20±0.49) and ChatGPT-4o (4.14±0.41), with p=0.007. Each tested genAI model exhibited near-identical performance across the two languages, with ChatGPT-4o demonstrating the most balanced linguistic capabilities (p=0.957), while Qwen-2.5 and DeepSeek-R1 showed a marginal superiority for English. An in-depth examination of genAI performance across key CLEAR components revealed that Qwen-2.5 consistently excelled in content completeness, factual accuracy, and relevance in both English and Arabic, setting a new benchmark for genAI in medical inquiries. Despite minor linguistic disparities, all three models exhibited robust multilingual capabilities, challenging the long-held assumption that genAI is inherently biased toward English. These findings highlight the evolving nature of AI-driven medical assistance, with Chinese genAI models being able to rival or even surpass ChatGPT-4o in ophthalmology-related queries.

Clinical Pharmacology: Advances and Applications Clinical Pharmacology: Advances and Applications Published by Taylor & Francis Publishes clinical trials, with a focus on early trials, including detailed pharmacological data, predicted applications, side effects, and safety and efficacy. Clinica..., 2025

Malaria remains a persistent challenge in global health, disproportionately affecting populations... more Malaria remains a persistent challenge in global health, disproportionately affecting populations in endemic regions (eg, sub-Saharan Africa). Despite decades of international collaborative efforts, malaria continues to claim hundreds of thousands of lives each year, with young children and pregnant women enduring the heaviest burden. This concise review aimed to provide an up-to-date assessment of malaria vaccines progress, challenges, and future directions. Methods: A PubMed/MEDLINE search (2015-2024) was conducted to identify studies on malaria vaccine development, implementation barriers, efficacy, and vaccination hesitancy. Clinical trials, reviews, and global health reports were included based on relevance to the review aims. No strict inclusion criteria were applied, and selection was guided by key review themes and policy relevance. Results: The introduction of pre-erythrocytic malaria vaccines (RTS,S/AS01 and R21/Matrix-M), represents an important milestone in malaria control efforts with promising results from the erythrocytic vaccine RH5.1/Matrix-M in recent clinical trials. However, the approval of these vaccines is accompanied by significant challenges such as the limited efficacy, the complexity of multi-dose regimens, and numerous barriers to widespread implementation in resource-limited settings. The review identified the complex challenges to broad malaria vaccination coverage, including logistical barriers, healthcare infrastructure effect, financial limitations, malaria vaccine hesitancy, among other obstacles in malaria-endemic regions. Promising developments in malaria vaccination, such as next-generation candidates (eg, mRNA-based vaccines), hold the potential to offer improved efficacy, longer-lasting protection, and greater scalability. There is a critical need to integrate malaria vaccination efforts with established malaria control interventions (eg, insecticide-treated bed nets, vector control strategies, and anti-malarial drugs). Conclusion: Achieving sustained control of malaria morbidity and mortality will require strong global collaboration, sufficient funding, and continuous efforts to address inequities in access and delivery of malaria control measures including the malaria vaccines.

Frontiers in Management Science, 2025

Decision-making in healthcare leadership often relies on subjective experiences rather than struc... more Decision-making in healthcare leadership often relies on subjective experiences rather than structured, evidence-based approaches, leading to inefficiency, missed opportunities for improvement and ineffective control over rising healthcare costs. This narrative review examined key facilitators that enhance the adoption of Evidence-Based Management (EBMgt) in healthcare, focusing on leadership effectiveness, operational efficiency, and strategic decision-making. A comprehensive literature search was conducted across PubMed, ABI/INFORM, Google Scholar, Emerald, ResearchGate, Harvard Business Review, ProQuest, and Health Business Elite, covering studies from 2015 to 2025. After applying inclusion criteria, 37 studies were analyzed to identify enablers supporting EBMgt implementation. The most common study designs were quantitative cross-sectional studies (n=11), systematic literature reviews (n=6), and qualitative studies with semi-structured interviews (n=5), with most studies conducted in the United States (n=9), Iran (n=6), and Australia (n=4). The findings showed that leadership commitment, organizational culture, access to high-quality evidence,

Preprints.org, 2025

Obesity remains a global health challenge, requiring long-term, sustainable treatment strategies.... more Obesity remains a global health challenge, requiring long-term, sustainable treatment strategies. Tirzepatide, a dual glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) receptor agonist is the latest clinically approved and commercially available pharmacological option for obesity management, necessitating further research in non-diabetic individuals. This narrative review synthesizes existing clinical evidence on the efficacy and safety of Tirzepatide in non-diabetic obese individuals. A comprehensive literature search was conducted using PubMed, Scopus, Web of Science, ClinicalTrials.gov, and Google Scholar databases to identify relevant clinical trials, meta-analyses, and studies assessing its weight-loss impact from 2022 onwards. Synthesized evidence indicates that Tirzepatide achieved up to 20.9% weight loss over 72 weeks (SURMOUNT-1), 18.4% after lifestyle intervention (SURMOUNT-3), 17.5% in Chinese adults (SURMOUNT-CN), and 25.3% with continued treatment over 88 weeks (SURMOUNT-4). Metaanalyses confirmed higher odds of ≥5%-20% weight loss versus Semaglutide and Liraglutide, significantly reducing body mass index (BMI), waist circumference, blood pressure, and Atherosclerotic Cardiovascular Disease (ASCVD) risk. Health-related quality of life (HRQoL) improved with greater weight loss, and gastrointestinal side effects (nausea, diarrhea, constipation) were common but mild to moderate, with <5% treatment discontinuation. Tirzepatide achieved significant weight loss, cardiometabolic benefits, and improved quality of life in non-diabetic obese individuals, but further research is needed on long-term efficacy, safety, and clinical application.

Journal of Pharmaceutical Policy and Practice, 2025

Background: Pharmacy workforces are central to healthcare systems, yet the profession faces chall... more Background: Pharmacy workforces are central to healthcare systems, yet the profession faces challenges in job satisfaction and retention due to evolving roles, workload pressures, and other issues. Understanding workforce stability is crucial for optimising pharmacy services. Objective: This systematic review aimed to identify and analyze the critical factors impacting pharmacy staff job satisfaction and retention, providing actionable insights to improve workforce stability and long-term engagement in the profession. Methods: A comprehensive search was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), covering broad academic databases including EMBASE, Web of Science, PubMed, International Pharmaceutical Abstracts, and the supplementary use of Google Scholar for studies published between 2019 and 2024. The quality of the included articles was evaluated, revealing a generally low to moderate risk of bias. Results: The review synthesised findings from 81 studies and extracted ten relevant themes. Countries including the United States, Saudi Arabia, Nigeria, Pakistan, and Southeast Asia countries contributed most frequently, highlighting regional research diversity. Key factors influencing job satisfaction included burnout, stress, and workload (24%); work conditions and roles (22%); professional development (14%); earnings and benefits (10%); and leadership support (9%). Conclusion: With a global perspective that travels across 36 countries in five continents, this study is the latest in-depth analysis of factors influencing job satisfaction in the pharmacy workforce. This review emphasises the need for policy reforms and further research on workplace conditions in different locations. It provides insights for policymakers and healthcare leaders to enhance the pharmacy workforce's strategic support and engagement initiatives.

Viruses, 2025

The extensive genetic diversity of HIV-1 represents a major challenge to public health interventi... more The extensive genetic diversity of HIV-1 represents a major challenge to public health interventions, treatment, and successful vaccine design. This challenge is particularly pronounced in the Middle East and North Africa (MENA) region, where limited data among other barriers preclude the accurate characterization of HIV-1 genetic diversity. The objective of this review was to analyze studies conducted in the MENA region to delineate possible barriers that would hinder the accurate depiction of HIV-1 genetic diversity in this region. A systematic search of PubMed/MEDLINE and Google Scholar was conducted for published records on HIV-1 genetic diversity in the English language up until 1 October 2024 across 18 MENA countries. The pre-defined themes of challenges/barriers included limited sampling, data gaps, resource and infrastructure constraints, HIV-1-specific factors, and socio-cultural barriers. A total of 38 records were included in the final review, comprising original articles (55.3%), reviews (21.1%), and sequence notes (10.5%). Libya (15.8%), Morocco (13.2%), Saudi Arabia, and MENA as a whole (10.5% for each) were the primary sources of the included records. Of the 23 records with original MENA HIV-1 sequences, the median number of sequences was 46 (range: 6–193). The identified barriers included the following: (1) low sampling density; (2) limited clinical data (21.7% with no data, 60.9% partial data, and 17.4% with full data); (3) reliance solely on population sequencing and insufficient use of advanced sequencing technologies; (4) lack of comprehensive recombination analysis; and (5) socio-cultural barriers, including stigma with subsequent under-reporting among at-risk groups. The barriers identified in this review can hinder the ability to map the genetic diversity of HIV-1 in the MENA. Poor characterization of HIV-1’s genetic diversity in the MENA would hinder efforts to optimize prevention strategies, monitor drug resistance, and develop MENA-specific treatment protocols. To overcome these challenges, investment in public health/research infrastructure, policy reforms to reduce stigma, and strengthened regional collaboration are recommended.

Babylonian Journal of Artificial Intelligence , 2025

Background: The emergence of Chinese generative AI (genAI) models, such as DeepSeek and Qwen, has... more Background: The emergence of Chinese generative AI (genAI) models, such as DeepSeek and Qwen, has introduced strong competition to Western genAI models. These advancements hold significant potential in healthcare education. However, benchmarking the performance of genAI models in specialized medical disciplines is crucial to assess their strengths and limitations. This study builds on prior research evaluating ChatGPT (GPT-3.5 and GPT-4), Bing, and Bard against human postgraduate students in Medical Laboratory Sciences, now incorporating DeepSeek and Qwen to assess their effectiveness in Clinical Chemistry Multiple-Choice Questions (MCQs). Methods: This study followed the METRICS framework for genAI-based healthcare evaluations, assessing six models using 60 Clinical Chemistry MCQs previously administered to 20 MSc students. The facility index and Bloom’s taxonomy classification were used to benchmark performance. GenAI models included DeepSeek-V3, Qwen 2.5-Max, ChatGPT-4, ChatGPT-3.5, Microsoft Bing, and Google Bard, evaluated in a controlled, non-interactive environment using standardized prompts. Results: The evaluated genAI models showed varying accuracy across Bloom’s taxonomy levels. DeepSeek-V3 (0.92) and ChatGPT-4 (1.00) outperformed humans (0.74) in the Remember category, while Qwen 2.5-Max (0.94) and ChatGPT-4 (0.94) surpassed human performance (0.61) in the Understand category. ChatGPT-4 (+23.25%, p < 0.001), DeepSeek-V3 (+18.25%, p = 0.001), and Qwen 2.5-Max (+18.25%, p = 0.001) significantly outperformed human students. Decision tree analysis identified cognitive category as the strongest predictor of genAI accuracy (p < 0.001), with Chinese AI models performing comparably to ChatGPT-4 in lower-order tasks but exhibiting lower accuracy in higher-order domains. Conclusions: The findings highlighted the growing capabilities of Chinese genAI models in healthcare education, proving that DeepSeek and Qwen can compete with, and in some areas outperform, Western genAI models. However, their relative weakness in higher-order reasoning raises concerns about their ability to fully replace human cognitive processes in clinical decision-making. As genAI becomes increasingly integrated into health education, concerns regarding academic integrity, genAI dependence, and the validity of MCQ-based assessments must be addressed. The study underscores the need for a re-evaluation of medical assessment strategies, ensuring that students develop critical thinking skills rather than relying on genAI for knowledge retrieval.

Jordan Journal of Applied Science - Natural Science Series, 2025

Background: Hospital pharmacies face challenges with insurance claim rejections, affecting revenu... more Background: Hospital pharmacies face challenges with insurance claim rejections, affecting revenue cycle management and efficiency. Lean Six Sigma methodologies provide structured frameworks for enhancing process efficiency. Objective: This study aimed to evaluate the impact of implementing Lean Six Sigma (LSS) principles on reducing insurance claim rejections at Mediclinic Welcare Hospital Pharmacy in Dubai, UAE. Methods: A quality improvement project framework was applied using the DMAIC (Define, Measure, Analyze, Improve, Control) methodology. Baseline data were collected from January to March 2024, with interventions implemented from April to August 2024. The validated key performance indicators (KPIs) included (1) A percentage improvement in staff competency in handling claims, (2) Reduction in total cost due to claim rejections, and (3) Improvement in the accuracy of pharmacy billing systems. KPIs were mapped, challenges identified, and targeted interventions implemented. Statistical analysis using the Mann-Whitney U test (P<0.05) and Sigma-level calculations quantified improvements and process efficiency enhancements. Results: Implementing LSS interventions significantly increased staff competency in handling claims, from 50% to 93% post-intervention (P <0.05). The sigma level also improved from 3.1 to 4.0. KPI (2) saw a 70% reduction in total costs associated with rejections. KPI (3) reflected a 111% improvement in billing accuracy, increasing from 45% to 95% (P <0.05). The Sigma level for billing processes improved from 3.1 to 4.1, signifying enhanced process stability and reduced Defects Per Million Opportunities. Conclusion: Applying Lean Six Sigma at Mediclinic Welcare Hospital Pharmacy improved process accuracy in reducing insurance claim rejections. This approach fostered operational excellence, a culture of continuous improvement, and long-term process efficiency, highlighting LSS as an effective strategy in healthcare.

Mesopotamian Journal of Big Data, 2025

The rise of superintelligent open-source generative AI (genAI) heralds both extraordinary potenti... more The rise of superintelligent open-source generative AI (genAI) heralds both extraordinary potential and unprecedented risk, exemplified by the rapid emergence of DeepSeek as a global AI innovator. This perspective article examines the dual-edged nature of open source genAI technologies, highlighting their capacity to democratize innovation while exposing critical vulnerabilities. By providing affordable, high-performing, and openly available models like DeepSeek-R1 and DeepSeek-V3, this Chinese AI company has disrupted the proprietary dominance of Western AI giants. These advancements are expected to empower researchers in resource-limited settings, foster global collaboration, and enable breakthroughs across numerous fields. Open-source AI, as illustrated by DeepSeek, has the potential to redefine the technological landscape by making advanced capabilities accessible to underrepresented communities and encouraging ethical and inclusive innovation. However, the openness that drives such progress is fraught with existential risks. Superintelligent open-source models, accessible to anyone with minimal resources, lower barriers for misuse by malicious actors. From automated cyberattacks and disinformation campaigns to destabilizing critical infrastructures, the potential for harm is vast and unprecedented. Beyond immediate security concerns, these technologies threaten economic stability by displacing entire workforces and exacerbating inequalities, and they undermine human agency by enabling manipulation on an individual and societal level. This perspective seeks to explore the profound benefits of open-source superintelligent AI while critically addressing the urgent need for ethical and regulatory frameworks to mitigate its risks. The story of DeepSeek underscores the fragile balance between innovation and destruction in an era where technological progress outpaces safeguards. Humanity's ability to harness the transformative power of open-source AI without succumbing to its destructive potential is not just a technological challenge-it is an existential imperative. This perspective argues for vigilance, responsibility, and global cooperation to ensure that the promise of open-source AI serves humanity rather than imperiling it.

Pharmacy Practice, 2025

Background: Hospital pharmacies encounter significant operational challenges that can affect serv... more Background: Hospital pharmacies encounter significant operational challenges that can affect service quality and client's satisfaction. Objective: This study focuses on the fundamental role of hospital pharmacy leadership and Lean management practices in transforming pharmacy operations at Mediclinic Parkview Hospital in Dubai, United Arab Emirates (UAE). Methods: Lean Leadership was vital in executing Lean Six Sigma (LSS) in the hospital pharmacy, promoting a patient-focused approach emphasizing quality, improvement, and staff engagement. The study employed the LSS DMAIC (Define, Measure, Analyze, Improve, Control) method to identify inefficiencies and improve overall performance, statistical analyses, and Sigma-level calculations. Results: Implementing Lean Six Sigma methodologies led to substantial enhancements in three Critical-to-Quality (CTQ) Key Performance Indicators (KPIs). Waiting times were reduced by 76%, patient satisfaction, as measured by Net Promoter Score (NPS), increased by 136%, and employee engagement scores improved by 28%. These advancements increased operational efficiency, improved patient retention, and decreased staff turnover. Additionally, the research utilized a validated questionnaire to examine the influence of DMAIC constructs on service quality using the SERVQUAL instrument across five dimensions: Tangibility, Empathy, Assurance Reliability, and Responsiveness. The results showed significant improvements across all models, with P-values below 0.001 confirming the robustness of the findings. Adjusted R-squared values ranging from 0.386 to 0.638 demonstrate that the Lean and Six Sigma methodologies applied in the study played a substantial role in enhancing service quality. Conclusion: This research emphasized the efficiency of the Lean Six Sigma DMAIC framework in enhancing hospital pharmacy operations, leading to substantial advancements in service quality across essential dimensions. The study focused on specialized training, Lean Leadership principles, and customized DMAIC components, supporting its practical implementation in healthcare settings.

Preprints.org, 2024

The extensive genetic diversity of HIV-1 represents a major challenge to public health interventi... more The extensive genetic diversity of HIV-1 represents a major challenge to public health interventions, treatment, and successful vaccine design. This challenge is particularly pronounced in the Middle East and North Africa (MENA) region, where limited data among other barriers preclude accurate characterization of HIV-1 genetic diversity. The objective of this review was to analyze studies conducted in the MENA region to delineate possible barriers that would hinder accurate depiction of HIV-1 genetic diversity in the MENA region. A systematic search of PubMed/MEDLINE and Google Scholar was conducted for published records on HIV-1 genetic diversity in English up till 1 October 2024 across 18 MENA countries. The pre-defined themes of challenges/barriers included limited sampling, data gaps, resource and infrastructure constraints, HIV-specific factors, and socio-cultural barriers. A total of 38 records were included in the final review, comprising original articles (55.3%), reviews (21.1%), and sequence notes (10.5%). Libya (15.8%), Morocco (13.2%), Saudi Arabia and MENA as a whole (10.5% for each) were the primary sources of the included records. Of the 23 records with original MENA HIV-1 sequences, the median number of sequences was 46 (range: 6–193). The identified barriers included (1) low sampling density; (2) limited clinical data (21.7% with no data, 60.9% partial data, and 17.4% with full data); (3) reliance solely on population sequencing and insufficient use of advanced sequencing technologies; (4) lack of comprehensive recombination analysis; (5) socio-cultural barriers including stigma with subsequent underreporting among at-risk groups. The barriers identified in this review can hinder the ability to map the genetic diversity of HIV-1 in the MENA. Poor characterization of HIV-1 genetic diversity in the MENA would hinder the efforts to optimize prevention strategies, monitor drug resistance, and develop MENA-specific treatment protocols. To overcome these challenges, investment in public health/research infrastructure, policy reforms to reduce stigma, and strengthened regional collaboration are recommended.

Cureus, 2024

Background: Drug shortages have become a significant challenge globally, affecting healthcare del... more Background: Drug shortages have become a significant challenge globally, affecting healthcare delivery and patient outcomes. This study aimed to assess drug shortages’ prevalence, causes, and impact at a tertiary care hospital in Dubai, the United Arab Emirates (UAE), providing actionable insights for future mitigation strategies. Methods: A retrospective descriptive study was conducted at Mediclinic Parkview (MPAR) Hospital, part of Mediclinic Middle East (MCME), UAE. Data were collected from January 2019 to December 2023. Reported drug shortages were analyzed to assess their frequency, duration, causes, and management, with a focus on identifying trends and underlying factors. Results: Drug shortages peaked at 995 in 2020, particularly during the COVID-19 pandemic. The median time spent managing shortages reached 19.5 days per shortage in Q3 2020. Oral forms accounted for the highest frequency (n = 2231), representing 61% of all shortages, followed by topical forms (n = 414, 11%) and injection forms (n = 386, 10%). Most affected drugs were in the infectious disease (n = 547, 15%), cardiovascular (n = 387, 11%), and respiratory (n = 330, 9%) categories. Drug shortages were driven by regulatory issues and manufacturing delays (39%), unknown reasons (29%), and supply chain disruptions exacerbated by the pandemic (10%). A monopoly environment worsened the situation and limited sourcing flexibility, with 66% of shortages linked to zero supply competitors. Tirzepatide (n = 20) and oseltamivir (n = 18) were the drugs most frequently reported to be unavailable over the 60-month study interval. Regarding management efforts, 80% of the time was spent gathering information and communicating with the different stakeholders. The hospital’s response included contacting prescribers for alternatives and increased reliance on internal procurement and inter-pharmacy coordination. These shortages caused significant operational strain, with increased workloads and higher costs. Conclusion: The study highlighted the need for adopting proactive measures, improved strategies, enhanced communication, and better preparedness to address future drug shortages. Key actions involved investing in technology, strengthening supplier relationships, and advocating for policy reforms to mitigate risks and ensure continuity of care.

Mesopotamian Journal of Artificial Intelligence in Healthcare, 2024

Background: The potential of generative artificial intelligence (genAI) tools, such as ChatGPT, i... more Background: The potential of generative artificial intelligence (genAI) tools, such as ChatGPT, is being increasingly explored in healthcare settings. However, the same tools also introduce significant cybersecurity risks that could compromise patient safety, data integrity, and institutional trust. This study aimed to examine real-world security breaches involving genAI and extrapolate their potential implications for healthcare settings. Methods: Using a systematic Google News search and a consensus-based approach among the authors, five high-profile genAI breaches were identified and analyzed. These cases included: (1) Data exposure in ChatGPT (OpenAI) due to an open-source library bug (March 2023); (2) Unauthorized data disclosure via Samsung’s (Samsung Group) use of ChatGPT (2023); (3) Logical vulnerabilities in Chevrolet (General Motors) AI-powered chatbot resulting in pricing errors (December 2023); (4) Prompt injection vulnerability in Vanna AI (Vanna AI, Inc.) which enabled remote code execution (2024); and (5) the deepfake technology used in a scam targeting the engineering firm Arup (Arup Group Limited), leading to fraudulent transactions (February 2024). Hypothetical healthcare scenarios were constructed based on the five cases, mapping their mechanisms to vulnerabilities in electronic health records (EHRs), clinical decision support systems (CDSS), and patient engagement platforms. Each case was analyzed using the Confidentiality, Integrity, and Availability (CIA) triad of information security to systematically identify vulnerabilities and propose actionable safeguards. Results: The analyzed cases of AI security breaches revealed significant risks to healthcare systems. Confidentiality violations included the potential exposure of sensitive patient records and billing information, extrapolated from incidents such as the ChatGPT data exposure and Samsung’s cases. These identified security breaches raised concerns about privacy violations, identity theft, and non-compliance with regulations such as Health Insurance Portability and Accountability Act (HIPAA). Integrity vulnerabilities were highlighted in Vanna AI's prompt injection flaw incident, with risks of altering patient records, compromising diagnostic algorithms, and misleading CDSS with erroneous recommendations. Similarly, logic errors identified in the Chevrolet case exposed potential risks of inaccurate billing, double-booked appointments, and flawed treatment plans within healthcare contexts. Availability disruptions, observed through system outages and operational suspensions following breaches like the ChatGPT and deepfake cases, can delay access to EHR systems or AI-driven CDSS. Such interruptions would directly impact patient care and create inefficiencies in administrative workflows. Conclusions: Generative AI presents a double-edged sword in healthcare, with transformative potential accompanied by substantial risks. Extrapolation of security breach cases in this study highlighted the urgent need for robust safeguards if genAI is implemented in healthcare settings. To address these vulnerabilities, healthcare institutions must implement strong security protocols, enforce strict data governance, and create AI-specific incident response plans. The balance between genAI-enabled innovation and protection of patient safety and data integrity trust requires proactive safety measures.

Preprint, 2024

Malaria remains a persistent challenge in global health, disproportionately affecting populations... more Malaria remains a persistent challenge in global health, disproportionately affecting populations in endemic regions (e.g., sub-Saharan Africa). Despite decades of international collaborative efforts, this parasitic disease continues to claim hundreds of thousands of lives each year, with young children and pregnant women enduring the heaviest burden of malaria. The introduction of pre-erythrocytic malaria vaccines (RTS,S/AS01 and R21/Matrix-M), represents an important milestone in malaria control efforts with promising results from the erythrocytic vaccine RH5.1/Matrix-M in recent clinical trials. However, the approval of these vaccines is accompanied by significant challenges such as the limited efficacy, the complexity of multi-dose regimens, and numerous barriers to widespread implementation in resource-limited settings. This concise review provides an overview of the historical development and current status of malaria vaccines, tracking their milestones from initial scientific breakthroughs to the deployment of first-generation vaccines. The review also examines the complex challenges to broad malaria vaccination coverage, including logistical barriers, healthcare infrastructure effect, financial limitations, malaria vaccine hesitancy, among other obstacles in malaria-endemic regions. Additionally, we explore promising developments in malaria vaccination, such as next-generation candidates (e.g., mRNA-based vaccines), that hold the potential to offer improved efficacy, longer-lasting protection, and greater scalability. Finally, we emphasize the critical need to integrate malaria vaccination efforts with established malaria control interventions (e.g., insecticide-treated bed nets, vector control strategies, and anti-malarial drugs). Based on this review, we concluded that achieving sustained control of malaria morbidity and mortality will require strong global collaboration, sufficient funding, and continuous efforts to address inequities in access and delivery of malaria control measures including the malaria vaccines.

Jordan Medical Journal, 2024

Background and Aims: Endocrine and metabolic disorders, including diabetes mellitus (DM), pose m... more Background and Aims: Endocrine and metabolic disorders, including diabetes
mellitus (DM), pose major global health challenges. Generative artificial
intelligence (genAI) models are increasingly used for patient self-help. This study
aimed to evaluate the performance of two genAI models, ChatGPT and Microsoft
Copilot, in addressing endocrine-related queries in English and Arabic.
Materials and Methods: This descriptive study adhered to the METRICS
checklist for genAI-based healthcare studies, comparing responses from
ChatGPT-4o and Microsoft Copilot to 20 endocrine-related queries in English and
Arabic (15 DM queries in addition to five endocrine queries). The responses were
evaluated using the CLEAR tool, which assessed completeness, accuracy, and
relevance/appropriateness. Three endocrinology experts independently evaluated
the genAI outputs.
Results: Per language and model, a total of 80 responses were assessed. Inter
rater reliability was high with Intraclass Correlation Coefficient=0.832.
ChatGPT-4o consistently outperformed Microsoft Copilot, earning 'Excellent'
ratings in English and ‘Very good’ in Arabic, while Microsoft Copilot achieved
‘Very good’ ratings in English and ‘Good’ to ‘Very good’ ratings in Arabic.
ChatGPT-4o surpassed Microsoft Copilot in completeness (4.38 vs. 3.36, p<.001,
Mann-Whitney U test (M-W)), accuracy (4.18 vs. 3.83, p=.014, M-W), and
relevance (4.44 vs. 3.82, p<.001, M-W). Performance varied significantly
between English and Arabic responses, with p<.001 for completeness, p=.001 for
accuracy, p=.012 for relevance, and p<.001 for the overall CLEAR score using
the M-W test. No statistically significant differences were found based on the
query topic.
Conclusions: ChatGPT-4o outperformed Microsoft Copilot in all CLEAR
components, but notable language-based disparities were evident. Addressing
these limitations is crucial to ensure equitable access to endocrine care for non
English-speaking patients.

Curēus, May 18, 2024

Obesity is a complex and chronic condition that presents a significant global health challenge, r... more Obesity is a complex and chronic condition that presents a significant global health challenge, resulting in a wide range of health problems, such as heart disease, stroke, and diabetes, therefore diminishing the overall well-being of numerous individuals. Conventional treatment options often prove inadequate, providing temporary relief and frequent weight regain. However, a promising medication called tirzepatide has emerged and been approved by the FDA as a groundbreaking solution for managing obesity. Through its unique mechanism of action as a glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) receptor agonist, as well as its impressive results in clinical trials, tirzepatide has the potential to completely transform the current approach to treating obesity. This editorial provides a quick snap for the clinical implications of tirzepatide, its mechanism of action, effectiveness, safety record, and the challenges it faces, such as insurance coverage and drug shortages. It emphasizes the importance of an integrated treatment approach and highlights the necessity for continuous research and policy backing to enhance accessibility and advance public health outcomes related to weight management.

Curēus, May 18, 2024

Antimicrobial resistance (AMR) poses a significant threat to global health, compromising the effe... more Antimicrobial resistance (AMR) poses a significant threat to global health, compromising the effectiveness of treatments and increasing medical risks. In this crisis, the importance of vaccines in reducing AMR is being increasingly acknowledged, although not thoroughly explored. This literature review asserts that vaccines can significantly lessen the occurrence of infections, thereby reducing the need for antibiotics and limiting the emergence of resistance. Vaccines play a crucial role in antimicrobial stewardship programs by preventing diseases that would otherwise necessitate the use of antibiotics. Expanding vaccine coverage supports responsible usage of antimicrobials and aligns with global health priorities to maintain effective medical interventions. This review emphasizes the need for equitable funding and policy support for vaccine initiatives comparable to new antibiotics and diagnostic techniques. Moreover, it calls for more detailed investigations into vaccines' economic and health benefits in managing AMR, highlighting their potential as cost-effective solutions to this urgent health challenge. Through a careful analysis of existing literature, this review highlights the fundamental role of vaccines in transforming the landscape of AMR, shifting the focus from a protective approach to a preventive health strategy.

Preprint, 2025

Diabetes, Metabolic Syndrome and Obesity, 2025

Obesities, 2025

Narra J, 2025

Frontiers in Management Science, 2025

Preprints.org, 2025

Journal of Pharmaceutical Policy and Practice, 2025

Viruses, 2025

Babylonian Journal of Artificial Intelligence , 2025

Jordan Journal of Applied Science - Natural Science Series, 2025

Mesopotamian Journal of Big Data, 2025

Pharmacy Practice, 2025

Preprints.org, 2024

The extensive genetic diversity of HIV-1 represents a major challenge to public health interventi... more The extensive genetic diversity of HIV-1 represents a major challenge to public health interventions, treatment, and successful vaccine design. This challenge is particularly pronounced in the Middle East and North Africa (MENA) region, where limited data among other barriers preclude accurate characterization of HIV-1 genetic diversity. The objective of this review was to analyze studies conducted in the MENA region to delineate possible barriers that would hinder accurate depiction of HIV-1 genetic diversity in the MENA region. A systematic search of PubMed/MEDLINE and Google Scholar was conducted for published records on HIV-1 genetic diversity in English up till 1 October 2024 across 18 MENA countries. The pre-defined themes of challenges/barriers included limited sampling, data gaps, resource and infrastructure constraints, HIV-specific factors, and socio-cultural barriers. A total of 38 records were included in the final review, comprising original articles (55.3%), reviews (21.1%), and sequence notes (10.5%). Libya (15.8%), Morocco (13.2%), Saudi Arabia and MENA as a whole (10.5% for each) were the primary sources of the included records. Of the 23 records with original MENA HIV-1 sequences, the median number of sequences was 46 (range: 6–193). The identified barriers included (1) low sampling density; (2) limited clinical data (21.7% with no data, 60.9% partial data, and 17.4% with full data); (3) reliance solely on population sequencing and insufficient use of advanced sequencing technologies; (4) lack of comprehensive recombination analysis; (5) socio-cultural barriers including stigma with subsequent underreporting among at-risk groups. The barriers identified in this review can hinder the ability to map the genetic diversity of HIV-1 in the MENA. Poor characterization of HIV-1 genetic diversity in the MENA would hinder the efforts to optimize prevention strategies, monitor drug resistance, and develop MENA-specific treatment protocols. To overcome these challenges, investment in public health/research infrastructure, policy reforms to reduce stigma, and strengthened regional collaboration are recommended.

Cureus, 2024

Mesopotamian Journal of Artificial Intelligence in Healthcare, 2024

Preprint, 2024

Malaria remains a persistent challenge in global health, disproportionately affecting populations... more Malaria remains a persistent challenge in global health, disproportionately affecting populations in endemic regions (e.g., sub-Saharan Africa). Despite decades of international collaborative efforts, this parasitic disease continues to claim hundreds of thousands of lives each year, with young children and pregnant women enduring the heaviest burden of malaria. The introduction of pre-erythrocytic malaria vaccines (RTS,S/AS01 and R21/Matrix-M), represents an important milestone in malaria control efforts with promising results from the erythrocytic vaccine RH5.1/Matrix-M in recent clinical trials. However, the approval of these vaccines is accompanied by significant challenges such as the limited efficacy, the complexity of multi-dose regimens, and numerous barriers to widespread implementation in resource-limited settings. This concise review provides an overview of the historical development and current status of malaria vaccines, tracking their milestones from initial scientific breakthroughs to the deployment of first-generation vaccines. The review also examines the complex challenges to broad malaria vaccination coverage, including logistical barriers, healthcare infrastructure effect, financial limitations, malaria vaccine hesitancy, among other obstacles in malaria-endemic regions. Additionally, we explore promising developments in malaria vaccination, such as next-generation candidates (e.g., mRNA-based vaccines), that hold the potential to offer improved efficacy, longer-lasting protection, and greater scalability. Finally, we emphasize the critical need to integrate malaria vaccination efforts with established malaria control interventions (e.g., insecticide-treated bed nets, vector control strategies, and anti-malarial drugs). Based on this review, we concluded that achieving sustained control of malaria morbidity and mortality will require strong global collaboration, sufficient funding, and continuous efforts to address inequities in access and delivery of malaria control measures including the malaria vaccines.

Jordan Medical Journal, 2024

Curēus, May 18, 2024

ProQuest ‎Dissertations & Theses Global, United States, 2024

The focus of this study was to examine how implementing Lean Six Sigma (LSS) ‎methodologies impac... more The focus of this study was to examine how implementing Lean Six Sigma (LSS) ‎methodologies impacted the Service Quality and effectiveness of the Pharmacy at Mediclinic ‎Parkview Hospital in Dubai, United Arab Emirates. The study employed the LSS DMAIC ‎‎(Define, Measure, Analyze, Improve, Control) method to identify inefficiencies and improve ‎overall performance statistical analyses and Sigma-level calculations. The implementation of ‎Lean Six Sigma methods led to an average increase of approximately 41.96% in performance ‎across six established Critical-to-Quality (CTQ) Key Performance Indicators (KPIs) within the ‎hospital pharmacy. The research utilized a validated questionnaire to examine how ‎demographic factors affect stakeholders' perceptions and challenges in implementing LSS ‎methodologies. Older adults faced more obstacles than their younger counterparts, with ‎noteable disparities observed across different fields of expertise education levels. This suggests ‎diverse experience with the implementation of LSS. Additionally, the study examined the ‎influence of DMAIC constructs on Service Quality using the SERVQUAL instrument across ‎various dimensions such as Tangibility, Reliability, Responsiveness, Assurance, and Empathy. ‎The findings revealed significant improvements across all models, indicated by p-values less ‎than 0.001, confirming the reliability of the results. Adjusted R-squared values ranging from ‎‎0.386 to 0.638 indicate that a substantial portion of service quality improvements can be ‎directly attributed to these methods. The “Improve” and “Control” constructs consistently ‎demonstrated positive effects, highlighting their critical role in enhancing service quality and ‎supporting the effective application of DMAIC in healthcare settings. This dissertation ‎enhances hospital pharmacy operations management through the Lean Six Sigma (LSS) ‎framework, emphasizing specialized training and customization of DMAIC elements to meet ‎healthcare service requirements.