Background: Antimicrobial resistance (AMR) is one of the key challenges in healthcare, and effective antimicrobial stewardship programs (ASPs) can play a vital role to control it. The aim of the current study was to assess the impact of the Lean Six Sigma (LSS) methodology on a hospital-wide ASP. Methods: This retrospective descriptive study was conducted at Mediclinic Welcare Hospital (MWEL), Dubai, the United Arab Emirates (UAE). The critical-to-quality (CTQs) data were collected pre/post interventions, including leadership support, guideline implementation, and audits. The study focused on inpatients who received antimicrobials from January 2021 to July 2022, analyzing ASP metrics (utilization, processes, and outcome measures). Results: The ASP improvements led to an 81.7% decrease in hospital’s parenteral antimicrobial expenses from January 2021 to July 2022, and a 54.2% reduction in antimicrobial usage while maintaining clinical outcomes. The average defined daily dose per 100 bed-days drop of 12.5% further demonstrated this positive trend. The intervention was not accompanied by higher nosocomial infection rates, longer stays, or mortality. Additionally, intervention led to better compliance with surgical prophylaxis bundles, antimicrobial protocols, hand hygiene and other ASP CTQ metrics. Conclusions and recommendations: This study emphasized the significance of implementing the LSS methodology in addressing process variations, enhancing ASP outcomes, and reducing antimicrobial use. These findings can inform health policymakers to improve future ASP outcomes. Additionally, sustainability through continuous monitoring and ongoing education initiatives should be considered to ensure the long-term success of these improvements.

Background: Data on cerebral pressure‐flow autoregulation in the youngest children are scarce. We studied the correlation between mean arterial pressure and cerebral tissue oxygen saturation (rSO₂) by near‐infrared spectroscopy (NIRS) in patients undergoing nose, lip, and palate surgery.Aim: We tested the hypothesis that cerebral pressure‐flow autoregulation is impaired in children less than 1 year undergoing surgery and general anesthesia with sevoflurane under controlled mechanical ventilation.Method: After approval from the Ethical board, 15 children aged <1 year were included. Before anesthesia induction, a NIRS sensor (INVOS^TM, Medtronic, Minneapolis, USA) was placed over the cerebral frontal lobe. Frontal rSO₂, a surrogate for cerebral perfusion, mean arterial pressure, end‐tidal CO₂‐ and sevoflurane concentration, and arterial oxygen saturation were sampled every minute after the induction. A repeated measures correlation analysis was performed to study correlation between mean arterial pressure and cerebral rSO₂, and the repeated measures correlation coefficient (r_rm) was calculated.Results: Fifteen patients, aged 7.7 ± 1.9 months, were studied. rSO₂ showed a positive correlation with mean arterial pressure ([95% CI: 9.0‐12.1], P < 0.001) with a moderate to large effect size (r_rm = 0.462), indicating an impaired cerebral pressure‐flow autoregulation. The slopes of the rSO₂‐mean arterial pressure correlations were steeper in patients who were hypotensive (mean arterial pressure <50 mm Hg) compared to patients having a mean arterial pressure ≥50 mm Hg, indicating that at lower mean arterial pressure, the cerebral pressure dependence of cerebral oxygenation is even more pronounced.Conclusion: During sevoflurane anesthesia in the youngest pediatric patients, cerebral perfusion is pressure‐dependent, suggesting that the efficiency of the cerebral blood flow autoregulation is limited.

Obesity represents a global health challenge, with a critical and urgent need for long-term, sustainable management strategies. Tirzepatide is a novel dual glucose-dependent 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, meta-analyses, 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.

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). Meta-analyses 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.

Generative artificial intelligence (genAI) models are rapidly being adopted for health information delivery. Nevertheless, systematic cross-linguistic evaluations of their clinical reliability—particularly in high-burden conditions such as asthma, allergy, and respiratory tract infections (RTIs)—remain limited. The aim of this study was to compare the English and Arabic performance of ChatGPT‑4o, Gemini, and DeepSeek in responding to common asthma, allergy, and RTI queries using a validated clinical assessment framework. A bilingual evaluation was conducted using 30 frequently asked questions (FAQs) related to asthma, allergy, and RTIs. Each question was submitted in English and Arabic to ChatGPT‑4o, Gemini, and DeepSeek. Responses were evaluated independently by three bilingual clinical experts using the CLEAR framework for Completeness, Accuracy, and Relevance of the generated content. Inter-rater reliability was assessed using intraclass correlation coefficients (ICCs). Language and model comparisons were analyzed using non-parametric Kruskal-Wallis and Mann-Whitney U tests. The study followed the METRICS reporting guideline for genAI in healthcare. ChatGPT‑4o consistently outperformed Gemini and DeepSeek across all CLEAR dimensions and the two languages. In English, the mean CLEAR scores were: ChatGPT‑4o: 3.90, Gemini: 2.50, DeepSeek: 2.09. In Arabic, ChatGPT‑4o again scored highest (3.63), followed by Gemini (2.38) and DeepSeek (1.84). All inter-model differences were statistically significant (p < 0.001). Inter-rater reliability was excellent across dimensions: ICC for completeness = 0.858, accuracy = 0.917, relevance = 0.950 (all p < 0.001), confirming strong consistency and validity in scoring. Within each genAI model, English outputs significantly outperformed Arabic in completeness, accuracy, relevance, and the overall CLEAR score. Domain-wise, asthma queries achieved the highest performance across models and languages, while allergy queries showed the lowest accuracy. ChatGPT‑4o demonstrated superior bilingual performance, while Gemini and DeepSeek exhibited significant limitations, particularly in Arabic. These findings highlight persistent language-based disparities in genAI health outputs. Rigorous cross-linguistic evaluation and domain-specific fine-tuning are essential to ensure safe and equitable deployment of genAI tools in global health communication.

The molecular epidemiology and antiretroviral (ARV) drug resistance of human immunodeficiency virus type 1 (HIV-1) remain incompletely outlined in the Middle East and North Africa (MENA). The aim of this retrospective molecular epidemiology study was to analyze MENA HIV-1 sequences for phylogenetic clustering and to delineate surveillance drug-resistance mutations (SDRMs) for nucleoside reverse-transcriptase inhibitors (NRTIs), non-nucleoside reverse-transcriptase inhibitors (NNRTIs), and protease inhibitors (PIs) across various periods, locations, and subtypes/circulating recombinant forms (CRFs). Viral sequences were retrieved from the Los Alamos HIV Sequence Database as of 15 April 2026. Analyses were done using multiple sub-gene regions (two env regions (n = 224 and n = 60) and PR (n = 2413) and RT (n = 2103) of the pol gene). Phylogeny construction was conducted using maximum-likelihood estimation, while ARV drug resistance analysis was conducted using the Stanford HIVdb algorithm. The HIV-1 MENA sequences showed a remarkable genetic diversity, with co-circulation of multiple subtypes/CRFs, including subtype B in the Maghreb, Levant, and Egypt sub-regions, subtypes A1, G, CRF01_AE, and CRF02_AG in the Gulf Cooperation Council (GCC) and Yemen sub-region, and subtypes C and D in the Horn of Africa and Sudan sub-region. The percentage of MENA HIV-1 sequences in clusters was 10.3% for env1, 8.3% for env2, 22.0% for PR and 37.2% for RT. Phylogenetic reconstruction hinted at a structured epidemic dominated by small transmission units, with most clusters comprising dyads (n = 260) or networks (n = 142) and a limited number of large clusters (n = 8) that were largely confined within national boundaries, with only occasional cross-border linkages (n = 8). Overall SDRM prevalence was 3.2% in the PR region and 14.9% in the RT region, with a higher percentage of NNRTI-associated mutations (10.0%) than NRTI-associated mutations (9.1%) and dual-class resistance observed in 4.1% of sequences. Phylogenetic clustering was not associated with the probability of harboring SDRMs; however, negative binomial models showed that non-clustered sequences had a greater burden of NRTI-associated mutations, whereas no such association was observed for NNRTI- or PI-associated mutations. The findings showed predominantly localized and fragmented MENA HIV-1 transmission dynamics. Heterogeneous ARV drug resistance dynamics indicated that resistance emergence might be shaped by broader epidemiologic and treatment-related factors rather than ongoing clustered transmission. There is a need for coordinated molecular surveillance and optimized ART strategies across the MENA countries.