Clinical studies on anti-obesity medications in Arab countries
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Bibliographic record
Abstract
OBJECTIVES: To identify and summarize studies carried out in Arab countries on anti-obesity medications (AOMs), with a focus on the types of medications investigated, study designs, and the efficacy/effectiveness and safety metrics reported. METHODS: We carried out a comprehensive scoping review of primary studies examining the use of AOMs in adult Arab populations. Five databases (Medline, Embase, Cochrane Library, Index Medicus for the Eastern Mediterranean Region, and e-Marefa) were searched for English-language publications up to October 2024. Data extraction was carried out on study characteristics, participant demographics, interventions, and outcomes related to weight reduction, metabolic parameters, and side effects. The risk of bias (RoB) was assessed using the Newcastle-Ottawa scale for non-randomized studies and a modified RoB tool for randomized controlled trials. RESULTS: A total of 59 clinical studies published between 2014-2024 were included. The majority (89.8%) were observational in design. Most studies were carried out in Saudi Arabia (40.7%) and the United Arab Emirates (20.3%). Glucagon-like peptide-1 receptor agonists were investigated in 72.9% of the studies, with liraglutide being the most frequently studied agent (54.2%). The most commonly reported efficacy outcomes included changes in total body weight (45.8%), body mass index (39.0%), and the proportion of weight loss (28.8%). Gastrointestinal side effects were reported in 32.2% of patients across studies. CONCLUSION: Despite the growing body of research on AOMs in Arab countries, most studies remain observational and focus primarily on earlier-generation agents. There is a need for randomized controlled trials to evaluate the efficacy and safety of newer AOMs, such as semaglutide and tirzepatide, within Arab populations to inform culturally and genetically tailored obesity management strategies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it