Cost-Utility Analysis of Metabolic Bariatric Surgery for Individuals with Obesity in Saudi Arabia
Bibliographic record
Abstract
Background: Metabolic bariatric surgery (MBS) is an effective and relatively safe intervention for managing obesity. This study aimed to evaluate the cost-utility of MBS compared with the standard treatment-lifestyle modification plus liraglutide-in the Kingdom of Saudi Arabia (KSA). Methods: A Markov model was developed to estimate the lifetime costs and outcomes of MBS. Costs and outcomes were discounted at an annual rate of 3%. The analysis was conducted from societal and healthcare system perspectives, using a willingness-to-pay (WTP) threshold of one to three times the gross domestic product (GDP) per capita per quality-adjusted life years (QALY) gained. Direct medical and nonmedical costs were obtained from hospital records and patient surveys, respectively. Transitional probabilities and utility values were obtained from published literature and primary data collection in the KSA. One-way and probabilistic sensitivity analyses were performed to assess parameter uncertainty. Results: Over a lifetime horizon, MBS yielded 0.38 incremental QALY and US$ 11,975 (Saudi Riyal [SAR] 44,905; purchasing power parity [PPP] 23,911) incremental costs, leading to an incremental cost-effectiveness ratio (ICER) of US$ 31,909 (SAR 119,660; PPP 63,717) per QALY gained from a societal perspective and US$ 36,353 (SAR 136,324); PPP 72,590) from a healthcare system perspective. The model was most sensitive to the discount rates of costs and outcomes and the direct medical costs associated with MBS. At a WTP threshold of one GDP per capita (US$ 30,436; SAR 114,135; PPP 60,775), the standard treatment had a 63% probability of being cost-effective. However, at a threshold of approximately 1.8 GDP per capita (US$ 56,000; SAR 210,000; PPP 111,821), MBS was cost-effective in 100% of the iterations. Conclusion: without comorbidities across the country.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".