Cost-effectiveness of bariatric surgery versus community weight management to treat obesity-related idiopathic intracranial hypertension: evidence from a single-payer healthcare system
Bibliographic record
Abstract
BACKGROUND: Idiopathic intracranial hypertension (IIH) is associated with significant morbidity, predominantly affecting women of childbearing age living with obesity. Weight loss has demonstrated successful disease-modifying effects; however, the long-term cost-effectiveness of weight loss interventions for the treatment of IIH has not yet been established. OBJECTIVES: To estimate the cost-effectiveness of weight-loss treatments for IIH. SETTING: Single-payer healthcare system (National Health Service, England). METHODS: A Markov model was developed comparing bariatric surgery with a community weight management intervention over 5-, 10-, and 20-year time horizons. Transition probabilities, utilities, and resource use were informed by the IIH Weight Trial (IIH:WT), alongside the published literature. A probabilistic sensitivity analysis was conducted to characterize uncertainty within the model. RESULTS: In the base case analysis, over a 20-year time horizon, bariatric surgery was "dominant," led to cost savings of £49,500, and generated an additional 1.16 quality-adjusted life years in comparison to the community weight management intervention. The probabilistic sensitivity analysis indicated a probability of 98% that bariatric surgery is the dominant option in terms of cost-effectiveness. CONCLUSION: This economic modeling study has shown that when compared to community weight management, bariatric surgery is a highly cost-effective treatment option for IIH in women living with obesity. The model shows that surgery leads to long-term cost savings and health benefits, but that these do not occur until after 5 years post surgery, and then gradually increase over time.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".