Cost-effectiveness of procedure-less intragastric balloon therapy as substitute or complement to bariatric surgery
Bibliographic record
Abstract
BACKGROUND: Procedure-less intragastric balloon (PIGB) eliminates costs and risks of endoscopic placement/removal and involves lower risk of serious complications compared with bariatric surgery, albeit with lower weight loss. Given the vast unmet need for obesity treatment, an important question is whether PIGB treatment is cost-effective-either stand-alone or as a bridge to bariatric surgery. METHODS: We developed a microsimulation model to compare the costs and effectiveness of six treatment strategies: PIGB, gastric bypass or sleeve gastrectomy as stand-alone treatments, PIGB as a bridge to gastric bypass or sleeve gastrectomy, and no treatment. RESULTS: PIGB as a bridge to bariatric surgery is less costly and more effective than bariatric surgery alone as it helps to achieve a lower post-operative BMI. Of the six strategies, PIGB as a bridge to sleeve gastrectomy is the most cost-effective with an ICER of $3,781 per QALY gained. While PIGB alone is not cost-effective compared with bariatric surgery, it is cost-effective compared with no treatment with an ICER of $21,711 per QALY. CONCLUSIONS: PIGB can yield cost savings and improve health outcomes if used as a bridge to bariatric surgery and is cost-effective as a stand-alone treatment for patients lacking access or unwilling to undergo surgery.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".