Incremental Cost-Effectiveness of Aspiration Therapy vs Bariatric Surgery and No Treatment for Morbid Obesity
Bibliographic record
Abstract
INTRODUCTION: Despite its recent approval by the US Food and Drug Administration and Health Canada, aspiration therapy-one of the latest weight loss treatments-remains controversial. Critics have expressed concerns that the therapy could lead to bulimia and other binge eating disorders. Meanwhile, proponents argue that the therapy is less invasive, reversible, and cheaper than bariatric surgery. Cost-effectiveness of this therapy, however, is not yet established. METHODS: We developed a Markov model to estimate the incremental cost-effectiveness of aspiration therapy relative to 2 most common bariatric surgery procedures (gastric bypass and sleeve gastrectomy) and no treatment over a lifetime horizon. Costs were estimated from the health system's perspective using US data. Effectiveness was measured in terms of quality-adjusted life-years (QALYs). RESULTS: Despite being a cheaper procedure than bariatric surgery, aspiration therapy costs more than bariatric surgery in the long term because of its high maintenance costs (i.e., periodic replacement of device parts). It also yields lower QALYs than bariatric surgery because of its smaller weight loss effects. Thus, the therapy is dominated by bariatric surgery. In particular, compared with gastric bypass, it costs US$5,318 more and yields 1.31 fewer QALYs. However, aspiration therapy is cost-effective relative to no treatment with an incremental cost-effectiveness ratio of US$17,532 per QALY gained. DISCUSSION: Given its high lifetime costs and its modest weight loss effects, aspiration therapy is not cost-effective relative to bariatric surgery. However, it is a cost-effective treatment option for patients who lack access to bariatric surgery.
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 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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".