A systematic review on neuromodulation therapies for reducing body weight in patients with obesity
Bibliographic record
Abstract
The global prevalence of obesity increases yearly along with a rising demand for efficacious, safe, and accessible treatments. Neuromodulation interventions (i.e., deep brain stimulation [DBS], transcranial magnetic stimulation [TMS], transcranial direct current stimulation [tDCS], percutaneous neurostimulation [PENS], vagus nerve stimulation [VNS], and gastric electrical stimulation [GES]) have been proposed as novel therapies. This systematic review sought to examine the safety and efficacy of neuromodulation therapies in reducing body weight in patients with obesity. Using PRISMA guidelines, we performed a systematic review for studies on neuromodulation for the treatment of obesity, resulting in 60 trials included (7 DBS, 5 TMS, 7 tDCS, 17 PENS and VNS, and 24 GES; a total of 3,042 participants). While promising results have been reported in open label studies, double-blinded randomized clinical trials often did not reach their primary endpoints, with no technique inducing a striking reduction in body weight. Bearing in mind the complexity and multifactorial nature of obesity, it is possible that a single treatment may not be enough for patients to lose or maintain the weight lost at long term.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.005 | 0.006 |
| 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) | 0.007 | 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".