Observational studyObesity surgery2015
abiliti Closed-Loop Gastric Electrical Stimulation System for Treatment of Obesity: Clinical Results with a 27-Month Follow-Up.
Observational study in Obesity surgery, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.
- Systematic review on gastric electrical stimulation in obesity treatment.Expert review of medical devices · 2019Pooled it
- Implanted Closed-Loop Gastric Electrical Stimulation (CLGES) System with Sensor-Based Feedback Safely Limits Weight Regain at 24 Months.Obesity surgery · 2018Trial
- Closed-loop gastric electrical stimulation versus laparoscopic adjustable gastric band for the treatment of obesity: a randomized 12-month multicenter study.International journal of obesity (2005) · 2016Trial
- Anatomy and function of efferent and afferent vagal innervation of the stomach.Autonomic neuroscience : basic & clinical · 2026Review
- Neuromodulation using Bioelectronics-enabled therapies to combat insulin resistance and its comorbidities.Journal of diabetes and metabolic disorders · 2026Review
- Advances and future directions in endoscopic bariatric therapies.World journal of gastrointestinal endoscopy · 2025Review
- Neurobiological and Microbiota Alterations After Bariatric Surgery: Implications for Hunger, Appetite, Taste, and Long-Term Metabolic Health.Brain sciences · 2025Review
- Current state of the art and future directions for implantable sensors in medical technology: Clinical needs and engineering challenges.APL bioengineering · 2023Review
- Electroceuticals for Neurogastroenterology and Motility Disorders.Current gastroenterology reports · 2023Review
- Decoding Vagus-Nerve Activity with Carbon Nanotube Sensors in Freely Moving Rodents.Biosensors · 2022Article
- Powering Implantable and Ingestible Electronics.Advanced functional materials · 2021Article
- Miniaturized wireless gastric pacing via inductive power transfer with non-invasive monitoring using cutaneous Electrogastrography.Bioelectronic medicine · 2021Article
- Intestinal Electrical Stimulation Alters Hypothalamic Expression of Oxytocin and Orexin and Ameliorates Diet-Induced Obesity in Rats.Obesity surgery · 2021Article
- Energy-Efficient Integrated Circuit Solutions Toward Miniaturized Closed-Loop Neural Interface Systems.Frontiers in neuroscience · 2021Review
- The GAMMA concept (gastrointestinal activity manipulation to modulate appetite) preliminary proofs of the concept of local vibrational gastric mechanical stimulation.Surgical endoscopy · 2020Article
- Clinical practice guidelines of the European Association for Endoscopic Surgery (EAES) on bariatric surgery: update 2020 endorsed by IFSO-EC, EASO and ESPCOP.Surgical endoscopy · 2020Article
- The Role of Minimally Invasive and Endoscopic Technologies in Morbid Obesity Treatment: Review and Critical Appraisal of the Current Clinical Practice.Obesity surgery · 2020Review
- Obesity and Eating Disturbance: the Role of TFEQ Restraint and Disinhibition.Current obesity reports · 2019Review
- Vagal mechanisms as neuromodulatory targets for the treatment of metabolic disease.Annals of the New York Academy of Sciences · 2019Review
- Bioelectric neuromodulation for gastrointestinal disorders: effectiveness and mechanisms.Nature reviews. Gastroenterology & hepatology · 2019Review
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe aim of the study was to evaluate the safety and effectiveness of a novel closed-loop gastric electric stimulation device (abiliti system) featuring a transgastric sensor to detect food intake and an accelerometer to record physical activity to induce and maintain lifestyle changes to treat obesity.
methodsIn a prospective, multi-center study, 34 obese subjects (BMI of 42.1 ± 5.3 kg/m(2)) who passed an eligibility evaluation were implanted with the abiliti system. Safety evaluation included an endoscopic exam to assess the intragastric electrode healing. Efficacy evaluation at 1 year of therapy included weight loss, improvements in eating, and exercise behavior and quality of life.
resultsThe transgastric implant controlled by endoscopy was stable for all participants. At 12 months (12 M) the mean excess weight loss (EWL) was 28.7% (95%CI, 34.5 to 22.5%), and mean reduction in BMI was 4.8 ± 3.2 kg/m(2). At 27 months (27 M), the EWL was 27.5% (95% CI, 21.3% to 33.7%). Eating behavior, evaluated by the "Three Factor Eating Questionnaire", showed a significant increase in the cognition factor and decrease in the disinhibition and hunger factors at 12 M in comparison to baseline (p < 0.001). Participants significantly increased their weekly physical activity (p < 0.001). Quality of life was improved in 55.2% of the patients.
conclusionsGastric electrical stimulation with abiliti system in obese participants is well tolerated and leads to significant 12 M weight loss, which was stable to 27 M. We suggest that weight loss is achieved due to the assessed alteration of eating behavior in particular the reduction in disinhibition and hunger, and the measured increase in physical activity.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.