Sustained weight loss after duodenal-jejunal bypass liner treatment in patients with body mass index below, but not above 35 kg/m 2 : A retrospective cohort study.
Patchaya Boonchaya-AnantMarco BueterChristoph GublerPhilipp A GerberPublished in: Clinical obesity (2022)
Previous data from short term studies have shown an efficacy of the duodenal-jejunal bypass liner (DJBL) for weight loss. However, less data is available regarding weight change after device removal and possible predictors for weight loss. This is a retrospective chart review of all patients who had DJBL inserted at the University Hospital Zurich between December 2012 and June 2015. A total of 27 patients had DJBL insertion. The median BMI at baseline was 38.5 (34.0-42.2) kg/m 2 . In the 24 patients with DJBL treatment >3 months (failed implantation or early removal due to side effects in 3 patients), the mean duration of implantation was 42.9 ± 13.1 weeks. During the treatment, the mean total body weight loss (%TBWL) was 15.0 ± 8.3%. Fifteen patients had long-term follow-up data available (mean duration of follow-up 4.0 ± 0.9 years). The mean weight change was 12.7 ± 12.8 kg, corresponding with a mean % weight regain of 13.3 ± 13.3%. Five patients (33.3%) subsequently underwent bariatric surgery. In patients with class I obesity (BMI <35 kg/m 2 at baseline), 4 out of 6 (66.7%) had a stable weight or only a weight regain <7%. In contrast, no patient with BMI >35 kg/m 2 at baseline was able to keep weight regain below 7%. DJBL is an effective treatment for obesity, but substantial weight regain occurs during long-term follow up after the device removal, in particular in patients with BMI > 35 kg/m 2 .
Keyphrases
- weight loss
- body mass index
- bariatric surgery
- weight gain
- end stage renal disease
- gastric bypass
- roux en y gastric bypass
- chronic kidney disease
- ejection fraction
- newly diagnosed
- physical activity
- prognostic factors
- peritoneal dialysis
- obese patients
- electronic health record
- metabolic syndrome
- insulin resistance
- machine learning
- type diabetes
- glycemic control
- big data
- magnetic resonance
- computed tomography
- replacement therapy
- combination therapy
- adipose tissue
- artificial intelligence