Patient profiling for success after weight loss surgery (GO Bypass study): An interdisciplinary study protocol

Bodil Just Christensen, Julie Berg Schmidt, Mette Søndergaard Nielsen, Louise Tækker, Lotte Holm, Susanne Lunn, Wender L P Bredie, Christian Ritz, Jens Juul Holst, Torben Hansen, Anja Hilbert, Carel W le Roux, Oliver J Hulme, Hartwig Siebner, Tobias Morville, Lars Naver, Andrea Karen Floyd, Anders Sjödin

15 Citationer (Scopus)


Despite substantial research efforts, the mechanisms proposed to explain weight loss after gastric bypass (RYGB) and sleeve gastrectomy (SL) do not explain the large individual variation seen after these treatments. A complex set of factors are involved in the onset and development of obesity and these may also be relevant for the understanding of why success with treatments vary considerably between individuals. This calls for explanatory models that take into account not only biological determinants but also behavioral, affective and contextual factors. In this prospective study, we recruited 47 women and 8 men, aged 25-56 years old, with a BMI of 45.8 ± 7.1 kg/m2 from the waiting list for RYGB and SL at Køge hospital, Denmark. Pre-surgery and 1.5, 6 and 18 months after surgery we assessed various endpoints spanning multiple domains. Endpoints were selected on basis of previous studies and include: physiological measures: anthropometrics, vital signs, biochemical measures and appetite hormones, genetics, gut microbiota, appetite sensation, food and taste preferences, neural sensitivity, sensory perception and movement behaviors; psychological measures: general psychiatric symptom-load, depression, eating disorders, ADHD, personality disorder, impulsivity, emotion regulation, attachment pattern, general self-efficacy, alexithymia, internalization of weight bias, addiction, quality of life and trauma; and sociological and anthropological measures: sociodemographic measures, eating behavior, weight control practices and psycho-social factors.Joining these many endpoints and methodologies from different scientific disciplines and creating a multi-dimensional predictive model has not previously been attempted. Data on the primary endpoint are expected to be published in 2018.

Trial registration: Clinicaltrials. gov ID NCT02070081.

TidsskriftContemporary Clinical Trials Communications
Sider (fra-til)121-130
StatusUdgivet - 1 jun. 2018


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