Performance of a predictive weight loss model in terms of rapid detection of inadequate weight loss after Roux-en-Y gastric bypass

Abstract

Background: Predictive weight loss models can help patients meet their expectations after bariatric surgery and assist physicians in responding to deviations from the predicted weight. A model published by Seyssel et al. appears to accurately predict postoperative body mass index.

Objectives: We aimed to demonstrate this model's performance in terms of rapid detection of insufficient weight loss (surgical nonresponse).

Setting: Cantonal Hospital, Switzerland.

Methods: We retrospectively analyzed weight and body mass index deviations at 2 years postoperatively, based on values predicted by the model of Seyssel et al. The primary outcome was the timing of detection of surgical nonresponse. The secondary outcome was how patients' weight loss expectations influenced their real weight loss.

Results: Between 2016 and 2019, 190 patients underwent Roux-en-Y gastric bypass. Of these patients, 36 were lost to follow-up and 154 were included in this study. At 24 months, 16 patients had surgical nonresponse, defined as a real weight of +1 standard deviation higher than that predicted. Among these patients, 44% had a weight of ≥+1 standard deviation higher than predicted at 3 months, and 63% at 12 months. The positive and negative predictive values at 12 months were 59% and 95%, respectively. Patients with a lower hypothetically wanted weight (38.5%) exhibited greater weight loss (P < .05).

Conclusions: The predictive weight loss model of Seyssel et al. enables rapid detection of surgical nonresponse, allowing physicians to react as early as 3 months postsurgery. Patients' overestimation of postoperative weight loss was positively correlated with the actual weight loss achieved.

Keywords: Bariatric surgery; Obesity; Predictive weight loss model; Roux-en-Y gastric bypass; Weight loss.