Weight Loss Prediction after Metabolic and Bariatric Surgery

Metabolic/bariatric surgery is currently the most effective measure to treat morbid obesity and obesity-related comorbidities such as type 2 diabetes. It has proven effective not only in terms of short-term weight loss, but also in maintaining the lower body weight for several decades. Such weight loss improves patient quality of life and extends life expectancy. It is crucial for patients to understand the likely results of a given bariatric procedure so that they can make an informed decision about whether to undergo surgery. The amount of weight loss after metabolic/bariatric surgery is usually the most important outcome of interest to patients considering surgical treatment. It is also the most common primary endpoint for healthcare providers. Patients undergoing surgery want tangible and realistic expectations about how much weight they could lose after surgery, and healthcare professionals need to determine at each follow-up visit after surgery whether patients are on track to reach their weight loss target so they can provide timely intervention to patients with insufficient weight loss or weight re-gain. Weight loss after metabolic/bariatric surgery is influenced by many clinical variables, including initial body mass index, age, gender, ethnicity, and type of surgery. A well-validated chronological weight loss prediction model would enable patient-centered counseling and goal setting. This review summarizes and compares sev-eral publicly available prediction models.

Automated summary

Metabolic/bariatric surgery is the most effective method for treating morbid obesity and its related comorbidities. It not only results in short-term weight loss, but also helps maintain a lower body weight for decades, improving patients' quality of life and life expectancy. Patients need to understand the likely outcomes of the surgery, especially the amount of weight loss, in order to make informed decisions. Healthcare professionals also need reliable prediction models to assess patients' weight loss progress.