BACKGROUND: Average percent excess weight loss data is commonly discussed preoperatively to guide patient expectations following surgery. However, there is a wide range and variation in weight loss following vertical sleeve gastrectomy (SG). Unfortunately, most surgeons and even fewer patients have heard of using predictive models to help guide their decisions on procedure choice. We have developed a predictive model for SG to help patient choice prior to this major life-changing decision. OBJECTIVE: Predict weight loss results for SG patients at 1 year using preoperative data. SETTING: Private practice. METHODS: Three hundred and seventy-one SG patients met the criteria for our study. These patients underwent surgery between October 2008 and June 2016. Non-linear regressions were performed to interpolate individual patient weights at 1 year. Multivariate analysis was used to find factors that affected weight loss. A model was constructed to predict weight loss performance. RESULTS: Variables that affect weight loss were found to be preoperative body mass index (BMI), age, hypertension, and diabetes. Diabetes and hypertension together were found to significantly affect weight loss. CONCLUSION: Patient weight loss can be accurately predicted by simple preoperative factors. These findings should be used to help patients and surgeons decide if the SG is an appropriate surgery for each patient. Using this model, most patients can avoid failure by choosing an appropriate surgical approach for their personal circumstances.
BACKGROUND: Average percent excess weight loss data is commonly discussed preoperatively to guide patient expectations following surgery. However, there is a wide range and variation in weight loss following vertical sleeve gastrectomy (SG). Unfortunately, most surgeons and even fewer patients have heard of using predictive models to help guide their decisions on procedure choice. We have developed a predictive model for SG to help patient choice prior to this major life-changing decision. OBJECTIVE: Predict weight loss results for SG patients at 1 year using preoperative data. SETTING: Private practice. METHODS: Three hundred and seventy-one SG patients met the criteria for our study. These patients underwent surgery between October 2008 and June 2016. Non-linear regressions were performed to interpolate individual patient weights at 1 year. Multivariate analysis was used to find factors that affected weight loss. A model was constructed to predict weight loss performance. RESULTS: Variables that affect weight loss were found to be preoperative body mass index (BMI), age, hypertension, and diabetes. Diabetes and hypertension together were found to significantly affect weight loss. CONCLUSION: Patient weight loss can be accurately predicted by simple preoperative factors. These findings should be used to help patients and surgeons decide if the SG is an appropriate surgery for each patient. Using this model, most patients can avoid failure by choosing an appropriate surgical approach for their personal circumstances.
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