The Use of Predictive Markers for the Development of a Model to Predict Lowest Quartile Weight Loss following Roux-en-Y Gastric Bypass. - Cottam, Samuel; Cottam, Daniel; Cottam, Austin; Surve, Amit; Zaveri, Hinali; Richards, Christina (Journal of Obesity Management, 2016)
Introduction: The Roux-en-Y Gastric Bypass (RYGB) has been one of the most popular surgeries in the USA for years. While many models have been made to investigate the factors that affect weight loss, these factors are still highly debated. Objective: To create a model that predict performance of RYGB patients. Methods: 110 out of 344 patients who received a RYGB at a single institution between Jan 2010 and April 2014 were included in this study. Data was collected retrospectively. Patients were included if they had greater than 1 year follow up with at least three follow up points and could be modeled with r2>0.95. All patients were one year beyond surgery, while 40 were completely lost to follow up, 104 at 1 month, 138 at 3 months, 188 at 6 months, and 225 at one year. 9 patients were not included because they did not meet the criteria of the study. Patients were divided into quartiles based on percentage excess weight loss (%EWL) at one year. Multivariate analysis was performed to determine the significant factors that influence patients being in the first quartile of weight loss (17-60% %EWL). Results: Only males with a Body Mass Index (BMI) above 44 and females with a BMI above 64 were found to be predictive of patients being in the first quartile. Our model has Positive and Negative predictor values of 66% and 80% respectively with sensitivity and specificity of 29% and 95% respectively. Conclusions: An model to predict %EWL was created, only gender and pre-operative BMI were found to be significant factors. In general females have better outcomes with higher BMI’s than do males. This information should be discussed with patients when deciding a procedure. However, more studies are needed for validation of these results.
Keywords: multivariate analysis; Roux-en-Y Gastric Bypass; Predictive factors; BMI; Gender.