BACKGROUND: The standard analysis of bariatric surgery weight outcomes data (using t tests) is well known. However, these uncontrolled comparisons may yield misleading results and limit the range of research questions. The aim of the study was to develop a valid approach to the longitudinal analysis of weight loss outcomes after bariatric surgery using multivariable mixed models. This study has a multi-institutional setting. METHODS: We developed a mixed-effects model to examine weight after gastric bypass surgery while controlling for several independent variables: gender, anastomotic technique, age, race, initial weight, height, and institution. We contrasted this approach with traditional uncontrolled analyses using percent excess weight loss (%EWL). RESULTS: One thousand one hundred sixty-eight gastric bypass procedures were performed between 2000 and 2006. The average %EWL at 1, 2, and 3 years was 71%, 79%, and 76%, respectively. Using weight as the outcome variable, initial weight and gender were the only independent predictors of outcome (p<0.001). %EWL was substantially less accurate than weight as an outcome measure in multivariable modeling. Including initial weight and height as separate independent variables yielded a more accurate model than using initial body mass index. In a traditional uncontrolled analysis, average %EWL was higher in women than men. However, average weight loss was lower, not higher, in women (p<0.001) in our multivariable mixed model. Height, surgical technique, race and age did not independently predict weight loss. CONCLUSIONS: Multivariable mixed models provide more accurate analyses of weight loss surgery than traditional methods and should be used in studies that examine repeated measurements.
BACKGROUND: The standard analysis of bariatric surgery weight outcomes data (using t tests) is well known. However, these uncontrolled comparisons may yield misleading results and limit the range of research questions. The aim of the study was to develop a valid approach to the longitudinal analysis of weight loss outcomes after bariatric surgery using multivariable mixed models. This study has a multi-institutional setting. METHODS: We developed a mixed-effects model to examine weight after gastric bypass surgery while controlling for several independent variables: gender, anastomotic technique, age, race, initial weight, height, and institution. We contrasted this approach with traditional uncontrolled analyses using percent excess weight loss (%EWL). RESULTS: One thousand one hundred sixty-eight gastric bypass procedures were performed between 2000 and 2006. The average %EWL at 1, 2, and 3 years was 71%, 79%, and 76%, respectively. Using weight as the outcome variable, initial weight and gender were the only independent predictors of outcome (p<0.001). %EWL was substantially less accurate than weight as an outcome measure in multivariable modeling. Including initial weight and height as separate independent variables yielded a more accurate model than using initial body mass index. In a traditional uncontrolled analysis, average %EWL was higher in women than men. However, average weight loss was lower, not higher, in women (p<0.001) in our multivariable mixed model. Height, surgical technique, race and age did not independently predict weight loss. CONCLUSIONS: Multivariable mixed models provide more accurate analyses of weight loss surgery than traditional methods and should be used in studies that examine repeated measurements.
Authors: Horacio E Oria; Carlos Carrasquilla; Paul Cunningham; Douglas S Hess; Patrice Johnell; Mark D Kligman; Melodie K Moorehead; Francesco S Papadia; Kathleen E Renquist; Raul Rosenthal; Thomas A Stellato Journal: Surg Obes Relat Dis Date: 2005 Jan-Feb Impact factor: 4.734
Authors: Ricard Corcelles; Mena Boules; Dvir Froylich; Amani Hag; Christopher R Daigle; Ali Aminian; Stacy A Brethauer; Barto Burguera; Philip R Schauer Journal: Obes Surg Date: 2016-08 Impact factor: 4.129
Authors: Anita P Courcoulas; Nicholas J Christian; Robert W O'Rourke; Greg Dakin; E Patchen Dellinger; David R Flum; Ph D Melissa Kalarchian; James E Mitchell; Emma Patterson; Alfons Pomp; Walter J Pories; Konstantinos Spaniolas; Kristine Steffen; Bruce M Wolfe; Steven H Belle Journal: Surg Obes Relat Dis Date: 2015-01-23 Impact factor: 4.734
Authors: Janelle W Coughlin; Angela S Guarda; Jeanne M Clark; Margaret M Furtado; Kimberley E Steele; Leslie J Heinberg Journal: J Clin Psychol Med Settings Date: 2013-12