Literature DB >> 11735279

Biexponential model for predicting weight loss after gastric surgery for obesity.

E H Livingston1, J L Sebastian, S Huerta, I Yip, D Heber.   

Abstract

BACKGROUND: Following gastric restrictive surgery, morbidly obese patients rarely achieve their ideal body weight defined by Metropolitan Life tables. The final body weight will depend on the initial body composition because there will be greater weight loss from fat than lean body mass. The purpose of this study was to develop a mathematical model that accurately estimates the rate and extent of weight loss following gastric bypass surgery.
METHODS: Patients underwent gastric bypass followed by intensive medical therapy and serial bioelectrical impedance analysis (BIA) body composition measurements. Differential equations were derived to model weight loss.
RESULTS: Weight loss in the fat and lean body compartments followed monoexponential decay kinetics with differing rate constants. Total body weight loss (W(T)) at time t was W(T) = k(f)(k(f) - k(l)) (W(f(o))e(-k(f)t) + W(l(o))e(-k(l)t)), where W(fo) and W(lo) are the initial fat and lean body masses determined by BIA and k(f) and k(l) are the rate constants for the fat and lean compartments, respectively. Following surgically induced weight loss, k(f) = 7.61 +/- 1.27 x 10(-2), and k(l) = -0.93 +/- 0.13 x 10(-2), with the ratio of residual sum of the squares to the total sum of the squares of 98.8%.
CONCLUSION: Accurate prediction of weight loss depends on the initial fat and lean compartment mass since each of these loses weight at a different rate and to a different extent. When these effects are accounted for, the total body weight loss can be accurately predicted for any given time following surgery.

Entities:  

Mesh:

Year:  2001        PMID: 11735279     DOI: 10.1006/jsre.2001.6286

Source DB:  PubMed          Journal:  J Surg Res        ISSN: 0022-4804            Impact factor:   2.192


  8 in total

1.  Comparability of weight loss reporting after gastric bypass and sleeve gastrectomy using BOLD data 2008-2011.

Authors:  John P Sczepaniak; Milton L Owens; Heena Shukla; John Perlegos; William Garner
Journal:  Obes Surg       Date:  2015-05       Impact factor: 4.129

2.  A mathematical model of the effects of resistance exercise-induced muscle hypertrophy on body composition.

Authors:  Marcella Torres; Eric T Trexler; Abbie E Smith-Ryan; Angela Reynolds
Journal:  Eur J Appl Physiol       Date:  2017-12-18       Impact factor: 3.078

3.  Predictors of Inadequate Weight Loss After Laparoscopic Gastric Bypass for Morbid Obesity.

Authors:  Waleed Al-Khyatt; Rebecca Ryall; Paul Leeder; Javed Ahmed; Sherif Awad
Journal:  Obes Surg       Date:  2017-06       Impact factor: 4.129

4.  Use of bariatric outcomes longitudinal database (BOLD) to study variability in patient success after bariatric surgery.

Authors:  Stephen C Benoit; Tina D Hunter; Diane M Francis; Nestor De La Cruz-Munoz
Journal:  Obes Surg       Date:  2014-06       Impact factor: 4.129

5.  A simpler method for predicting weight loss in the first year after Roux-en-Y gastric bypass.

Authors:  John P Sczepaniak; Milton L Owens; William Garner; Farouk Dako; Kristin Masukawa; Samuel E Wilson
Journal:  J Obes       Date:  2012-01-19

6.  Modeling transitions in body composition: the approach to steady state for anthropometric measures and physiological functions in the Minnesota human starvation study.

Authors:  James L Hargrove; Grete Heinz; Otto Heinz
Journal:  Dyn Med       Date:  2008-10-07

7.  The dynamics of human body weight change.

Authors:  Carson C Chow; Kevin D Hall
Journal:  PLoS Comput Biol       Date:  2008-03-28       Impact factor: 4.475

8.  Dissecting Long-Term Glucose Metabolism Identifies New Susceptibility Period for Metabolic Dysfunction in Aged Mice.

Authors:  Anuradha Chauhan; Heike Weiss; Franziska Koch; Saleh M Ibrahim; Julio Vera; Olaf Wolkenhauer; Markus Tiedge
Journal:  PLoS One       Date:  2015-11-05       Impact factor: 3.240

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.