Nomogram-Based Prediction Model for Suboptimal Weight Loss Outcomes After Metabolic Bariatric Surgery Using CT-Derived Body Composition Parameters: A Prospective Chinese Cohort Study.

Authors

Wei Zhu, Xiaoqing Yuan, Zhen Hao, Jia Li, Fengxia Yu, Weihua Li, Hongxia Yin, Peng Zhang, Zhenchang Wang, Wenmin Guan, Peng Zhang

Published in

Diabetes, metabolic syndrome and obesity : targets and therapy. Volume 19. Pages 614373. Epub Sep 30, 2026.

Abstract

Metabolic bariatric surgery (MBS) provides potent and sustained efficacy in managing obesity and its associated comorbidities. Nevertheless, suboptimal weight loss outcomes persist in a notable proportion of patients after MBS. This study aimed to identify influencing risk factors and develop a predictive model to predict 1-year suboptimal weight loss outcomes following MBS in a prospective Chinese cohort.
This study involved a prospective cohort of 120 patients who underwent MBS at Beijing Friendship Hospital from November 2021 to September 2023. Optimal weight loss outcome was defined as a total weight loss percentage (%TWL) ≥ 20% at the 1-year follow-up. Patient's clinical, biochemical, and CT-derived body composition parameters were collected at baseline and 1 year postoperatively. Independent predictors of suboptimal weight loss outcome were identified through univariate and multivariate logistic regression. Subsequently, a nomogram was constructed and internally validated with its discrimination, calibration, and clinical utility.
The study included 120 patients (77.5% female) with a mean age of 33.4 ± 8.7 years and a baseline body mass index (BMI) of 38.5 ± 7.1 kg/m². Patients' weight, BMI, glycemic control, lipid profiles, and body composition parameters were improved significantly after MBS (P < 0.05). Twenty‑two patients (18.3%) were categorized as suboptimal outcome. Univariate and multivariate logistic regression analyses revealed that higher fasting blood glucose (FBG, OR 1.284, P = 0.037), lower HDL-C (OR 0.426, P = 0.024), larger subcutaneous adipose tissue (SAT; OR 1.006, P = 0.018), and lower paraspinal muscle (PSM) area (OR 0.938, P = 0.033) were independent predictors of suboptimal outcomes. The resulting nomogram demonstrated good discrimination with an AUC of 0.801 (95% CI: 0.708-0.914) and calibration, with decision curve analysis confirming its clinical utility.
Preoperative body composition parameters, specifically SAT and PSM, are critical determinants of weight loss outcome following MBS. The nomogram model constructed based on biochemical and body composition factors in this prospective Chinese cohort may offers great significance for preoperative assessment for MBS candidates in China. Nevertheless, further external validation in independent cohorts is warranted before its routine clinical application.

PMID:
42831034
Bibliographic data and abstract were imported from PubMed on 05 Oct 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.