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Nomogram For Predicting Remission Of Metabolic Syndrome 1 Year After Sleeve Gastrectomy Surgery In Chinese Patients With Obesity.

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Nomogram For Predicting Remission Of Metabolic Syndrome 1 Year After Sleeve Gastrectomy Surgery In Chinese Patients With Obesity.

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Nomogram for Predicting Remission of Metabolic Syndrome 1 Year after Sleeve Gastrectomy Surgery in Chinese Patients

Yunhui Pan¹, Xiaodong Han², Yinfang Tu¹

¹Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Clinical Center of Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai, 200233, China.

Obesity Surgery

|March 13, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

A new nomogram accurately predicts metabolic syndrome remission after sleeve gastrectomy in obese patients. This tool aids in assessing the likelihood of remission one year post-surgery.

Keywords:

Metabolic syndrome Nomogram Sleeve gastrectomy

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Area of Science:

Bariatric Surgery
Metabolic Disorders
Predictive Modeling

Background:

Sleeve gastrectomy (SG) is a key treatment for obesity and related metabolic issues.
Currently, no specific tool exists to forecast metabolic syndrome (MS) remission post-SG.

Purpose of the Study:

To develop and validate a nomogram for predicting MS remission probability in obese patients one year after SG.
To identify key predictors of MS remission following sleeve gastrectomy.

Main Methods:

Retrospective analysis of 318 obese patients with preoperative MS who underwent SG.
Development of a nomogram using multivariate logistic regression on a training set.
Validation of the nomogram's discrimination and calibration using a separate validation set and decision curve analysis (DCA).

Main Results:

A nomogram incorporating age, preoperative HDL cholesterol, triglycerides, and glycated hemoglobin was developed.
The nomogram demonstrated moderate discriminative ability (AUC 0.800 training, 0.727 validation) and good calibration.
Decision curve analysis indicated clinical utility for the nomogram in both datasets.

Conclusions:

The developed nomogram accurately predicts metabolic syndrome remission in Chinese obese patients one year after sleeve gastrectomy.
This tool can assist clinicians in managing and counseling patients undergoing SG for obesity and metabolic abnormalities.