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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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Abstract

Purpose

Sleeve gastrectomy (SG) is a widely used and effective treatment for patients with obesity and comorbid metabolic abnormalities. No specialized tool is available to predict metabolic syndrome (MS) remission after SG. We presented a nomogram that evaluated the probability of MS remission in obese patients 1 year after SG.

Materials and Methods

Patients with preoperative MS who underwent SG were enrolled in this retrospective study. They were divided into a training set and a validation set. Multivariate logistic regression analysis was performed to identify independent predictors of MS remission, and these predictors were included in the nomogram. Receiver operating characteristic curve was used to evaluate discrimination. Calibration was performed with the Hosmer–Lemeshow goodness-of-fit test. The net benefits of the nomogram were evaluated using decision curve analysis (DCA).

Results

Three hundred and eighteen patients with a median age of 34.0 years were analyzed. A training set and a validation set with 159 individuals each were established. A combination of age, preoperative high-density lipoprotein cholesterol, elevated triglycerides and glycated hemoglobin level independently and accurately predicted MS remission. The nomogram included these factors. The discriminative ability was moderate in training and validation sets (Area under curve 0.800 and 0.727, respectively). The Hosmer–Lemeshow X2 value of the nomogram was 8.477 (P = 0.388) for the training set and 5.361 (P = 0.718) for the validation set, indicating good calibration. DCA showed the nomogram had clinical benefits in both datasets.

Conclusion

Our nomogram could accurately predict MS remission in Chinese patients with obesity 1 year after SG.

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Data Availability

The data are not publicly available due to their containing information that could compromise the privacy of the research participants.

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Acknowledgements

This study was supported by grants from the Clinical Research Plan of SHDC (SHDC2020CR1017B) and Important Disease Joint Research Project in Xuhui Health Systems of Shanghai (XHLHGG202110).

Funding

This work was supported by Clinical Research Plan of SHDC, SHDC2020CR1017B, Yuqian Bao, Important Disease Joint Research Project in Xuhui Health Systems of Shanghai, XHLHGG202110, Yuqian Bao

Author information

Author notes

  1. Yunhui Pan and Xiaodong Han have contributed equally to this work.

Authors and Affiliations

  1. Department 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

    Yunhui Pan, Yinfang Tu, Haoyong Yu & Yuqian Bao

  2. Department of General Surgery, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China

    Xiaodong Han & Pin Zhang

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  1. Yunhui Pan
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  2. Xiaodong Han
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Corresponding author

Correspondence to Yuqian Bao.

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Ethics

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all individual participants included in the study.

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The authors declare that they have no conflict of interest.

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Key Points

1. A nomogram for MS remission in patients with obesity 1 year after SG is established.

2. The nomogram is composed of age, preoperative HDL-c, HbA1c, and presence of elevated TG.

3. The nomogram predicts MS remission after SG accurately with good calibration and clinical benefits.

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Pan, Y., Han, X., Tu, Y. et al. Nomogram for Predicting Remission of Metabolic Syndrome 1 Year after Sleeve Gastrectomy Surgery in Chinese Patients with Obesity. OBES SURG 34, 1590–1599 (2024). https://doi.org/10.1007/s11695-024-07156-x

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  • DOI: https://doi.org/10.1007/s11695-024-07156-x

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