Volume 116, Issue 4 pp. 533-544
RESEARCH ARTICLE

A quantified risk-scoring system and rating model for postsurgical gastroparesis syndrome in gastric cancer patients

Xiao-dong Chen MD

Xiao-dong Chen MD

Department of Gastrointestinal Surgery, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China

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Chen-chen Mao MD

Chen-chen Mao MD

Department of Gastrointestinal Surgery, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China

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Wei-teng Zhang MD

Wei-teng Zhang MD

Department of Gastrointestinal Surgery, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China

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Ji Lin MD

Ji Lin MD

Department of Gastrointestinal Surgery, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China

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Rui-sen Wu MD

Rui-sen Wu MD

Department of Gastrointestinal Surgery, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China

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Feng-min Zhang BS

Feng-min Zhang BS

Department of Gastrointestinal Surgery, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China

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Xiang-wei Sun MD

Xiang-wei Sun MD

Department of Gastrointestinal Surgery, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China

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Chu-huai Chi MD

Chu-huai Chi MD

Department of Gastrointestinal Surgery, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China

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Xian Shen MD, PhD

Corresponding Author

Xian Shen MD, PhD

Department of Gastrointestinal Surgery, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China

Department of Gastrointestinal Surgery, The Second Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China

Correspondence

Peng-fei Wang, MD, Department of Gastrointestinal Surgery, The First Affiliated Hospital, Wenzhou Medical University, Shangcai Village, Wenzhou, Zhejiang Province, China.

Email: [email protected]

Xian Shen, PhD, Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China.

Email: [email protected]

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Peng-fei Wang MD

Corresponding Author

Peng-fei Wang MD

Department of Gastrointestinal Surgery, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China

Correspondence

Peng-fei Wang, MD, Department of Gastrointestinal Surgery, The First Affiliated Hospital, Wenzhou Medical University, Shangcai Village, Wenzhou, Zhejiang Province, China.

Email: [email protected]

Xian Shen, PhD, Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China.

Email: [email protected]

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First published: 25 July 2017
Citations: 15
Xiao-dong Chen and Chen-chen Mao contributed equally to this work.

Abstract

Background and Objectives

The study aimed to investigate the relationship between obesity and postsurgical gastroparesis syndrome (PGS), and to construct a scoring system and a risk model to identify patients at high risk.

Methods

A total of 634 patients were retrospectively analyzed. Clinical characteristics were evaluated via receiver operating characteristic (ROC) curve analysis. Logistic analysis was performed to determine the independent predictive indicators of PGS. A scoring system consisting of these indicators and a risk-rating model were constructed and evaluated via ROC curve analysis.

Results

Based on the ROC curves, the visceral fat area (VFA) cutoff value for PGS was 94.00. Logistic analysis showed that visceral obesity (VFA ≥ 94.00 cm2), the reconstruction technique, and tumor size were independent prognostic factors for PGS. The scoring system could predict PGS reliably with a high area under the ROC curve ([AUC] = 0.769). A high-risk rating had a high AUC (AUC I = 0.56, AUC II = 0.65, and AUC III = 0.77), indicating that the risk-rating model could effectively screen patients at high risk of PGS.

Conclusions

Visceral obesity defined by VFA effectively predicted PGS. Our scoring system may be a reliable instrument for identifying patients most at risk of PGS.

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