A quantified risk-scoring system and rating model for postsurgical gastroparesis syndrome in gastric cancer patients
A quantified risk-scoring system and rating model for postsurgical gastroparesis syndrome in gastric cancer patients
复制标题
胃癌患者术后胃轻瘫综合征的量化风险评分系统和评级模型
DOI：
10.1002/jso.24691
复制
发表时间：
2017-09-15
影响因子：
2.5
通讯作者：
Wang, Peng-fei
中科院分区：
文献类型：
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作者：
Chen, Xiao-dong;Mao, Chen-chen;Wang, Peng-fei
背景与目的本研究旨在探讨肥胖与术后胃轻瘫综合征（PGS）的关系，并构建评分系统和风险模型来识别高危患者。方法对634例患者进行回顾性分析。通过受试者工作特征（ROC）曲线分析评估临床特征。进行Logistic分析以确定PGS的独立预测指标。构建了由这些指标和风险评级模型组成的评分系统，并通过ROC曲线分析进行评估。结果根据ROC曲线，PGS的内脏脂肪面积（VFA）截止值为94.00。 Logistic分析显示内脏肥胖(VFA94.00cm(2))、重建技术和肿瘤大小是PGS的独立预后因素。评分系统可以可靠地预测 PGS，ROC 曲线下面积较高（[AUC]=0.769）。高风险评级具有较高的AUC（AUC I=0.56、AUC II=0.65、AUC III=0.77），表明风险评级模型可以有效筛选PGS高风险患者。结论VFA定义的内脏肥胖可以有效预测PGS。我们的评分系统可能是识别最有 PGS 风险的患者的可靠工具。
Background and ObjectivesThe 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.MethodsA 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.ResultsBased on the ROC curves, the visceral fat area (VFA) cutoff value for PGS was 94.00. Logistic analysis showed that visceral obesity (VFA94.00cm(2)), 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.ConclusionsVisceral obesity defined by VFA effectively predicted PGS. Our scoring system may be a reliable instrument for identifying patients most at risk of PGS.