| 陈晓晓,高建松.超声弹性成像技术联合血清学标志物在预测2型糖尿病中的应用价值[J].浙江中西医结合杂志,2023,33(1): |
| 超声弹性成像技术联合血清学标志物在预测2型糖尿病中的应用价值 |
| Application value of ultrasound elastography combined with serological markers in predicting type 2 diabetes mellitus |
| 投稿时间：2022-03-02 修订日期：2022-10-18 |
| DOI： |
| 中文关键词: 2型糖尿病 弹性成像 血清生物标志物 脂肪衰减度 肝脏硬度 |
| 英文关键词:Type 2 diabetes mellitus Elastography Serum biomarkers Liver stiffness measurement Liver hardness |
| 基金项目:浙江省卫生厅立项课题(2020KY770) |
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| 中文摘要: |
| 目的 探讨基于超声弹性成像技术联合外周血清学标志物构建联合模型用于识别早期2型糖尿病患者(Type 2 diabetes mellitus, T2DM)的应用价值。方法 回顾性分析2017年4月至2021年8月在杭州西溪医院行弹性成像的161例受检者相关资料,其中54例确诊为T2DM,将患者分为训练组(n=111)和测试组(n=50)。基于训练组数据选取每例患者的超声弹性成像测得的肝脏脂肪衰减值(Fat attenuation index, FAI)及硬度值(Liver stiffness measurement, LSM)并联合血清学指标使用单因素逻辑回归筛选独立临床危险因素并使用多变量逻辑回归构建预测模型。使用ROC评估联合模型在训练组中的准确性并通过验证组进行验证。结果 单因素logistic回归分析显示年龄、FAI及肌酐是识别T2DM患者的独立预测因子。基于独立预测因子构建的联合模型在训练和验证组中显示出良好的校准性能,识别T2DM患者的AUC值分别为0.809和0.802。Delong检验显示联合模型诊断效能与其他独立预测因子诊断效能均有统计学差异(P<0.05)。结论 基于超声弹性成像技术联合血清学标志物构建的联合模型可作为一种量化工具早期识别2型糖尿病。 |
| 英文摘要: |
| Objective To discuss the value of a combined model based on ultrasound elastography and peripheral serological markers for identifying patients with early type 2 diabetes mellitus (T2DM). Methods The data of 161patients who underwent elastography in Hangzhou Xixi Hospital from April 2017 to August 2021 were analyzed retrospectively,of which 54 cases were diagnosed with T2DM and were divided into a training group (n=111) and a test group (n=50).Based on the training group data, liver fat attenuation index (FAI) and liver stiffness measurement (LSM) from ultrasound elastography of each patient were selected and combined with serological indicators to screen independent clinical risk factors using univariate logistic regression, and multivariate logistic regression was used to construct Prediction models were constructed using multivariate logistic regression.Use ROC to evaluate the accuracy of the combined model in the training group and validate it with the validation group.Results Univariate logistic regression analysis showed that age, FAI and creatinine were independent predictors for identifying patients with T2DM.A combined model based on independent predictor constructs a good calibration performance in the training and verification group, with AUC values of 0.809 and 0.802 for identifying T2DM patients, The Delong test showed that there Was Significant difference Among the Diagnostic Efficiency of combined Model and Other Independent Predictive Factor (P<0.05).Conclusion A combined model based on ultrasound elastography combined with serological markers can be used as a quantitative tool for early identification of type 2 diabetes. |
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