三维斑点追踪超声心动图早期识别家族性肥厚型心肌病无症状突变基因携带者的临床价值
DOI:
CSTR:
作者:
作者单位:

1.宁夏医科大学总医院;2.宁夏医科大学临床医学院

作者简介:

通讯作者:

中图分类号:

基金项目:

宁夏回族自治区重点研发计划项目(项目编号2021BEG03063)


Logistic regression analysis of echocardiographic parameters in asymptomatic mutation gene carriers of familial hypertrophic cardiomyopathy
Author:
Affiliation:

General Hospital of Ningxia Medical University

Fund Project:

Key Research and Development Project of Ningxia Hui Autonomous Region (2021BEG03063)

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    目的 应用Logistic回归模型筛选超声心动图中早期识别FHCM无症状突变基因携带者(G+P-)的有效参数。方法 纳入FHCM患者一级亲属56例,依据基因检测结果进行分组,其中病例组(G+P-) 22例,对照组(G-P-) 34例。应用Philips iE33超声诊断仪及TomTec脱机分析软件获取相关超声心动图参数。使用SPSS 22.0对数据进行分析,将超声心动图参数中有统计学意义的参数设为自变量进行二元Logistic回归分析,并建立回归方程。结果 在众多超声心动图参数中,左室流出道速度时间积分(LVOT-VTI)与整体纵向应变(GLS)是识别G+P-与G-P-的独立危险因素。依此建立的回归方程为:Logistic (P)= 1.851+0.462X1+0.503X2(X1:LVOT-VTI;X2:GLS)。回归模型预测G+P-的ROC曲线下面积为0.906(95%CI:0.830-0.983),约登指数最大值为0.644,当截点值为Logistic (P)=0.247时,其预测灵敏度0.909,特异度0.735,准确度0.804。结论 Logistic回归分析在鉴别G+P-和G-P-中有良好的诊断效能,超声心动图参数LVOT-VTI与GLS可作为鉴别G+P-与G-P-的可靠指标,为G+P-者应用超声心动图精准预测提供了一种新的思路和方法。

    Abstract:

    Objective The Logistic regression model was used to screen the effective parameters for early identification of FHCM asymptomatic mutant gene carriers (G+P-) in echocardiography. Methods A total of 56 first-degree relatives of FHCM patients were enrolledand and grouped according to the results of genetic testing, including 22 cases of G+P- and 34 cases of G-P-. Philips iE33 ultrasonic diagnostic instrument and TomTec offline analysis software were used to obtain relevant echocardiographic parameters. SPSS 22.0 was used to analyze the data, and the parameters with statistical significance in echocardiography parameters were set as independent variables for binary logistic regression analysis, and regression equations were established. Results Among many echocardiographic parameters, LVOT-VTI and GLS were independent risk factors for identifying G+P- and G-P-. The regression equation thus established is: Logistic (P)= 1.851+0.462X1+0.503X2 (X1: LVOT-VTI; X2: GLS). The AUC value of the regression model to predicted G+P- was 0.906 (95%CI: 0.830-0.983), and the maximum value of Youden index was 0.644. When the cut-off value was Logistic (P)=0.247, its predictive sensitivity was 0.909, the specificity was 0.735, and the accuracy was 0.804. Conclusion Logistic regression analysis has good diagnostic performance in differentiating G+P- and G-P-. Echocardiographic parameters LVOT-VTI and GLS can be used as reliable indicators for differentiating G+P- and G-P-, which providing a new idea and method for G+P- patients to accurately predict by echocardiography.

    参考文献
    相似文献
    引证文献
引用本文

崔丽萍,段奕全,梁青青,吴楠,纳丽莎.三维斑点追踪超声心动图早期识别家族性肥厚型心肌病无症状突变基因携带者的临床价值[J].临床超声医学杂志,2023,25(10):

复制
相关视频

分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2023-01-30
  • 最后修改日期:2023-09-20
  • 录用日期:2023-04-10
  • 在线发布日期: 2023-10-30
  • 出版日期:
文章二维码

扫码关注

官方微信