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首页> 外文期刊>Annals of noninvasive electrocardiology: the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc >Aspects of left ventricular morphology outperform left ventricular mass for prediction of QRS duration.
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Aspects of left ventricular morphology outperform left ventricular mass for prediction of QRS duration.

机译:在预测QRS持续时间方面,左心室形态方面优于左心室肿块。

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摘要

BACKGROUND: The knowledge of the case-specific normal QRS duration in each individual is needed when determining the onset, severity and progression of the heart disease. However, large interindividual variability even of the normal QRS duration exists. The aims of the study were to develop a model for prediction of normal QRS complex duration and to test it on healthy individuals. METHODS: The study population of healthy adult volunteers was divided into a sample for development of a prediction model (n = 63) and a testing sample (n = 30). Magnetic resonance imaging data were used to assess anatomical characteristics of the left ventricle: the angle between papillary muscles (PM(A)), the length of the left ventricle (LV(L)) and left ventricular mass (LV(M)). Twelve-lead electrocardiogram (ECG) was used for measurement of the QRS duration. Multiple linear regression analysis was used to develop a prediction model to estimate the QRS duration. The accuracy of the prediction model was assessed by comparing predicted with measured QRS duration in the test set. RESULTS: The angle between PM(A) and the length of the LV(L) were statistically significant predictors of QRS duration. Correlation between QRS duration and PM(A) and LV(L) was r = 0.57, P = 0.0001 and r = 0.45, P = 0.0002, respectively. The final model for prediction of the QRS was: QRS(Predicted)= 97 + (0.35 x LV(L)) - (0.45 x PM(A)). The predicted and real QRS duration differed with median 1 ms. CONCLUSIONS: The model for prediction of QRS duration opens the ability to predict case-specific normal QRS duration. This knowledge can have clinical importance, when determining the normality on case-specific basis.
机译:背景:在确定心脏病的发作,严重程度和进展时,需要了解每个人的具体病例正常QRS持续时间。但是,即使是正常QRS持续时间,也存在较大的个体差异。该研究的目的是建立一个预测正常QRS复合体持续时间的模型,并在健康个体上进行测试。方法:将健康成人志愿者的研究人群分为用于建立预测模型的样本(n = 63)和测试样本(n = 30)。磁共振成像数据用于评估左心室的解剖特征:乳头肌之间的角度(PM(A)),左心室的长度(LV(L))和左心室质量(LV(M))。十二导联心电图(ECG)用于测量QRS持续时间。多元线性回归分析用于建立预测模型以估计QRS持续时间。通过将预测与测试集中的QRS持续时间进行比较,评估了预测模型的准确性。结果:PM(A)与LV(L)长度之间的夹角是QRS持续时间的统计学显着预测因子。 QRS持续时间与PM(A)和LV(L)之间的相关性分别为r = 0.57,P = 0.0001和r = 0.45,P = 0.0002。预测QRS的最终模型为:QRS(Predicted)= 97 +(0.35 x LV(L))-(0.45 x PM(A))。预测QRS持续时间和实际QRS持续时间相差1 ms。结论:QRS持续时间的预测模型开启了预测特定病例正常QRS持续时间的能力。当根据案例确定正常性时,此知识可能具有临床重要性。

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