背景:本研究旨在探索基于心电图(ECG)指数的模型是否可以预测美托洛尔治疗小儿体位性心动过速综合征(POTS)的有效性。
方法:本研究由训练集和外部验证集组成。纳入接受美托洛尔治疗的POTS儿童和青少年,在后续行动之后,根据美托洛尔的疗效,将他们分为无应答者和应答者.在训练集中分析两组之间治疗前基线ECG指标的差异。进一步对显著不同的基线变量和治疗效果之间的关联进行二元logistic回归分析。建立列线图模型来预测对美托洛尔的治疗反应。接收器工作特性曲线(ROC),校准,和内部验证用于评估预测模型。在外部验证集中验证了模型的预测能力。
结果:在95名患者中,65对美托洛尔治疗有反应,30人没有回应。在响应者中,校正后P波的最大值(Pcmax),P波色散(Pd),修正后的Pd(Pcd),QT间期离散度(QTd),校正后的QTd(QTcd),最大T峰到T端间隔(Tpemax),T峰间离散度(Tped)延长(P均<0.01),与无反应者相比,P波振幅增加(P<0.05)。相比之下,校正后P波持续时间的最小值(Pcmin),校正后QT间期的最小值(QTcmin),应答者的最小T峰至T端间隔(Tpemin)短于非应答者(分别为P<0.01,<0.01和<0.01)。基于临床意义和多重共线性分析筛选上述指标,构建二元logistic回归模型。因此,预处理Pcmax,QTcmin,和Tped被确定为显著相关的因素,可以组合在一起,以提供对研究对象中美托洛尔治疗反应的准确预测,产生良好的辨别力[曲线下面积(AUC)=0.970,95%置信区间(CI)0.942-0.998],预测灵敏度为93.8%,特异性为90.0%,良好的校准,校正的C指数为0.961。此外,校正曲线与标准曲线拟合良好。引导重复采样的内部验证的准确性为0.902。相比之下,kappa值为0.769,表明预测模型与实际观测结果的一致性令人满意.在外部验证集中,预测模型的AUC为0.895,敏感性和特异性分别为90.9%和95.0%,分别。
结论:成功开发了高精度预测模型,并进行了外部验证。它对美托洛尔对儿童和青少年POTS的治疗效果具有良好的预测价值。
The present work was designed to explore whether electrocardiogram (ECG) index-based models could predict the effectiveness of metoprolol therapy in pediatric patients with postural tachycardia syndrome (POTS).
This study consisted of a training set and an external validation set. Children and adolescents with POTS who were given metoprolol treatment were enrolled, and after follow-up, they were grouped into non-responders and responders depending on the efficacy of metoprolol. The difference in pre-treatment baseline ECG indicators was analyzed between the two groups in the training set. Binary logistic regression analysis was further conducted on the association between significantly different baseline variables and therapeutic efficacy. Nomogram models were established to predict therapeutic response to metoprolol. The receiver-operating characteristic curve (ROC), calibration, and internal validation were used to evaluate the prediction model. The predictive ability of the model was validated in the external validation set.
Of the 95 enrolled patients, 65 responded to metoprolol treatment, and 30 failed to respond. In the responders, the maximum value of the P wave after correction (Pcmax), P wave dispersion (Pd), Pd after correction (Pcd), QT interval dispersion (QTd), QTd after correction (QTcd), maximum T-peak-to-T-end interval (Tpemax), and T-peak-to-T-end interval dispersion (Tped) were prolonged (all P < 0.01), and the P wave amplitude was increased (P < 0.05) compared with those of the non-responders. In contrast, the minimum value of the P wave duration after correction (Pcmin), the minimum value of the QT interval after correction (QTcmin), and the minimum T-peak-to-T-end interval (Tpemin) in the responders were shorter (P < 0.01, < 0.01 and < 0.01, respectively) than those in the non-responders. The above indicators were screened based on the clinical significance and multicollinearity analysis to construct a binary logistic regression. As a result, pre-treatment Pcmax, QTcmin, and Tped were identified as significantly associated factors that could be combined to provide an accurate prediction of the therapeutic response to metoprolol among the study subjects, yielding good discrimination [area under curve (AUC) = 0.970, 95% confidence interval (CI) 0.942-0.998] with a predictive sensitivity of 93.8%, specificity of 90.0%, good calibration, and corrected C-index of 0.961. In addition, the calibration curve and standard curve had a good fit. The accuracy of internal validation with bootstrap repeated sampling was 0.902. In contrast, the kappa value was 0.769, indicating satisfactory agreement between the predictive model and the results from the actual observations. In the external validation set, the AUC for the prediction model was 0.895, and the sensitivity and specificity were 90.9% and 95.0%, respectively.
A high-precision predictive model was successfully developed and externally validated. It had an excellent predictive value of the therapeutic effect of metoprolol on POTS among children and adolescents.