PurposeThe study was designed to investigate the profile of plasma human growth cytokines in pediatric vasovagal syncope (VVS).Materials and methodsIn the discovery set of the study, plasma human growth cytokines were measured using a Quantiboby Human Growth Factor Array in 24 VVS children and 12 healthy controls. Scatter and principal component analysis (PCA) diagrams were used to describe the samples, an unsupervised hierarchical clustering analysis was used to categorize the samples. Subsequently, the cytokines obtained from the screening assays were verified with a suspension cytokine array in the validation set of the study including 53 VVS children and 24 controls. Finally, the factors associated with pediatric VVS and the predictive value for the diagnosis of VVS were determined.ResultsIn the discovery study, the differential protein screening revealed that the plasma hepatocyte growth factor (HGF), transforming growth factor b1 (TGF-b1), insulin-like growth factor binding protein (IGFBP)-4, and IGFBP-1 in children suffering from VVS were higher than those of the controls (all adjust P- value < 0.05). However, the plasma IGFBP-6, epidermal growth factor (EGF), and IGFBP-3 in pediatric VVS were lower than those of the controls (all adjust P- value < 0.01). Meanwhile, the changes of 7 differential proteins were analyzed by volcano plot. Unsupervised hierarchical cluster analysis demonstrated that patients in the VVS group could be successfully distinguished from controls based on the plasma level of seven differential proteins. Further validation experiments showed that VVS patients had significantly higher plasma concentrations of HGF, IGFBP-1, and IGFBP-6, but lower plasma concentrations of EGF and IGFBP-3 than controls. The logistics regression model showed that increased plasma concentration of HGF and IGFBP-1 and decreased plasma concentration of EGF were correlated with the development of pediatric VVS. ROC curve analysis showed that the abovementioned 3 proteins were useful for assisting the diagnosis of VVS.ConclusionPlasma human growth cytokine profiling changed in pediatric VVS. Elevated plasma concentrations of HGF and IGFBP-1, and decreased EGF were associated factors in the development of pediatric VVS. The abovementioned three proteins are helpful for the diagnosis of pediatric VVS.
Vasovagal syncope (VVS) is a common subtype of neurally mediated syncope. It is prevalent in children and adolescents, and critically affects the quality of life of patients. In recent years, the management of pediatric patients with VVS has received extensive attention, and β-blocker serves as an important choice of the drug therapy for children with VVS. However, the empirical use of β-blocker treatment has limited therapeutic efficacy in patients with VVS. Therefore, predicting the efficacy of β-blocker therapy based on biomarkers related to the pathophysiological mechanism is essential, and great progress has been made by applying these biomarkers in formulating individualized treatment plans for children with VVS. This review summarizes recent advances in predicting the effect of β-blockers in the management of VVS in children.
Background 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). Methods 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. Results 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. Conclusions 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.
ObjectiveThis study was designed to develop an easy-to-perform and inexpensive measure to predict efficacy of the oral rehydration salts (ORS) in children with vasovagal syncope (VVS).Materials and methodsChildren diagnosed with VVS and treated with ORS for a median of 3 months at the Peking University First Hospital, China, were enrolled and followed up. Demographic data, clinical hemodynamic parameters, and variables related to red blood cells were collected at the baseline. On the basis of changes in symptom scores after treatment, participants were divided into effective or ineffective groups at the end of the follow-up. Logistic regression analysis was used to investigate parameters related to therapeutic efficacy of ORS and a predictive model of ORS effectiveness was created. The predictive efficiency was evaluated using the receiver operating characteristic curve. The accuracy/consistency was evaluated by the Hosmer–Lemeshow test and calibration curve. Internal validation was done using the bootstrap approach.ResultsTotally 97 pediatric participants were included in the study and 4 (4.1%) were lost during the follow-up. ORS therapy was effective in 46 children and ineffective in 47 children. Children in the effective group had higher baseline red blood cell count, hemoglobin, and hematocrit than those in the ineffective group (p < 0.01). Through logistic regression analysis, the baseline hematocrit and body mass index (BMI) were included in predictive model for the response to ORS treatment. The predictive efficacy of the model showed an area under the curve of 0.77 (p < 0.01). The predicted probability cut-off value of 0.5 was found to be optimal, with a resulting sensitivity of 67.4% and specificity of 80.9%. In the Hosmer–Lemeshow test, p-value was 0.75, and the calibration plot showed a good model fitness. Internal validation was performed using the bootstrap approach (n = 1,000), showing 95% confidence interval of 0.67–0.86.ConclusionHemoglobin combined with BMI was useful for predicting the therapeutic efficacy of ORS in children with VVS.
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