Value of Immediate Heart Rate Alteration From Supine to Upright in Differential Diagnosis Between Vasovagal Syncope and Postural Tachycardia Syndrome in Children

摘要

>Objectives: To explore the predictive value of immediate heart rate alteration from supine to upright in the differential diagnosis between vasovagal syncope (VVS) and postural tachycardia syndrome (POTS) in children.>Materials and Methods: A total of 76 pediatric outpatients or inpatients who visited the Peking University First Hospital from July 2016 to November 2017 were recruited in the study. Among them, 52 patients were diagnosed with VVS and 24 patients were diagnosed with POTS. The differential diagnostic value of acceleration index (AI) and 30/15 ratio was evaluated by the receiver operating characteristic (ROC) curve. An external validation test was performed in another 46 patients.>Results: Compared with the cases in the VVS group, patients in the POTS group had a significantly increased AI but a decreased 30/15 ratio (33.495 ± 8.472 vs. 23.440 ± 8.693, p < 0.001; 0.962 ± 0.067 vs. 1.025 ± 0.084, p = 0.002; respectively). The ROC curves showed that AI and 30/15 ratio were useful for differentiating POTS from VVS. A cut-off value of AI set at 28.180 yielded a sensitivity of 79.2% and a specificity of 73.1%. A cut-off value of 30/15 ratio set at 1.025 yielded a sensitivity of 87.5% and a specificity of 61.5%. A combined use of these two indices improved the sensitivity to 95.8% when either AI or 30/15 was used, and specificity to 80.8% with the use of both AI and 30/15 at the same diagnosis. The external validation test showed that the positive and negative predictive values of the AI and 30/15 ratio were 77.3 and 79.2%, and 72.0 and 81.0%, respectively. The positive predictive value increased to 87.5% when both the AI and 30/15 ratio cut-off values were used together.>Conclusions: The AI and 30/15 ratio, which are easy to perform and non-invasive, have proper sensitivity and specificity to differentiate patients with POTS from those with VVS. The combination of these two indices significantly improves the predictive value.