Huang Tien-Chi, Chi Nai-Yu, Lan Chih-Sung, Chen Chang-Jen, Jhuo Shih-Jie, Lin Tsung-Han, Liu Yi-Hsueh, Chou Li-Fang, Chang Chien-Wei, Liao Wei-Sheng, Kao Pei-Heng, Hsu Po-Chao, Lee Chee-Siong, Lin Yi-Hsiung, Lee Hsiang-Chun, Lu Ye-Hsu, Yen Hsueh-Wei, Lin Tsung-Hsien, Su Ho-Ming, Lai Wen-Ter, Tsai Wei-Chung, Lin Shien-Fong, Lee Chien-Hung
Division of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan.
Division of Cardiology, Department of Internal Medicine, Show Chwan Memorial Hospital, Changhua 500, Taiwan.
J Pers Med. 2021 Oct 21;11(11):1053. doi: 10.3390/jpm11111053.
(1) Background: The autonomic imbalance plays a role in vasovagal syncope (VVS) diagnosed by head-up tilting test (HUT). neuECG is a new method of recording skin electrical signals to simultaneously analyze skin sympathetic nerve activity (SKNA) and electrocardiogram. We hypothesize that SKNA is higher in subjects with tilt-positive than tilt-negative and the SKNA surges before syncope. (2) Methods: We recorded neuECG in 41 subjects who received HUT (according to the "Italian protocol"), including rest, tilt-up, provocation and recovery phases. Data were analyzed to determine the average SKNA (aSKNA, μV) per digitized sample. Electrocardiogram was used to calculate standard deviation of normal-to-normal beat intervals (SDNN). The "SKNA-SDNN index" was calculated by rest aSKNA multiplied by the ratio of tilt-up to rest SDNN. (3) Results: 16 of 41 (39%) subjects developed syncope. The aSKNA at rest phase is significantly higher in the tilt-positive (1.21 ± 0.27 µV) than tilt-negative subjects (1.02 ± 0.29 µV) ( = 0.034). There are significant surges and withdraw of aSKNA 30 s before and after syncope (both ≤ 0.006). SKNA-SDNN index is able to predict syncope ( < 0.001). (4) Conclusion: Higher SKNA at rest phase is associated with positive HUT. The SKNA-SDNN index is a novel marker to predict syncope during HUT.
（1）背景：自主神经失衡在通过直立倾斜试验（HUT）诊断的血管迷走性晕厥（VVS）中起作用。神经心电图（neuECG）是一种记录皮肤电信号以同时分析皮肤交感神经活动（SKNA）和心电图的新方法。我们假设倾斜试验阳性受试者的SKNA高于倾斜试验阴性受试者，且SKNA在晕厥前激增。（2）方法：我们对41名接受HUT（根据“意大利方案”）的受试者进行了神经心电图记录，包括静息、倾斜、激发和恢复阶段。分析数据以确定每个数字化样本的平均SKNA（aSKNA，微伏）。使用心电图计算正常心动周期间期的标准差（SDNN）。“SKNA - SDNN指数”通过静息aSKNA乘以倾斜与静息SDNN的比值来计算。（3）结果：41名受试者中有16名（39%）发生了晕厥。倾斜试验阳性受试者静息期的aSKNA（1.21±0.27微伏）显著高于倾斜试验阴性受试者（1.02±0.29微伏）（P = 0.034）。晕厥前后30秒aSKNA有显著的激增和下降（均P≤0.006）。SKNA - SDNN指数能够预测晕厥（P<0.001）。（4）结论：静息期较高的SKNA与HUT阳性相关。SKNA - SDNN指数是预测HUT期间晕厥的一种新标志物。
