Karri Jay, Zhang Larry, Li Shengai, Chen Yen-Ting, Stampas Argyrios, Li Sheng
Department of Physical Medicine and Rehabilitation, The University of Texas Health Science Center at HoustonHouston, TX, United States.
TIRR Memorial Hermann Research Center, TIRR Memorial Hermann HospitalHouston, TX, United States.
Front Physiol. 2017 Jul 18;8:495. doi: 10.3389/fphys.2017.00495. eCollection 2017.
Heart rate variability (HRV), the physiological variance in the heart's R-R interval length, can be analyzed to produce various parameters reflective of one's autonomic balance. HRV analysis may be used to capture those autonomic aberrations associated with chronic neuropathic pain (NP) in spinal cord injury (SCI). This study assesses the capacity of HRV parameters to diagnose NP in an SCI cohort. An electrocardiogram (ECG) was collected at rest from able bodied participants (AB, = 15), participants with SCI only (SCI-NP, = 11), and those with SCI and NP (SCI+NP, = 20). HRV parameters were analyzed using conventional time and frequency analysis. At rest, there were no heart rate differences amongst groups. However, SCI+NP participants demonstrated lower overall HRV, as determined by the SDNN time domain parameter, compared to either AB ( < 0.01) or SCI-NP ( < 0.05) groups. Moreover, AB and SCI-NP participants were statistically comparable for all HRV time and frequency domain parameters. Additional analyses demonstrated no differences in HRV parameters between T4, above vs. T5, below SCI groups (for all parameters: > 0.15) or between C8, above vs. T1, below SCI groups ( > 0.30). Participants with SCI and NP exhibit a lower overall HRV, which can be determined by HRV time domain parameter SDNN. HRV analysis is an innovative modality with the capacity for objective quantification of chronic NP in participants with SCI.
心率变异性(HRV)是心脏R-R间期长度的生理变化,对其进行分析可得出反映个体自主神经平衡的各种参数。HRV分析可用于捕捉与脊髓损伤(SCI)中的慢性神经性疼痛(NP)相关的自主神经异常。本研究评估了HRV参数在SCI队列中诊断NP的能力。在静息状态下,从健全参与者(AB,n = 15)、仅患有SCI的参与者(SCI-NP,n = 11)以及患有SCI和NP的参与者(SCI+NP,n = 20)中收集心电图(ECG)。使用传统的时域和频域分析方法对HRV参数进行分析。静息时,各组之间心率无差异。然而,与AB组(P < 0.01)或SCI-NP组(P < 0.05)相比,SCI+NP参与者的总体HRV较低,这由SDNN时域参数确定。此外,AB组和SCI-NP组在所有HRV时域和频域参数上具有统计学可比性。进一步分析表明,T4以上与T5以下SCI组之间(所有参数:P > 0.15)或C8以上与T1以下SCI组之间(P > 0.30)的HRV参数无差异。患有SCI和NP的参与者表现出较低的总体HRV,这可以通过HRV时域参数SDNN来确定。HRV分析是一种创新方法,能够客观量化SCI参与者的慢性NP。