Zhao Zhenqiao, Liang Junchao, Hou Shujie, Zhu Guojia, Liu Ning, Hao Wei, Xu Zhijuan
Graduate School of Hebei University of Traditional Chinese Medicine, Shijiazhuang, Hebei, China.
Department of Anesthesiology, Hebei Provincial Hospital of Traditional Chinese Medicine, Hebei Technology Innovation Center of TCM Spleen and Kidney Diseases, Shijiazhuang, Hebei, China.
Front Neurol. 2025 May 7;16:1513395. doi: 10.3389/fneur.2025.1513395. eCollection 2025.
Heart rate variability (HRV), which reflects the balance of the sympathetic and parasympathetic systems, is associated with insomnia. However, its relationship with preoperative acute insomnia has not yet been investigated. This study aimed to assess the associations of HRV characteristics with preoperative acute insomnia.
This study enrolled 563 patients who were scheduled for elective surgery. Preoperative clinical characteristics, including demographics, the apnea-hypopnea index (AHI), HRV characteristics, and sleep quality data, were recorded.
Among the 563 patients included, 78.5% met the criteria for insomnia. Age ( = 0.005), AHI score ( < 0.001), and AHI stage ( < 0.001) were positively associated, whereas education level ( = 0.004) was negatively associated with preoperative acute insomnia. In terms of HRV characteristics, low-frequency (LF) ( = 0.012) and high-frequency (HF) ( = 0.011) were positively associated with preoperative acute insomnia. Multivariate logistic regression analyses screened out the variables associated with preoperative acute insomnia, including education level [ = 0.028, odds ratio (OR) = 0.603], AHI score ( < 0.001, OR = 1.068), standard deviation of all normal NN intervals (SDNN) ( = 0.004, OR = 0.956), the root mean square of the successive differences (rMSSD) (= 0.001, OR = 1.130), NN50 count divided by the total number of all NN intervals (pNN50) ( = 0.006, OR = 0.893), ultra-low-frequency (ULF) ( = 0.003, OR = 1.000), LF/HF ratio ( = 0.018, OR = 0.608), and HF ratio ( = 0.072, OR = 0.953). Receiver operating characteristic analysis revealed that the combination of these variables had good predictive value for preoperative acute insomnia, with an area under the curve of 0.750.
Preoperative acute insomnia is a prevalent issue and is associated with an imbalance in the sympathetic/parasympathetic system. A predictive model based on HRV characteristics may improve the management of preoperative acute insomnia.
心率变异性（HRV）反映交感神经和副交感神经系统的平衡，与失眠有关。然而，其与术前急性失眠的关系尚未得到研究。本研究旨在评估HRV特征与术前急性失眠的相关性。
本研究纳入了563例计划接受择期手术的患者。记录术前临床特征，包括人口统计学资料、呼吸暂停低通气指数（AHI）、HRV特征和睡眠质量数据。
在纳入的563例患者中，78.5%符合失眠标准。年龄（=0.005）、AHI评分（<0.001）和AHI分期（<0.001）与术前急性失眠呈正相关，而教育水平（=0.004）与术前急性失眠呈负相关。在HRV特征方面，低频（LF）（=0.012）和高频（HF）（=0.011）与术前急性失眠呈正相关。多因素logistic回归分析筛选出与术前急性失眠相关的变量，包括教育水平[=0.028，比值比（OR）=0.603]、AHI评分（<0.001，OR=1.068）、所有正常NN间期的标准差（SDNN）（=0.004，OR=0.956）、逐次差值的均方根（rMSSD）（=0.001，OR=1.130）、NN50计数除以所有NN间期总数（pNN50）（=0.006，OR=0.893）、超低频（ULF）（=0.003，OR=1.000）、LF/HF比值（=0.018，OR=0.608）和HF比值（=0.072，OR=0.953）。受试者工作特征分析显示，这些变量的组合对术前急性失眠具有良好的预测价值，曲线下面积为0.750。
术前急性失眠是一个普遍存在的问题，与交感神经/副交感神经系统失衡有关。基于HRV特征的预测模型可能会改善术前急性失眠的管理。
