Bekenova Nazira, Vochshenkova Tamara, Aitkaliyev Alisher, Imankulova Balkenzhe, Turgumbayeva Zhanatgul, Kassiyeva Balzhan, Benberin Valeriy
Medical Centre Hospital of President's Affairs Administration of the Republic of Kazakhstan, Mangilik El 80, Astana 010000, Kazakhstan.
University Medical Center Corporate Fund, Kerey and Zhanibek Khans St 5/1, Astana 010000, Kazakhstan.
Int J Environ Res Public Health. 2024 Dec 11;21(12):1653. doi: 10.3390/ijerph21121653.
In clinical practice, heart rate variability (HRV) has not been considered an indicator for the preventive assessment of cardiovascular autonomic neuropathy (CAN). The paper studies HRV in a large, randomly selected group. A cross-sectional study included a representative sample of 5707 Kazakhs aged 20 years and older from a total population of 25,454 attached to an urban clinic in the capital of Kazakhstan. The sample was drawn from individuals who visited the clinic for a preventive examination. CAN diagnosis was confirmed using data from questionnaires, electronic medical records, HRV, and heart rate measurements. Mean values of the standard deviation of normal sinus RR intervals (SDNN) and the root mean square of successive RR interval differences (RMSSDs) from a 24 h electrocardiogram recording were assessed. CAN was identified in 17.19% of the study participants, with a ratio of the subclinical to clinical phase of 1:0.24. Diabetes mellitus was present in 30.99% of patients with CAN. The prevalence of CAN varied by sex and age, aligning with the prevalence trajectory of diabetes. It was concluded that the SDNN and RMSSD parameters in electrocardiographic studies can be used for preventive measures in the context of limited healthcare resources.
在临床实践中，心率变异性（HRV）尚未被视为心血管自主神经病变（CAN）预防性评估的指标。本文在一个大型随机抽样群体中研究了HRV。一项横断面研究纳入了来自哈萨克斯坦首都一家城市诊所25454名总人口中5707名年龄在20岁及以上的哈萨克族代表性样本。该样本取自前往诊所进行预防性检查的个体。使用问卷、电子病历、HRV和心率测量数据来确诊CAN。评估了24小时心电图记录中正常窦性RR间期标准差（SDNN）和连续RR间期差值的均方根（RMSSD）的平均值。在17.19%的研究参与者中发现了CAN，亚临床期与临床期的比例为1:0.24。30.99%的CAN患者患有糖尿病。CAN的患病率因性别和年龄而异，与糖尿病的患病率轨迹一致。得出的结论是，在医疗资源有限的情况下，心电图研究中的SDNN和RMSSD参数可用于预防措施。
