基于心率变异性的生物年龄估计:一项初步研究

Oleksiy Bashkirtsev, Vitaliy Sagan, V. Gaevska, O. Zimba
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引用次数: 1

摘要

介绍。生物年龄(BA)的生物标记物对抗衰老研究和实践至关重要,因为它们可以预测预期寿命、检测过早衰老和估计抗衰老计划的有效性。本研究的目的是临床验证基于心率变异性(HRV)分析、人工智能技术和生物特征监测的生物年龄估计方法。方法。在医疗中心“Edem medical”接受健康和康复服务的51名患者中,基于HRV和机器学习算法的分析确定了生物年龄。并将该方法与其他已知的生物年龄估计方法进行了比较。选择医师以脆弱指数为基础的生物年龄估计作为参考方法。第二种方法是DNA甲基化年龄(DNAm PhenoAge)。该方法根据血液中的9个参数(白蛋白、肌酐、葡萄糖、c反应蛋白、淋巴细胞[%]、平均红细胞体积[MCV]、红细胞分布宽度[RDW]、碱性磷酸酶、白细胞计数)预测生物年龄。使用“留一个”技术,根据血液测试参数和ECG信号作为输入数据,创建了一个额外的算法来近似生物年龄。早上空腹、卧卧10分钟后进行HRV评估。采用Mawi Vital多传感器仪记录心电。使用以下统计检验来揭示不同生物年龄估计方法之间的关联:二元相关,2。平均绝对误差(MAE), 3。定性二元年龄估计。结果。所有测试的BA评估方法都与参考方法(医生确定年龄)有很强的相关性。基于HRV的入路优于其他方法。10例中有9例采用HRV进行的定性二元年龄评估与参考方法一致。HRV法对基于MAE的生物年龄估计最准确(3.62 vs 12.62)。结论。基于HRV的方法是一种经济、方便的生物年龄估计方法。这种方法为有加速衰老风险的个体提供了早期分层的机会。它很好地结合了基于预防、预测和个性化治疗每位患者的3p医学范式
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BIOLOGICAL AGE ESTIMATION BASED ON HEART RATE VARIABILITY: A PILOT STUDY
Introduction. Biomarkers of biological age (BA) are essential for anti-aging research and practice because of their prediction of life expectancy, detection of premature aging, and estimation of anti-ageing programs' effectiveness. The purpose of this study is a clinical validation of the method of biological age estimation based on the analysis of heart rate variability (HRV), artificial intelligence technologies, and biometric monitoring. Methods. In 51 patients who received wellness and rehabilitation services in the medical center "Edem Medical", biological age was determined based on the analysis of HRV and machine learning algorithms. A comparison was made between the proposed method and other known methods of biological age estimation. Biological age estimation by physicians which is based on the Frailty Index was chosen as a reference method. The second method was DNA methylation age (DNAm PhenoAge). This method predicts biological age based on nine parameters of blood (albumin, creatinine, glucose, C-reactive protein, lymphocytes [%], mean corpuscular volume [MCV], red cell distribution width [RDW], alkaline phosphatase, WBC count). Using the «leave one out» technique, an additional algorithm was created for approximating biological age in view of blood test parameters and ECG signals as input data. Morning HRV assessment was performed on empty stomach and after 10-minute rest in horizontal position. ECG was recorded using Mawi Vital multisensor device. The following statistical tests were used to reveal associations between different methods of biological age estimation: 1. bivariate correlation, 2. mean absolute error (MAE), 3. qualitative binary age estimation. Results. All tested methods of BA evaluation were strongly correlated with the reference method (physician-determined age). HRV based approach was superior in comparison with other methods. In 9 out of 10 cases, the qualitative binary age assessment using HRV coincided with the reference method. The HRV method was the most accurate for biological age estimation (3.62 vs 12.62) based on MAE. Conclusion. The method based on HRV is an affordable and convenient approach to biological age estimation. This method offers opportunities for early stratification of individuals at risk of accelerated aging. It combines well with the paradigm of 3 P medicine which is based on Prevention, Prediction, and Personalized approach to each patient
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