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智能终端手表估计颈股脉搏波速度的准确性评估

Accuracy Evaluation of Carotid-Femoral Pulse Wave Velocity Estimated by Smart Terminal Watch.

作者信息

Sun Ningling, Wang Luyan, Xi Yang, Wang Hongyi, Yang Fan, Chen Yuanyuan, Liu Jing, Cui Yuxian, Zeng Zhechun

机构信息

Department of Hypertension, Peking University People's Hospital, Beijing, China.

Beijing Institute of Heart Lung and Blood Vessel Disease, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.

出版信息

Front Cardiovasc Med. 2022 Jul 22;9:893557. doi: 10.3389/fcvm.2022.893557. eCollection 2022.

Abstract

To evaluate the accuracy of the smartwatch in estimating carotid-femoral pulse wave velocity (cfPWV). A cohort of gender-matched volunteers aged 18-80 years were recruited. At the sitting and supine positions, cfPWV was measured alternately by smartwatch and CompliorAnalyse, for each participant, and nine sets of data were collected from each participant with a 60 s interval between measurements. The accuracy of cfPWV measurement for smartwatches was assessed using mean error (ME) and mean absolute error (MAE), while the consistency of the two methods was assessed using the Bland-Altman analysis and concordance class correlation. A total of 347 participants were enrolled. The mean cfPWV was 9.01 ± 2.29 m/s measured by CompliorAnalyse and 9.06 ± 1.94 m/s by smartwatch. The consistency correlation coefficient (CCC) was 0.9045 (95% CI 0.8853-0.9206), the ME was 0.046 ± 0.92, and the MAE was 0.66 (95% CI 0.59-0.73). Bland-Altman analysis showed that the error of 95% samples was in the range between -1.77 m/s and 1.86 m/s. The Kappa value of cfPWV greater than 10 m/s was 0.79, the area under the ROC curve was 0.97 ( < 0.001), sensitivity was 0.90, specificity was 0.93, positive predictive value was 0.83 and negative predictive value was 0.96. Smartwatch can accurately estimate cfPWV to evaluate arterial stiffness. This method is simple and feasible and is suitable for people to actively and early monitor vascular elasticity.

摘要

评估智能手表在估计颈股脉搏波速度(cfPWV)方面的准确性。招募了一组年龄在18 - 80岁的性别匹配志愿者。在坐位和仰卧位时,由智能手表和CompliorAnalyse交替测量每位参与者的cfPWV,每次测量间隔60秒,从每位参与者收集九组数据。使用平均误差(ME)和平均绝对误差(MAE)评估智能手表测量cfPWV的准确性,同时使用Bland - Altman分析和一致性类别相关性评估两种方法的一致性。共招募了347名参与者。CompliorAnalyse测量的平均cfPWV为9.01±2.29米/秒,智能手表测量的为9.06±1.94米/秒。一致性相关系数(CCC)为0.9045(95%CI 0.8853 - 0.9206),ME为0.046±0.92,MAE为0.66(95%CI 0.59 - 0.73)。Bland - Altman分析显示,95%样本的误差在 - 1.77米/秒至1.86米/秒之间。cfPWV大于10米/秒时的Kappa值为0.79,ROC曲线下面积为0.97(<0.001),敏感性为0.90,特异性为0.93,阳性预测值为0.83,阴性预测值为0.96。智能手表可以准确估计cfPWV以评估动脉僵硬度。该方法简单可行,适合人们主动早期监测血管弹性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7a50/9353553/6511432c462b/fcvm-09-893557-g001.jpg

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