Department of Internal Medicine, University Hospital Greifswald, Germany; DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Germany.
Department of Internal Medicine, University Hospital Regensburg, Germany.
Am Heart J. 2021 Mar;233:102-108. doi: 10.1016/j.ahj.2020.12.003. Epub 2020 Dec 13.
The possibility to use built-in smartphone-cameras for photoplethysmographic (PPG) recording of pulse waves lead to the release of numerous health apps, claiming to measure blood pressure (BP) based on PPG signals. Even though these apps are highly popular, not a single one is clinically validated. Aim of the current study was to test systolic BP (sBP) estimation by a promising new algorithm in a large clinical setting.
The study was designed based on the European Society of Hypertension International Protocol Revision 2010. Each individual received 7 sequential BP measurements, starting with the reference device - an automated oscillometric cuff device - followed by the PPG recording at the patients' index finger.
A total 1,036 subjects were recruited of which 965 could be included for final analysis leading to 2,895 pairs of comparison. Mean (±SD) error between test and reference device was -0.41 (±16.52) mmHg. Only 38.1% of all 2,895 BP comparisons reached a delta within ±5 mmHg, while 29.3% reached a delta larger than 15 mmHg. Bland-Altman plot showed an overestimation of smartphone sBP in comparison to reference sBP in low range and an underestimation in high sBP range.
According to the European Society of Hypertension International Protocol Revision 2010 specifications the algorithm failed validation criteria for sBP measurement and was not commercialized. These findings emphasize that health apps should be rigorously validated according to common guidelines before market release as under- and/or overestimation of BP is potentially exposing persons at health risks in short and long term.
ClinicalTrials.gov, number NCT02552030.
利用智能手机内置摄像头进行光电容积脉搏波(PPG)记录脉搏波的可能性,导致了众多声称基于 PPG 信号测量血压(BP)的健康应用程序的发布。尽管这些应用程序非常受欢迎,但没有一个经过临床验证。本研究的目的是在大型临床环境中测试一种有前途的新算法对收缩压(sBP)的估计。
该研究是基于欧洲高血压学会国际协议 2010 年修订版设计的。每位参与者接受 7 次连续的 BP 测量,首先使用参考设备 - 自动示波法袖带设备 - 然后在患者的食指上进行 PPG 记录。
共招募了 1036 名受试者,其中 965 名可纳入最终分析,共得到 2895 对比较。测试设备与参考设备之间的平均(±SD)误差为-0.41(±16.52)mmHg。所有 2895 次 BP 比较中,只有 38.1%的差值在±5mmHg 以内,而 29.3%的差值大于 15mmHg。Bland-Altman 图显示,与参考 sBP 相比,智能手机 sBP 在低范围高估,在高 sBP 范围低估。
根据欧洲高血压学会国际协议 2010 年修订版的规范,该算法未能通过 sBP 测量的验证标准,因此未商业化。这些发现强调,健康应用程序在投放市场之前,应根据通用指南进行严格验证,因为 BP 的低估和/或高估可能会使人们在短期和长期内面临健康风险。
ClinicalTrials.gov,编号 NCT02552030。