Comparison Between Automated Office Blood Pressure And Traditional Office Blood Pressure Under The Environment Of Health Checkup Among Japanese General Population

JOURNAL OF HYPERTENSION(2018)

引用 0|浏览10
暂无评分
摘要
Objectives: To compare the automated office blood pressure (AOBP) measurement with traditional office blood pressure (BP) measurement for general population under the environment of health checkup. Methods: Participants were recruited by advertising the study through public relations magazine. Study staffs were trained to program an Omron 907 to wait 3 minutes and then record 2 readings at 1-minute intervals. After the device was activated, research staff left the examining room, with the participants being alone. Traditional office BP measurement was recorded 2 readings at 1-minute intervals after 2 minute rest by five doctors wearing white coats using electronic sphygmomanometer. We compared the average measurement value of AOBP and office BP. Results: There were 207 participants (73 males, 138 females, mean age 64.2 years) who were 20 years of age or older, and 79 participants had previously diagnosed hypertension. Mean AOBPs were 128.4 ± 19.6/75.5 ± 12.2 mmHg, and office BPs were 133.6 ± 20.0/78.0 ± 11.8 mmHg. There was a difference of systolic blood pressure (SBP) 5.2 ± 10.2 mmHg and diastolic blood pressure (DBP) 2.5 ± 7.4 mmHg between AOBP and office BP. In all participants, SBP increased with age in both measurement, and pulse pressure increased from 60 years of age or older. In addition, the white coat effect tended to be detected as much as older. In 79 participants undergoing hypertension treatment, the SBP difference was 5.6 ± 12.0 mmHg and the DBP difference was 2.9 ± 8.8 mmHg and the white coat effect was more strongly observed. Conclusion: Even in the health checkup environment of the general population, there was a difference between the AOBP measurement value and office BP measurement value, and the white coat effect was observed more strongly as the elderly.
更多
查看译文
关键词
AOBP, office BP
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要