A new method for assessing variability of 24 h blood pressure and its first application in 1526 elderly men.
1. Blood pressure variability (BPV) includes physiological and random variations in blood pressure (BP). Commonly used approaches, such as standard deviation (SD) and weighted standard deviation (wSD) methods, do not efficiently assess random variation in BP. In the present study, we propose a novel method to assess individual BP variations, extracting random variation in BP by eliminating physiological variation mathematically. This novel assessment method furthers our understanding of the relationship between BP variation and lacunar infarction (LACI). 2. In the present study, we analysed ambulatory blood pressure monitoring recordings taken from 1526 men aged 60-98 years of age. Individual curves were created using a mathematical method and the related BP variation calculated, namely the SD for individual BP variations. In addition, correlations between LACI and BP variations as determined by the classical SD method, wSD and our novel assessment method (SD') were evaluated. 3. The results demonstrated that 24 h variations in systolic BP (SBP) were closely associated with LACI when the SD and wSD methods were used (P < 0.05), but the most significant correlations were observed when the SD' method was used (P < 0.01). Furthermore, using SD' yielded the lowest value of the parameter P among the three different methods used to analyse BPV. Using the SD' method, a significant correlation was found between variations in SBP and the incidence of LACI (P < 0.05). It was found that the incidence of LACI increased by 2% with each 1 mmHg increase in SBP variation. 4. In conclusion, our novel assessment method enables mathematical removal of interference from physiological BP variation and the results show a better correlation with LACI. Thus, our novel method may be considered a simple index of 24 h BP variation that is superior to conventional SD and wSD methods.
Department of Gerontology, Xinhua Hospital, Shanghai Jiaotong University, Shanghai, China. junlishanghai2005@yahoo.com.cn
Jun-Li
JL
Duan
Chang-Ning
CN
Hao
Wei
W
Lu
Li
L
Han
Zhi-Hong
ZH
Pan
Yi
Y
Gu
Pei-Jing
PJ
Liu
Rui
R
Tao
Yi-Qin
YQ
Shi
Ye-Ye
YY
Du
D000368:Aged; D000369:Aged, 80 and over; D001794:Blood Pressure / Q000502:physiology; D018660:Blood Pressure Monitoring, Ambulatory / Q000379:methods*; D020520:Brain Infarction / Q000175:diagnosis*; D002940:Circadian Rhythm / Q000502:physiology; D015577:Geriatric Assessment / Q000379:methods*; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011237:Predictive Value of Tests; D013269:Stochastic Processes