BACKGROUND: Ambulatory blood pressure correlates more closely with left ventricular mass (LVM) than casual blood pressure in cross-sectional studies, but prospective evidence is very limited. OBJECTIVE: To evaluate the best predictors of LVM and change in LVM during 10 years of follow-up, in a prospective study. METHODS: At baseline, blood pressure was recorded by casual measurements and 24 h intra-arterial ambulatory monitoring. The study participants were 97 healthy, untreated, 35-45-year-old men (34 normotensive, 29 borderline hypertensive, and 34 mildly hypertensive). At 10-year follow-up, echocardiography was performed in 86 (89%) of the men; echocardiographic data were available both at baseline and at follow-up from 70 (72%) of them. Individuals who were not receiving antihypertensive medication (n = 66) were included in the prediction of LVM index (LVMI), which was analysed as a continuous variable. RESULTS: The blood pressure variables that were best in predicting the LVMI were: 24 h pulse pressure (r = 0.308, P = 0.012), night-time pulse pressure (r = 0.291, P = 0.018), daytime pulse pressure (r = 0.253, P = 0.041), and casual systolic blood pressure (r = 0.212, P = 0.088). The LVMI was best predicted by a model including 24 h pulse pressure, positive family history of hypertension, body mass index, and age (adjusted coefficients of determination (adj.R2) = 0.197; that for the casual blood pressure model was adj.R2 = 0.140). During the follow-up, LVMI increased by +7.5 g/m2 and +23 g/m2 in individuals receiving and not receiving antihypertensive medication, respectively (P = 0.015). The change in LVMI was best predicted by the change in casual pulse pressure and use of antihypertensive medication (adj.R2 = 0.102). CONCLUSIONS: Ambulatory blood pressure improved the prediction of future LVMI compared with that obtained from casual measurements. To our knowledge, this is the longest prospective follow-up to show that pulse pressure is the most significant blood pressure parameter in predicting future LVMI and change in LVMI.
BACKGROUND: Ambulatory blood pressure correlates more closely with left ventricular mass (LVM) than casual blood pressure in cross-sectional studies, but prospective evidence is very limited. OBJECTIVE: To evaluate the best predictors of LVM and change in LVM during 10 years of follow-up, in a prospective study. METHODS: At baseline, blood pressure was recorded by casual measurements and 24 h intra-arterial ambulatory monitoring. The study participants were 97 healthy, untreated, 35-45-year-old men (34 normotensive, 29 borderline hypertensive, and 34 mildly hypertensive). At 10-year follow-up, echocardiography was performed in 86 (89%) of the men; echocardiographic data were available both at baseline and at follow-up from 70 (72%) of them. Individuals who were not receiving antihypertensive medication (n = 66) were included in the prediction of LVM index (LVMI), which was analysed as a continuous variable. RESULTS: The blood pressure variables that were best in predicting the LVMI were: 24 h pulse pressure (r = 0.308, P = 0.012), night-time pulse pressure (r = 0.291, P = 0.018), daytime pulse pressure (r = 0.253, P = 0.041), and casual systolic blood pressure (r = 0.212, P = 0.088). The LVMI was best predicted by a model including 24 h pulse pressure, positive family history of hypertension, body mass index, and age (adjusted coefficients of determination (adj.R2) = 0.197; that for the casual blood pressure model was adj.R2 = 0.140). During the follow-up, LVMI increased by +7.5 g/m2 and +23 g/m2 in individuals receiving and not receiving antihypertensive medication, respectively (P = 0.015). The change in LVMI was best predicted by the change in casual pulse pressure and use of antihypertensive medication (adj.R2 = 0.102). CONCLUSIONS: Ambulatory blood pressure improved the prediction of future LVMI compared with that obtained from casual measurements. To our knowledge, this is the longest prospective follow-up to show that pulse pressure is the most significant blood pressure parameter in predicting future LVMI and change in LVMI.
Authors: Tero J W Pääkkö; Juha S Perkiömäki; Y Antero Kesäniemi; Antti S Ylitalo; Jarmo A Lumme; Heikki V Huikuri; Olavi H Ukkola Journal: J Hum Hypertens Date: 2018-02-07 Impact factor: 3.012
Authors: Gangadarshni Chandramohan; Kamyar Kalantar-Zadeh; Dulcie Kermah; Sheena Cecille Marie Go; Nosratola D Vaziri; Keith C Norris Journal: J Am Soc Hypertens Date: 2012 Jul-Aug