Physicians' Academy for Cardiovascular Education

Long-term pattern of blood pressure changes predict subclinical atherosclerosis

Literature - Allen NB et al. JAMA. 2014 - JAMA. 2014 Feb 5;311(5):490-7


Blood pressure trajectories in early adulthood and subclinical atherosclerosis in middle age

Allen NB, Siddique J, Wilkins JT, et al.
JAMA. 2014 Feb 5;311(5):490-7. doi: 10.1001/jama.2013.285122


Current risk prediction models take into account blood pressure (BP) level only at the time of risk prediction, and do not consider a potential effect of BP levels earlier in life, or the course of BP over time. Time-averaged and cumulative BP among adults have been found to be predictive of CVD risk in prospective studies [1-4]. Also changes in BP throughout middle and older age have been found to be significantly and proportionately associated with lifetime risk of CVD [5].
Although systolic BP (SBP) increases with age in most people, patterns of BP change may differ among individuals. This study aimed to study long-term BP trajectory patterns from young adulthood through middle age and the effect on presence of subclinical atherosclerosis as measured by coronary artery calcification (CAC) during middle age. They used the prospective Coronary Artery Risk Development in Young Adults (CARDIA) cohort, in which participants have been followed up for over 25 years.
Data have been collected across 8 examination cycles and the current analyses include data of 3442 CARDIA participants with BP measures available from at least 3 examinations and CAC measurements after 25 years. Five discrete trajectories in mid-BP (mean of SBP and DBP) from young adulthood to middle age were identified: 21.8% of participants were in the low stable group, 42.3% in the moderate-stable group, 12.2% had moderate-increasing BP levels over time, 19.0% had relatively elevated but stable BP levels throughout (elevated-stable group); and 4.8% were in the elevated increasing group.

Main results

  • All groups showed a small and steady increase in SBP and DBP, including participants who took antihypertensive medications. The moderate-increasing and elevated-increasing groups experienced a larger and more rapid increase in BP over time (mean increase in SBP 30.2 and 21.2 mmHg respectively).
  • A CAC score of at least 100 Hounsfield units (HU) was seen in 4.0% of participants in the low-stable BP trajectory group, up until 25.4% in the elevated-increasing group. Participants taking antihypertensive medications had a higher prevalence of CAC in comparison to participants in the same group not on those drugs.
  • Participants who showed a steeper increase in BP had a higher prevalence of a CAC score of >100 HU (7.9% vs 10.1%, respectively; P<.001 for trend).
  • In a statistical model correcting for demographic characteristics, other CV risk factors and antihypertensives use, odds ratios were 1.44 (95%CI: 0.83-2.49) for moderate-stable, 1.86 (95%CI: 0.91-3.82) for moderate-increasing, 2.28 (95% CI: 1.24-4.18) for elevated-stable, and 3.70 (95% CI: 1.66-8.20) for elevated-increasing groups, with respect to the low stable group, in which an adjusted prevalence of 5.8% was seen for a CAC score >100 HU.
  • Odds rations did not change significantly with additional adjustment for baseline SBP and DBP, or SBP and DBP in year 25.
  • Overall similar patterns were seen when SBP and DBP trajectories were analysed separately.
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Five different trajectories in mid-BP were identified over a 25-year time span from young adulthood to middle age. These trajectories were differently associated with the presence of subclinical atherosclerosis later in middle age, with participants who exhibited elevated and less stable BP levels having the highest odds of having a CAC score of 100 HU or greater. Most of these participants had BP levels within the range of prehypertension. Thus, long-term patterns of change in BP, starting already in early adulthood , may provide additional information on the risk of developing subclinical atherosclerosis. The utility of specific BP trajectories in risk prediction for clinical CVD events require further exploration.
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