Baseline and Cumulative Blood Pressure in Predicting the Occurrence of Cardiovascular Events

Abstract

Background: Both baseline blood pressure (BP) and cumulative BP have been used to estimate cardiovascular event (CVE) risk of higher BP, but which one is more reliable for recommendation to routine clinical practice is unclear.Methods: In this prospective study, conducted in the Kailuan community of Tanshan City, China, a total of 95,702 participants free of CVEs at baseline (2006–2007) were included and followed up until 2017. Time-weighted cumulative BP that expresses the extent of cumulative BP exposure is defined as the sum of the mean of two consecutive systolic or diastolic BP times the interval between the two determinations, then normalized by the total follow-up duration. Incident CVEs during 2006–2017 were confirmed by review of medical records. We performed a competing risk regression analysis to assess CVE risk of the different durations of higher BP exposure. ROC analysis was performed to assess the predictive value of higher BP on CVE occurrence.Results: We found that when the risk of higher BP on CVE occurrence was estimated based on time-weighted cumulative BP, the hazard ratios (HRs) increased with the increase in duration of higher BP exposure in each of the four BP groups: <120/<80, 120–129/<80, 130–139/80–89, and ≥140/≥90 mmHg; this time trend also occurred across the four different BP groups, with the higher BP group exhibiting CVE risk earlier during the follow-up. These results were confirmed by the same analysis performed on participants without baseline hypertension. However, such reasonable time trends did not occur when a single baseline BP was used as the primary estimation. We also demonstrated that the predictive values of baseline systolic and diastolic BP that predict CVE occurrence were only 0.6–3.2 and 0.2–3.1% lower, respectively, than those of cumulative BP combined with baseline BP during follow-up.Conclusions: Baseline BP remains a useful indicator for predicting future occurrence of CVEs. Nevertheless, time-weighted cumulative BP could more reliably estimate the CVE risk of higher BP exposure than baseline BP.

Joint longitudinal and time‐to‐event modelling compared with standard Cox modelling in patients with type 2 diabetes with and without established cardiovascular disease: An analysis of the EXSCEL trial

“…All analyses were adjusted for age, sex, race, smoking status, history of hypertension or hyperlipidaemia, lipid-lowering or hypertension medication, duration of diabetes, and atrial fibrillation at baseline. eGFR, estimated glomerular filtration rate; HbA1c, glycated haemoglobin; HDL, high-density lipoprotein cholesterol; LDL, low-density lipoprotein cholesterol; TC, total cholesterol; SBP, systolic blood pressure; TG, triglycerides measurements of the risk factor is first calculated and then implemented as a covariate into a standard survival model [12][13][14] ; another is a two-stage approach in which first the slope (or progression per unit time) of the risk factor is estimated using its repeated measurements over time. This slope is usually estimated using a linear mixed effect model.…”

“…These attempts have ranged from cumulative approaches using weighted averages of risk factors to statistical methods estimating slopes of risk factors for survival modelling, all of which exhibit inherent limitations. [10][11][12][13][14] The UKPDS Risk Engine uses two to six repeated measurements for modifiable risk factors to estimate outcomes. 4 In recent years, a newly developed survival model class, "joint models for longitudinal and time-to-event data", has gained attention in the field of biomedicine for modelling and incorporating repeated risk factor measurement over time to better predict the risk of subsequent outcomes.…”

“…Various attempts have been made to overcome the limitation of single risk factor measurements in current RPTs by incorporating information from repeated measurements into risk equations. These attempts have ranged from cumulative approaches using weighted averages of risk factors to statistical methods estimating slopes of risk factors for survival modelling, all of which exhibit inherent limitations 10‐14 . The UKPDS Risk Engine uses two to six repeated measurements for modifiable risk factors to estimate outcomes 4 …”

Cumulative exposure to elevated blood pressure better predicts cardiovascular disease risk in rural Chinese adults

“…The Lifetime Risk Pooling Project also found that using long-term measures of cumulative BP instead of single measurements at baseline can modestly improve the ability of CVD risk prediction models to correctly classify individuals in terms of their risk for CVD ( 23 ). The Kailuan Study demonstrated that the predictive value of baseline BP for the occurrence of cardiovascular events was only slightly lower than that of the cumulative BP ( 11 ). Considering that single baseline BP is more accessible, baseline BP may still be a useful marker for CVD risk assessment.…”

“…It is widely acknowledged that CVD occurrence arises from the progressive load of risk factors on vascular and cardiac tissues over time ( 9 , 10 ). Although previous studies have discovered that cumulative BP, which incorporates both the intensity and duration of long-term BP recordings, has a more informative predictive value for CVD risk than baseline BP measurements in different populations, the generalization of this discovery remains somewhat limited because of the specific occupational population ( 11 ) and age of the study populations ( 12 , 13 ). Whether cumulative BP has incremental predictive value at the time of CVD risk assessment among rural populations, the key target audience in primary care with higher morbidity and mortality than other populations in China ( 14 , 15 ), remains uncertain.…”