Introduction : Equations can calculate pulse wave velocity (ePWV) from blood pressure values (BP) and age. The ePWV predicts cardiovascular events beyond carotid-femoral PWV. We aimed to evaluate the correlation between four different equations to calculate ePWV.

Methods: The ePWV was estimated utilizing mean BP (MBP) from office BP (MBP_OBP) or 24-hour ambulatory BP (MBP_24-hBP). We separated the whole sample into two groups: individuals with risk factors and healthy individuals. The e-PWV was calculated as follows:  

We calculated the concordance correlation coefficient (Pc) between e1-PWV_OBP vs e2-PWV_OBP, e1-PWV_24-hBP vs e2-PWV_24-hBP, and mean values of e1-PWV_OBP, e2-PWV_OBP, e1-PWV_24-hBP, and e2-PWV_24-hBP . The multilevel regression model determined how much the ePWVs are influenced by age and MBP values.

Results:  We analyzed data from 1541 individuals; 1374 ones with risk factors and 167 healthy ones. The values are presented for the entire sample, for risk-factor patients and for healthy individuals, respectively. The correlation between e1-PWV_OBP with e2-PWV_OBP and e1-PWV_24-hBP with e2-PWV_24-hBP was almost perfect. The Pc for e1-PWV_OBP vs e2-PWV_OBP was 0.996 (0.995-0.996), 0.996 (0.995-0.996), and 0.994 (0.992-0.995); furthermore, it was 0.994 (0.993-0.995), 0.994 (0.994-0.995), 0.987 (0.983-0.990) to the e1-PWV_24-hBP vs e2-PWV_24-hBP. There were no significant differences between mean values (m/s) for e1-PWV_OBP vs e2-PWV_OBP 8.98±1.9 vs 8.97±1.8; p=0.88, 9.14±1.8 vs 9.13±1.8; p=0.88, and 7.57±1.3 vs 7.65±1.3; p=0.5; mean values are also similar for e1-PWV_24-hBP vs e2-PWV_24-hBP, 8.36±1.7 vs 8.46±1.6; p=0.09, 8.50±1.7 vs 8.58±1.7; p=0.21 and 7.26±1.3 vs 7.39±1.2; p=0.34. The multiple linear regression showed that age, MBP, and age² predicted more than 99.5% of all four e-PWV.

Conclusion: Our data presents a nearly perfect correlation between the values of two equations to calculate the estimated PWV, whether utilizing office or ambulatory blood pressure.

This study is a secondary analysis of data obtained from two cross-sectional studies conducted at a specialized center in Brazil to diagnose and treat non-communicable diseases. In both studies, the inclusion criteria were adults aged 18 years and above, referred to undergo ambulatory blood pressure monitoring (ABPM) due to suspected non-treated or uncontrolled hypertension following initial blood pressure measurements by a physician. The combined databases included 1541 people. For the first database, we recruited participants between 28 January and 13 December 2013, and for the second database, between 23 January 2016 and 28 June 2019. 

Prior to being fitted with an AMBP device and assisted by a trained nurse, all participants signed a written consent form to partake in the research. Later, the nurse collected demographic and clinical data, including any previous reports of clinical cardiovascular disease (CVD), acute myocardial infarction, acute coronary syndrome, coronary or other arterial revascularization, stroke, transient ischemic attack, aortic aneurysm, peripheral artery disease and severe chronic kidney disease (CKD). All subjects had their BP, weight, height, and waist circumference measured and their body mass index (BMI) calculated.

Although the ePWV data from the Reference Values for Arterial Stiffness Collaboration originated from cohorts lacking established cardiovascular disease, cerebrovascular disease, or diabetes, we included diabetes, CVD, CKD, smokers, and obese individuals. This choice reflects a sample that more closely resembles what can be seen in everyday Brazilian physician appointments.

The study population was divided into two groups: healthy individuals and those with risk factors. Healthy individuals did not present any risk factors and a non-elevated BP (<140 and 90 mmHg). Conversely, the group with risk factors consisted of individuals with elevated BP (≥140 and-or 90 mmHg) or at least one risk factor, such as previous hypertension, dyslipidemia, diabetes, smoking, body obesity (BMI ≥ 30 kg/m2), or an increased waist circumference at risk (waist circumference > 102 cm in males and > 88 cm in females).

Blood pressure measurement and ambulatory blood pressure monitoring

During the data collection for both studies, office BP (OBP) measurements were conducted following recommended guidelines to ensure accurate pressure values. In the first database, a nurse performed seven consecutive BP measurements utilizing a Microlife device BP3BTOA (Onbo Electronic Co, Shenzhen, China). In the second database, a nurse assistant operated a Microlife device model BP3AC1-1PC (Onbo Electronic Co, Shenzhen, China). This device operated on Microlife Average Mode which takes three measurements in succession and calculates the average BP value. The assistant took two sets of three BP measurements sequentially.

All individuals registered twenty-four hours of ABPM using a Dyna-Mapa / Mobil-O-Graph-NG monitor (Cardios, São Paulo, Brazil), equipped with an appropriately-sized cuff on their non-dominant arm. The readings were taken every 20 minutes during the day and every 30 minutes during the night, here understood as the period between going to bed and waking up. We respected all recommended protocols strictly to ensure quality recordings.

Calculation of estimated pulse wave velocity

The ePWV was calculated using the equations derived from the Reference Values for Arterial Stiffness Collaboration, incorporating age and MBP as follows:  

MBP was also calculated as diastolic BP+ 0.4*(systolic BP/diastolic BP). Thus, the values of e1-PWV and e2-PWV were obtained for the total sample, as well as separately for the groups comprising healthy individuals and those with risk factors. We used MBP from OBP (MBP_OBP) to calculate e1-PWV_OBP and e2-PWV_OBP, and MBP of twenty hours BP average (MBP_24-hBP) to e1-PWV_24-hBP and e2-PWV_24-hBP.

The Human Research Ethics Committee of Sirio Libanes Hospital and Federal University of the Triângulo Mineiro, provided ethical approval for data collection under protocol numbers 08930813.0.0000.5461 (first database) and 61985316.9.0000.5154 (second database), respectively.