Impact of 30- Versus 60-Second Time Intervals Between Automated Office Blood Pressure Measurements on Measured Blood Pressure

Hypertension ◽  
2021 ◽  
Vol 78 (5) ◽  
pp. 1502-1510
Author(s):  
Stephen P. Juraschek ◽  
Anthony M. Ishak ◽  
Kenneth J. Mukamal ◽  
Julia M. Wood ◽  
Timothy S. Anderson ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Clinical Practice ◽  
Linear Regression ◽  
Ambulatory Blood Pressure ◽  
The Other ◽  
Pressure Measurements ◽  
Time Intervals ◽  
Interaction Term ◽  
Automated Office Blood Pressure ◽  
The Relationship

Guidelines recommend 1 to 2 minutes between repeated, automated office-based blood pressure (AOBP) measures, which is a barrier to broader adoption. Patients from a single hypertension center underwent a 3-day evaluation that included a 24-hour ambulatory blood pressure (BP) monitor (ABPM) and one of two nonrandomized, unattended AOBP protocols. Half of the patients underwent 3 AOBP measurements separated by 30 seconds, and the other half underwent 3 BP measurements separated by 60 seconds. All measurements were compared with the average awake-time BP from ABPM and the first AOBP measurement. We used linear regression to assess whether the 30-second protocol was associated with individual or average AOBP measurements or awake-time ABPM and used an interaction term to determine whether interval modified the relationship between AOBP measurements (individual and mean) with awake-time ABPM. Among 102 patients (mean age, 59.2±16.2 years; 64% women; 24% Black), the average awake-time BP was 132.5±15.6/77.7±12.2 mm Hg among those who underwent the 60-second protocol and 128.6±13.6/76.5±12.5 mm Hg for the 30-second protocol. Mean systolic/diastolic BP was lower with the second and third AOBP measurement by −0.5/−1.7 mm Hg and −1.0/−2.3 mm Hg for the 60-second protocol versus −0.8/−2.0 mm Hg and −0.7/−2.7 mm Hg for the 30-second protocol; protocol did not significantly modify these differences. Differences between AOBP measurements (first, second, or third) and awake-time ABPM were nearly identical across protocols. In conclusion, a 30-second interval between AOBP measurements was as accurate and reliable as a 60-second interval. These findings support shorter time intervals between BP measurements, which would make AOBP more feasible in clinical practice.

scholarly journals Development of equations for converting random-zero to automated oscillometric blood pressure values

2019 ◽  
Vol 4 ◽  
pp. 146
Author(s):  
Li Yan ◽  
Xiaoxiao Wen ◽  
Alan R. Dyer ◽  
Haiyan Chen ◽  
Long Zhou ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Linear Regression ◽  
Blood Pressure Measurement ◽  
The Other ◽  
Pressure Measurements ◽  
Age And Gender ◽  
Several Variables ◽  
Oscillometric Device ◽  
And Gender ◽  
Over Time

Background: This study aimed to collect data to compare blood pressure values between random-zero sphygmomanometers and automated oscillometric devices and generate equations to convert blood pressure values from one device to the other. Methods: Omron HEM-907, a widely used automated oscillometric device in many epidemiologic surveys and cohort studies, was compared here with random-zero sphygmomanometers. In total, 201 participants aged 40-79 years (37% men) were enrolled and randomly assigned to one of two groups, with blood pressure measurement first taken by automated oscillometric devices or by random-zero sphygmomanometers. The study design enabled comparisons of blood pressure values between random-zero sphygmomanometers and two modes of this automated oscillometric device (automated and manual), and assessment of effects of measurement order on blood pressure values. Results: Among all participants, mean blood pressure levels were the lowest when measured with random-zero sphygmomanometers compared with both modes of automated oscillometric devices. Several variables, including age and gender, were found to contribute to the blood pressure differences between random-zero sphygmomanometers and automated oscillometric devices. Equations were developed using multiple linear regression after taking those variables into account to convert blood pressure values by random-zero sphygmomanometers to automated oscillometric devices. Conclusions: Equations developed in this study could be used to compare blood pressure values between epidemiologic and clinical studies or identify shift of blood pressure distribution over time using different devices for blood pressure measurements.

Why Use Automated Office Blood Pressure Measurements in Clinical Practice?

2011 ◽  
Vol 18 (3) ◽  
pp. 89-91 ◽  
Author(s):  
Emmanuel A. Andreadis ◽  
Epameinondas T. Angelopoulos ◽  
Gerasimos D. Agaliotis ◽  
Athanasios P. Tsakanikas ◽  
George P. Mousoulis
Keyword(s):  
Blood Pressure ◽  
Clinical Practice ◽  
Office Blood Pressure ◽  
Pressure Measurements ◽  
Automated Office Blood Pressure

scholarly journals Development of equations for converting random-zero to automated oscillometric blood pressure values

2019 ◽  
Author(s):  
Li Yan ◽  
Xiaoxiao Wen ◽  
Alan R Dyer ◽  
Haiyan Chen ◽  
Long Zhou ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Linear Regression ◽  
Blood Pressure Measurement ◽  
The Other ◽  
Pressure Measurements ◽  
Age And Gender ◽  
Several Variables ◽  
Oscillometric Device ◽  
And Gender ◽  
Over Time

AbstractObjectiveThis study aimed to collect data to compare blood pressure values between random-zero sphygmomanometers and automated oscillometric devices and generate equations to convert blood pressure values from one device to the other.MethodsOmron HEM-907, a widely used automated oscillometric device in many epidemiologic surveys and cohort studies, was compared here with random-zero sphygmomanometers. Two hundred and one participants aged 40-79 years (37% men) were enrolled and randomly assigned to one of two groups with blood pressure measurement first taken by automated oscillometric devices or by random-zero sphygmomanometers. The study design enabled comparisons of blood pressure values between random-zero sphygmomanometers and two modes of this automated oscillometric device – automated and manual, and assessment of effects of measurement order on blood pressure values.ResultsAmong all participants, mean blood pressure levels were lowest when measured with random-zero sphygmomanometers compared with both modes of automated oscillometric devices. Several variables, including age and gender, were found to contribute to the blood pressure differences between random-zero sphygmomanometers and automated oscillometric devices. Equations were developed using multiple linear regression after taking those variables into account to convert blood pressure values by random-zero sphygmomanometers to automated oscillometric devices.ConclusionEquations developed in this study could be used to compare blood pressure values between epidemiologic and clinical studies or identify shift of blood pressure distribution over time using different devices for blood pressure measurements.

Haematocrit: Relationships with Blood Lipids, Blood Pressure and other Cardiovascular Risk Factors

1994 ◽  
Vol 72 (01) ◽  
pp. 058-064 ◽  
Author(s):  
Goya Wannamethee ◽  
A Gerald Shaper
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Blood Pressure ◽  
Body Mass Index ◽  
Cardiovascular Risk ◽  
Cardiovascular Risk Factors ◽  
Alcohol Intake ◽  
Blood Lipids ◽  
The Other ◽  
The Relationship

SummaryThe relationship between haematocrit and cardiovascular risk factors, particularly blood pressure and blood lipids, has been examined in detail in a large prospective study of 7735 middle-aged men drawn from general practices in 24 British towns. The analyses are restricted to the 5494 men free of any evidence of ischaemic heart disease at screening.Smoking, body mass index, physical activity, alcohol intake and lung function (FEV1) were factors strongly associated with haematocrit levels independent of each other. Age showed a significant but small independent association with haematocrit. Non-manual workers had slightly higher haematocrit levels than manual workers; this difference increased considerably and became significant after adjustment for the other risk factors. Diabetics showed significantly lower levels of haematocrit than non-diabetics. In the univariate analysis, haematocrit was significantly associated with total serum protein (r = 0*18), cholesterol (r = 0.16), triglyceride (r = 0.15), diastolic blood pressure (r = 0.17) and heart rate (r = 0.14); all at p <0.0001. A weaker but significant association was seen with systolic blood pressure (r = 0.09, p <0.001). These relationships remained significant even after adjustment for age, smoking, body mass index, physical activity, alcohol intake, lung function, presence of diabetes, social class and for each of the other biological variables; the relationship with systolic blood pressure was considerably weakened. No association was seen with blood glucose and HDL-cholesterol. This study has shown significant associations between several lifestyle characteristics and the haematocrit and supports the findings of a significant relationship between the haematocrit and blood lipids and blood pressure. It emphasises the role of the haematocrit in assessing the risk of ischaemic heart disease and stroke in individuals, and the need to take haematocrit levels into account in determining the importance of other cardiovascular risk factors.

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