The accuracy of 8-hour ambulatory blood pressure monitoring, adjusted to seasons.
Sivan Zilka DarbianiMichael FrigerOrit BarrettAnna BasokTalya WolakPublished in: Journal of human hypertension (2022)
Ambulatory blood pressure monitoring (ABPM) is considered the most reliable and accurate measurement of blood pressure (BP). However, the use of ABPM has some limitations, which make it difficult to complete for the entire 24 h. We aimed to establish in which part of the day BP measurements are in highest correlation with full ABPM (over 24 h) results. We performed a retrospective cross-sectional study which included 3113 full ABPM. Each ABPM was divided into 6- and 8-hour segments, and mean BP in each time segment was calculated. Linear mix models for describing BP by BP in each time segment were performed. A total of 3113 ABPM measurements carried out on 2676 patients (mean age 57.78 ± 14.74) were included in the study. Linear mix models demonstrated significant association between mean systolic blood pressure (SBP) and diastolic blood pressure (DBP) in full ABPM, and SBP and DBP between 2-10 PM, respectively (SBP: β = 0.902, p < 0.001; DBP: β = 0.839, p < 0.001), adjusted for gender, age, season, and relevant interactions. This section had higher coefficient correlations than other sections which were examined. The study findings indicate high correlation between BP between 2-10 PM, and BP in full-ABPM, by each season. This time segment may be ideal for short-term BP monitoring as an initial screening test and for patients who are unable to complete full ABPM. However, since this time segment does not include nighttime hours, there is a risk of underdiagnosis of non-dipper.
Keyphrases
- blood pressure
- hypertensive patients
- heart rate
- end stage renal disease
- ejection fraction
- chronic kidney disease
- newly diagnosed
- peritoneal dialysis
- prognostic factors
- blood glucose
- air pollution
- magnetic resonance imaging
- type diabetes
- particulate matter
- left ventricular
- mass spectrometry
- mental health
- insulin resistance
- risk assessment
- weight loss
- skeletal muscle