Clinical Report: Visit-to-Visit Blood Pressure Variability and Cardiovascular Risk
Overview
This systematic review and meta-analysis evaluated visit-to-visit blood pressure variability (VVV BPV) as a predictor of cardiovascular disease (CVD) using data from electronic health records (EHR) and non-EHR sources. Findings demonstrate that VVV BPV independently predicts CVD risk, with comparable effect sizes between EHR and non-EHR data, and identified specific BPV thresholds linked to increased cardiovascular risk.
Background
High blood pressure is a well-established risk factor for cardiovascular disease, but recent research highlights the importance of visit-to-visit blood pressure variability (VVV BPV) as an independent predictor of cardiovascular outcomes. VVV BPV captures fluctuations in blood pressure over multiple clinical visits and has been associated with target organ damage and adverse cardiovascular events. Despite this, clinical use of VVV BPV remains limited, partly due to variability in measurement methods and uncertainty about the reliability of electronic health record data. This study addresses these gaps by systematically reviewing methodologies and quantifying the dose-response relationship between VVV BPV and cardiovascular risk.
Data Highlights
Data Source
Hazard Ratio (HR)
95% Confidence Interval (CI)
P-value
EHR
1.17
1.09–1.24
0.468
Non-EHR
1.14
1.10–1.17
BPV Thresholds Associated with 10% Increased CVD Risk:
Standard Deviation (SD): 6.72 mmHg
Coefficient of Variation (CV): 9.05%
Key Findings
Visit-to-visit blood pressure variability (VVV BPV) is an independent predictor of cardiovascular disease outcomes including myocardial infarction, stroke, heart failure, and cardiovascular mortality.
Effect sizes for the association between VVV BPV and CVD are similar when estimated from electronic health record (EHR) data (HR 1.17) and non-EHR data (HR 1.14), indicating reliability of EHR-based BPV assessment.
A BPV threshold of standard deviation ≥6.72 mmHg or coefficient of variation ≥9.05% is linked to a 10% increased risk of cardiovascular events.
There is no current consensus on the optimal BPV metric or classification method, with studies using various metrics such as SD, ARV, VIM, and CV, and differing follow-up durations.
Non-EHR studies tend to follow stricter BP measurement protocols compared to EHR data, which may have variable quality and measurement inconsistencies.
The dose-response relationship between VVV BPV and CVD risk is non-linear, with higher BPV associated with progressively increased cardiovascular risk.
Clinical Implications
Clinicians should consider incorporating visit-to-visit blood pressure variability into cardiovascular risk assessment, as it provides prognostic information beyond mean blood pressure values. Electronic health records offer a reliable and practical source for estimating BPV in routine care, facilitating identification of patients at elevated cardiovascular risk. Establishing standardized BPV measurement protocols and thresholds can improve risk stratification and guide targeted interventions.
Conclusion
Visit-to-visit blood pressure variability is a significant and independent predictor of cardiovascular disease, with reliable estimation achievable from electronic health records. Recognizing and integrating BPV into clinical practice could enhance cardiovascular risk prediction and prevention strategies.
References
Systematic Review and Dose-Response Meta-Analysis, 2024 -- Blood Pressure Variability Across Visits and Its Impact on Cardiovascular Events
