Visit-to-visit blood pressure variability and cardiovascular outcomes: a systematic review and dose-response meta-analysis

Clinical Snapshot

Key Findings

• P Value: P = 0.468 for comparison between EHR and non-EHR studies

• Effect Size: EHR studies HR 1.17, non-EHR studies HR 1.14

• Primary Outcome: Any cardiovascular disease outcome predicted by visit-to-visit blood pressure variability

• Nnt Or Sensitivity: 10% increased CVD risk at BPV threshold of SD ≥6.72 mmHg or CV ≥9.05%

• Confidence Interval: EHR: 95% CI 1.09-1.24; non-EHR: 95% CI 1.10-1.17

Clinical Application

High feasibility using existing EHR systems, though standardized protocols needed for implementation Highly relevant to Australian practice with widespread EHR adoption; could integrate with existing CVD risk assessment tools and RACGP guidelines for hypertension management Adults receiving routine blood pressure monitoring in primary and secondary care settings

Abstract

AIMS: Visit-to-visit blood pressure variability (VVV BPV) is a recognized risk factor for cardiovascular disease (CVD) that is underutilized in clinical practice. The reliability of electronic health record (EHR) data in estimating BPV and predicting CVD remains uncertain. This study compared BPV estimation methodologies using EHR vs. non-EHR data and examined dose-response associations with CVD. METHODS AND RESULTS: A systematic review and meta-analysis was conducted across five databases (MEDLINE, Scopus, EMBASE, CINAHL, and Web of Science) for studies published from January 2012 to August 2024. Studies assessing VVV BPV in adults and its association with CVD outcomes (e.g. myocardial infarction, stroke, heart failure, and cardiovascular mortality) were included. A dose-response meta-analysis (DRMA) evaluated BPV thresholds linked to increased CVD risk using standard deviation (SD) and coefficient of variation (CV). A total of 4926 studies were screened, 49 of which met the inclusion criteria. No consensus has emerged on BPV estimation methodologies, although non-EHR studies have followed stricter protocols. The meta-analysis showed that VVV BPV predicted any CVD outcome. Effect sizes were comparable between EHR [the hazard ratio (HR): 1.17, 95% confidence interval (CI): 1.09-1.24] and non-EHR (HR: 1.14, 95% CI: 1.10-1.17) studies (P-value = 0.468). A BPV threshold of SD 6.72 mmHg or CV 9.05% was linked to a 10% higher CVD risk. CONCLUSION: The EHR data reliably estimate BPV, yielding effect sizes similar to those of non-EHR sources. A non-linear dose-response relationship suggests that a higher BPV increases CVD risk. Visit-to-visit blood pressure variability needs to be incorporated into clinical practice, and further research is required to identify strategies to implement and scale up into routine workflow. Visit-to-visit blood pressure variability (VVV BPV) is capable of predicting CVD development in 6 years. However, its clinical use remains limited, and the reliability of electronic health records (EHR) in measuring BPV is uncertain. Having a standard deviation of VVV BPV ≥6.72 mmHg or a coefficient of variation of VVV BPV ≥9.05% mmHg is linked to a 10% higher CVD risk. Blood pressure variability estimates from EHR data were comparable to those from non-EHR studies, suggesting that EHR-based BPV assessment is reliable for CVD risk evaluation.

References

1. 1.Lukitasari, M., Jonnagaddala, J., Liaw, S. T., & Jalaludin, B. (2026). Visit-to-visit blood pressure variability and cardiovascular outcomes: a systematic review and dose-response meta-analysis. European Journal of Preventive Cardiology. https://doi.org/10.1093/eurjpc/zwaf546