To review methodologies for estimating visit-to-visit blood pressure variability (VVV BPV) and its association with cardiovascular disease (CVD) outcomes, specifically comparing the methodologies of studies using electronic health record (EHR) data versus those using non-EHR data.
Key Findings:
49 studies met inclusion criteria from 4926 screened.
No consensus on BPV estimation methodologies; non-EHR studies followed stricter protocols.
VVV BPV predicted any CVD outcome with comparable effect sizes between EHR (HR: 1.17, 95% CI: 1.09–1.24) and non-EHR (HR: 1.14, 95% CI: 1.10–1.17) studies.
A BPV threshold of SD 6.72 mmHg or CV 9.05% linked to a 10% higher CVD risk.
EHR data reliably estimate BPV, yielding effect sizes similar to non-EHR sources.
Interpretation:
Higher VVV BPV is associated with increased CVD risk, indicating a critical need for its incorporation into clinical practice to enhance patient outcomes.
Limitations:
Variable quality of EHR data and inconsistencies in data acquisition methods may impact the reliability of findings.
Lack of consensus on BPV metrics and classification for operational definitions complicates the interpretation of results.
Conclusion:
Visit-to-visit blood pressure variability is a significant predictor of CVD development, necessitating its integration into clinical workflows and further research on effective implementation strategies.
Federal prosecutors allege that a Florida physician and research staff fabricated clinical trial records that were submitted into database systems used to evaluate investigational drugs.
