Key result
Higher BP variability is linked to increased CV mortality and end-organ damage despite mean BP.
Why the study?
Hypertension is traditionally defined by mean blood pressure, but blood pressure variability has emerged as a contributor to multisystem risk and vascular injury.
This review highlights blood pressure variability as a dynamic marker of multisystem risk and explores the potential of AI-based devices for continuous monitoring and patient-specific risk stratification.
BPV may flag added CV risk beyond mean BP; challenges mean-BP-centric views but leaves open whether targeting variability improves outcomes.
Hypertension has been traditionally known to be highlighted by mean blood pressure; however, emerging evidence exhibits that blood pressure variability (BPV), including short-term, day-to-day, and visit-to-visit fluctuations can have an implication across multiple body systems. Elevated BPV reflects repetitive hemodynamic stress, affecting the physiologic hemostasis contributing to vascular injury and end organ damage. This narrative review is a compilation of recent evidence on the prognostic value of BPV, explained by pathophysiology, various devices with its measurement approaches, and, essentially, the clinical implication of BPV and the use of such devices utilizing artificial intelligence. A comprehensive literature search across PubMed, Cochrane Library, Scopus, and Web of Science were conducted, focusing on observational studies, cohorts, randomized trials, and meta-analyses. Higher BPV has been associated with an increased risk of cardiovascular mortality, stroke, coronary events, and heart failure, the progression of chronic kidney disease, cognitive decline, and preeclampsia, among other end organ damage, despite mean blood pressure. The various pathophysiologic mechanisms include autonomic dysregulation, arterial stiffness, endothelial dysfunction, circadian rhythm alteration, and systemic inflammation, which result in vascular remodeling and multisystem damage. Antihypertensive medications such as calcium channel blockers and renin–angiotensin–aldosterone system inhibitors seem to reduce BPV; randomized trials have not specifically investigated their BPV-reducing effects. The aim of this review is to highlight that BPV is a dynamic marker of multisystem risk, and question how various AI-based devices can aid continuous BPV monitoring and patient specific risk stratification.
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Pugalenthi et al. (2026) conducted a review in Hypertension. Blood pressure variability (BPV) was evaluated. Higher blood pressure variability is associated with an increased risk of cardiovascular mortality, stroke, coronary events, and heart failure, independent of mean blood pressure.
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