Relationship between sympatho-vagal balance and blood pressure variability: an analysis using simultaneous application of both 24-hour blood pressure monitoring and Holter ECG
D Lazzeroni, E Lazzaro, V Ziveri, M Bini, U Camaiora, S Geroldi, G Cacciola, A Guglielmetti, L Brambilla, L Moderato, F Gurgoglione, G Magnani, G Niccoli, A CabassiAbstract
Background
Autonomic dysfunction is a central pathophysiological mechanism in hypertension. Beyond its role in blood pressure regulation, sympatho-vagal imbalance is associated with adverse cardiovascular outcomes. However, the assessment of autonomic function in clinical practice relies on complex heart rate variability (HRV) analyses derived from 24-hour Holter ECG recordings. Whether 24-hour ambulatory blood pressure monitoring (ABPM), a widely available and standardized tool in hypertension management, may also capture signatures of autonomic dysregulation remains uncertain.
Aims
The primary aim of this study was to investigate the association between 24-hour blood pressure profiles and autonomic nervous system balance using simultaneous 24-hour ABPM and Holter ECG recordings. The secondary objective was to develop am ABPM-based predictive model of autonomic imbalance ("Dysautonomia ABPM Score”).
Methods
We performed a cross-sectional analysis of 499 consecutive subjects undergoing same-day 24-hour ABPM and Holter ECG monitoring (with time-frequency and non-linear analyses - figure A). ABPM features comprised 24- hour, daytime and nighttime mean values, coefficients of variation, weighted standard deviations, and dipping indices for systolic blood pressure (SBP), mean blood pressure (MBP), and heart rate (HR). First, unsupervised clustering based on comprehensive HRV metrics was used to identify autonomic phenotypes and define sympatho- vagal imbalance. Second, multivariable modelling and machine-learning techniques were employed to determine the ABPM variables most strongly associated with autonomic imbalance. The five highest-ranking ABPM features were selected to construct the Dysautonomia ABPM Score as a weighted linear combination of continuous variables, with weights proportional to their relative importance (B)
Results
Five ABPM parameters emerged as the strongest predictors of autonomic imbalance: daytime MBP coefficient of variation, MBP dipping, SBP dipping, HR dipping, and nighttime MBP. Individuals with sympatho-vagal imbalance exhibited significantly greater blood pressure variability and blunted nocturnal dipping of both blood pressure and heart rate. The Dysautonomia ABPM Score showed good discriminative ability for identifying autonomic imbalance (AUC 0.78), with sensitivity 0.74, specificity 0.71, and negative predictive value 0.86. Logistic regression analysis demonstrated a significant linear association between the score and the likelihood of dysautonomia (odds ratio 1.30 per unit increase; p=0.015), with a progressive increase in risk across score strata (C-D).
Conclusion
Autonomic imbalance is associated with a distinctive ABPM profile characterized by increased variability and impaired nocturnal dipping. A composite score derived from five routinely available ABPM parameters allows clinically interpretable estimation of sympatho-vagal imbalance without direct HRV analysis.figure