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Heart Rate Variability Has No Unique Meaning Without Heart Rate as Revealed by β-Adrenergic Blockade

Using a subject-specific heart-rate-dependent Master Curve framework in canine models, this study demonstrates that β-adrenergic blockade fundamentally alters the intrinsic heart rate–variability relationship rather than merely shifting the operating point, proving that heart rate variability lacks unique physiological meaning without accounting for concurrent heart rate.

Original authors: Andras Buzas, Leila Topal, Jenő A. Pintér, Mohhamed Aimen Salleh Abdullah, András Varró, András Dér

Published 2026-09-18

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CC BY 4.0

Original authors: Andras Buzas, Leila Topal, Jenő A. Pintér, Mohhamed Aimen Salleh Abdullah, András Varró, András Dér

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ⚕️ This is an AI-generated explanation of a preprint that has not been peer-reviewed. It is not medical advice. Do not make health decisions based on this content. Read full disclaimer

To understand the story of how our hearts beat, scientists have long relied on a concept called heart rate variability. This is not simply about how fast the heart beats, but about the tiny, natural differences in the time between each individual beat. A healthy heart does not tick like a metronome; it speeds up and slows down slightly with every breath and every shift in the body's needs. This fluctuation is a sign of a flexible, responsive nervous system. For decades, researchers have measured these fluctuations to gauge a person's health, stress levels, and risk of heart disease. The prevailing assumption has been that if the variability changes, the underlying control system has changed. However, there is a hidden complication: the speed of the heart itself changes the size of these fluctuations. Just as a fast-moving car covers more ground in a second than a slow one, a fast heart creates different patterns of timing than a slow one. This makes it difficult to tell if a change in variability is a sign of a new physiological state or just a mathematical side effect of the heart beating faster or slower.

A team of researchers at the University of Szeged in Hungary set out to solve this puzzle by testing whether heart rate variability has a unique meaning on its own, or if it is entirely dependent on the heart rate at that moment. They used a controlled experiment involving seven laboratory dogs, a species often chosen for such studies because their heart physiology closely mirrors that of humans. The dogs were trained to run on a treadmill, allowing the scientists to push their heart rates through a wide range of speeds, from rest to intense exercise. The researchers recorded the dogs' heart rhythms under normal conditions and then repeated the exercise after administering a common medication known as a beta-blocker. This drug works by blocking the signals from the nervous system that tell the heart to speed up, effectively lowering the heart rate and altering how the body controls it.

The core of the investigation was to see what happened to the relationship between heart rate and variability when the drug was introduced. If the old way of thinking were correct, the drug would simply move the heart to a different spot on an existing map, where a slower heart naturally has more variability. Instead, the researchers found something more profound. They constructed what they call a "Master Curve," a detailed map that shows exactly how much variability to expect at every single heart rate for each individual dog. When they compared the dogs' performance before and after the drug, they discovered that the entire map had shifted. The drug did not just move the heart to a new point on the curve; it dragged the whole curve downward.

This downward shift meant that for any given heart rate, the variability was significantly lower after the drug was given. In some cases, the variability dropped by more than half, even when the heart was beating at the same speed as it did before. The researchers observed this consistently across three of the dogs where the data was clear enough to analyze. The drug reduced the heart's ability to fluctuate, regardless of how fast it was beating. This finding challenges the idea that heart rate variability is a standalone measure of health. It suggests that the variability we see is not just a reflection of the nervous system's tone, but a dynamic response that changes its very nature when the system is chemically altered.

The study also looked at how the heart behaves during the transition from rest to exercise. Before the drug, as the dogs started to run, their heart rates rose and the variability dropped, which is normal. After the drug, the heart rate still rose, but the variability collapsed to a much lower level than before, even at the same speeds. The researchers used a mathematical approach to normalize the data, stripping away the influence of the heart rate itself to see the pure regulatory signal. This confirmed that the drug had fundamentally changed the system's behavior. The heart was no longer fluctuating with the same freedom it had before, even when the speed was identical.

This work helps explain why previous studies on heart rate variability have sometimes produced confusing or contradictory results. Some studies reported that beta-blockers increased variability, while others found a decrease. The researchers propose that both outcomes can be true at the same time, depending on where the heart rate lands on the curve. If the drug slows the heart down significantly, the natural increase in variability that comes with a slower heart might mask the fact that the system's overall flexibility has been reduced. Without a reference map that accounts for the heart rate, it is impossible to tell the difference between a simple shift in speed and a genuine change in the body's regulatory machinery.

The findings suggest that heart rate and heart rate variability are two different things that tell different parts of the story. Heart rate reflects the net result of the body's push and pull, the final speed of the engine. Variability, however, reflects the magnitude of the fluctuations around that speed, the dynamic adjustments the body makes moment to moment. When the drug blocked the sympathetic signals, it didn't just slow the engine; it dampened the vibrations and adjustments the engine made while running. This means that looking at variability alone, without knowing the heart rate, is like judging the stability of a car by looking at its speedometer without knowing if the road is smooth or rough.

The researchers concluded that to truly understand what heart rate variability means, it must always be interpreted in the context of the heart rate at that specific moment. They have provided a framework, the Master Curve, that allows scientists to distinguish between a heart simply moving to a new speed and a heart whose very nature of fluctuation has been altered. This distinction is crucial for understanding how medications, stress, or disease affect the heart. It moves the field away from treating variability as a single number and toward viewing it as a relationship that changes shape under different conditions. The study does not claim to have solved every mystery of heart regulation, but it offers a clearer lens through which to view the complex dance between the heart's speed and its rhythm.

Technical Summary: Heart Rate Variability Has No Unique Meaning Without Heart Rate as Revealed by β-Adrenergic Blockade

Problem Statement

Heart rate variability (HRV) is a standard non-invasive metric for assessing cardiovascular autonomic regulation. However, conventional HRV indices (such as RMSSD and SDNN) are mathematically and physiologically dependent on heart rate (HR). Because HR is a nonlinear transformation of the RR interval ( $HR \approx 1/RR$ ), identical absolute fluctuations in heart rate produce different RR interval fluctuations depending on the operating point.

This dependence creates a fundamental interpretational ambiguity: an observed change in HRV may result from either (i) a genuine alteration in physiological autonomic regulation, or (ii) a simple displacement of the cardiovascular system along an existing, unchanged HR–HRV relationship due to a change in heart rate. Conventional analysis, which typically compares measurements at single operating points without reconstructing the underlying HR–HRV relationship, cannot distinguish between these two mechanisms. This limitation is particularly evident in studies of $\beta$ -adrenergic blockade, where reported HRV changes are contradictory (increasing, decreasing, or remaining unchanged) depending on the accompanying heart rate shifts.

Methodology

The study utilized a controlled physiological perturbation model in a canine cohort to investigate the HR–HRV relationship under $\beta$ -adrenergic blockade.

Subjects and Protocol: Seven male laboratory canines underwent treadmill exercise protocols. Three animals provided ECG data of sufficient quality for quantitative analysis. The protocol included control conditions and a second session following the intravenous administration of metoprolol (1.5 mg/kg), a selective $\beta$ -adrenergic blocker.
Experimental Design: The exercise protocol involved continuous and interval running to drive heart rates across a wide physiological range (approx. 100–220 bpm). This allowed for the reconstruction of the HR–HRV relationship under both non-blocked and blocked conditions.
Data Analysis Framework:
- Master Curve Construction: The authors employed a subject-specific "Master Curve" framework based on a modified Poincaré plot. For consecutive RR intervals, the pairwise mean heart rate ( $mHR$ ) and successive difference ( $dRR$ ) were calculated. The Master Curve was defined as the root mean square of successive differences (RMSSD) within 1-bpm bins of $mHR$ , smoothed via spline fitting.
- Normalization: A heart-rate-normalized successive difference ( $nSD$ ) was calculated by dividing the actual $dRR$ by the expected value from the control Master Curve at that specific heart rate.
- Statistical Comparison: Repeated control measurements were used to establish within-subject reproducibility. The $\beta$ -blockade condition was compared against the subject-specific control Master Curve at matched heart rates. Statistical significance was assessed using the Wilcoxon signed-rank test on $\Delta \ln(RMSSD)$ values within predefined heart rate bins.
Theoretical Modeling: A stochastic integrate-and-fire model was extended to provide a mechanistic interpretation, distinguishing between the net chronotropic drive (determining HR) and the magnitude of dynamic regulatory fluctuations (determining HRV).

Key Results

Reproducibility of the Control Master Curve: Repeated control measurements in the same animals under non-blocked conditions yielded closely overlapping HR–RMSSD relationships. The within-subject deviations were substantially smaller than the changes observed after $\beta$ -blockade, confirming that the Master Curve represents a stable, subject-specific physiological reference.
Systematic Downward Displacement: $\beta$ $β$ -adrenergic blockade produced a consistent, systematic downward displacement of the Master Curve across all three analyzed animals. At matched heart rates, RMSSD values were significantly reduced relative to the control reference, with reductions ranging from 54.7% to 89.0% across the subjects.
- Statistical analysis confirmed these shifts were highly significant ( $p < 0.001$ ) across overlapping heart rate ranges (e.g., 110–190 bpm).
Normalized Variability: Heart-rate-normalized variability ( $\sigma_{nSD}$ and $LnSD$ ) decreased markedly after $\beta$ -blocker administration, particularly during exercise. This indicates that the reduction in variability was not merely a scaling effect of heart rate but a genuine reduction in the magnitude of regulatory fluctuations.
Model Validation: The proposed two-component model successfully explained the results. It posits that while heart rate reflects the net chronotropic drive ( $I_S - I_P$ ), HRV reflects the magnitude of fluctuations ( $\sqrt{(\alpha I_S)^2 + (\beta I_P)^2 + \dots}$ ). The model demonstrates that to maintain a specific heart rate under $\beta$ -blockade (reduced sympathetic drive), parasympathetic influence must also be reduced. This simultaneous reduction in both autonomic components leads to a lower magnitude of regulatory fluctuations, thereby lowering the expected HRV at that heart rate.

Key Contributions

Resolution of the Interpretation Paradox: The study provides a mechanistic explanation for the contradictory literature regarding $\beta$ -blockade and HRV. It demonstrates that $\beta$ -blockade simultaneously shifts the operating point (lowering HR) and displaces the entire HR–HRV relationship downward. The net observed HRV depends on the relative magnitude of these two opposing effects.
The Master Curve Framework: The paper establishes the heart-rate-dependent Master Curve as a necessary physiological reference. It argues that HRV cannot be interpreted as an absolute quantity but only as a relative measure defined by the underlying HR–HRV relationship.
Mechanistic Separation: The study distinguishes between "movement along a curve" (change in operating point) and "structural modification of the curve" (change in regulatory dynamics). It demonstrates that $\beta$ -blockade causes the latter, fundamentally altering the relationship between autonomic drive and cardiac variability.
Two-Component Model: The authors propose a theoretical framework separating the net chronotropic effect (determining HR) from the magnitude of dynamic regulatory fluctuations (determining HRV), explaining why identical heart rates can correspond to vastly different levels of variability.

Significance and Claims

The paper claims that Heart Rate Variability has no unique meaning without Heart Rate.

The authors assert that conventional HRV analysis is inherently ambiguous because it fails to account for the heart-rate-dependent nature of variability. Without a heart-rate-dependent reference (the Master Curve), it is impossible to determine whether an observed change in HRV reflects a genuine alteration in autonomic regulation or merely a shift to a different operating point on an existing curve.

The study concludes that $\beta$ -adrenergic blockade does not simply move the cardiovascular system along an unchanged HR–HRV relationship; it structurally modifies the relationship itself. Consequently, the physiological meaning of HRV emerges only when variability is interpreted relative to its heart-rate-dependent reference. This framework offers a more mechanistically grounded approach to interpreting HRV across pharmacological interventions, physiological transitions, and clinical conditions, moving beyond the limitations of isolated variability measures.