The World Health Organization (WHO) describes stroke as a pandemic. From 1990 to 2010 the world burden of stroke increased significantly with regard to the recent increase in the numbers of patients, of deaths (20% increase), and of disability-adjusted life years (DALY; 16% increase) (Krishnamurthi et al., 2013). According to the WHO, the estimated incidence of stroke events in Europe is likely to increase from 1.1 million per year in 2000 to more than 1.5 million per year in 2025 in relation to demographic changes (Truelsen et al., 2006). Worldwide, the number of deaths due to stroke was 4.4 million in 1990 (Murray and Lopez, 1997). This prevalence is underestimated as many strokes do not exhibit clinical evidence and remain unnoticed; indeed, systematic autopsies of large populations disclosed a 12.9% pathological evidence of cerebral infarction, although any clinical sign of stroke had ever been experienced by these patients who died from other diseases (Shinkawa et al., 1995). Many studies also reported previous silent strokes in those patients investigated for acute stroke as in the Framingham (Kase et al., 1989) and the Copenhagen (Jorgensen et al., 1994) cohorts. In the Veterans Affairs Cooperative Study, 14.7% of cerebral scans showed previous silent brain infarctions (Hénon et al., 1995). This percentage reached 38.3% in the SEPIVAC survey (Ricci et al., 1993).

Death from stroke is not the only societal drama as 40% of survivors demonstrate severe sequelae, and 30% fall in depression in the year following a stroke. Dementia is a frequent evolution. In developed countries, each case from stroke occurrence to death costs almost $80,000 US or €70,000, with an annual amount of more than $100 billion US for the United States only (Feigin et al., 2014); The incidence may be largely under evaluated as there is approximately 15 silent stroke for one clinically patent stroke (Leary and Saver, 2003).

Autonomic nervous system activity and traditional risk factors are strongly related as ANS imbalance contributes to the creation of a pre-pathological milieu of composite risk factors, such as hypertension, diabetes or atrial fibrillation and alterations of endothelial homeostasis in favor of pro-thrombotic/proinflammatory state, eventually leading to increased risk of stroke (Saeed et al., 2005; Bäck et al., 2019; Carandina et al., 2021). Thus ANS monitoring is of importance in stroke prevention focusing on the imbalance characterized by a decrease in parasympathetic activity and a concurrent increase in sympathetic activity.

As ANS monitoring is most often based on mathematical analysis of successive ECG sinusal intervals (RR intervals), those which are neuro-controlled, subjects suffering from arrhythmias are often excluded from the studies. As a matter of fact, antiarrhythmic drugs alter significantly the HRV measurements, according to their class (Zuanetti et al., 1991).

Autonomic nervous system parasympathetic outflow is a recognized predictor of longevity in centenarians, ANS decrease with aging being considered as a natural decrease of allostatic systems (Hernández-Vicente et al., 2020). In the general population, three longitudinal studies underlined the predictive value of decreased ANS activity for death, mainly cardiovascular, namely the ARIC (Atherosclerosis Risk in Communities), the ZUTPHEN and the FRAMINGHAM studies (Tsuji et al., 1996; Dekker et al., 1997, 2000). The same predictive value was attributed to a decrease in ANS after stroke of myocardial infarction (Kleiger et al., 1987). The ultracentenarians over 100 years of age have significantly higher parasympathetic activity than the elderly subjects from 81 to 100 years of age and the parasympathetic predominance may be the neuroautonomic feature that helps to protect ultra-centenarians against cardiovascular disease (Piccirillo et al., 1998). In animal models, increased sympathetic activity and decreased parasympathetic activity (Vanoli et al., 1991) are associated with a higher risk of sudden cardiac death (Kleiger et al., 1987; Bigger et al., 1993; Tsuji et al., 1996; Chen and Tan, 2007). Specifically, reduced 24-h HRV is independently associated with increased risk of myocardial infarction, congestive heart failure, death from cardiovascular disease, and total mortality (Kleiger et al., 1987; Bigger et al., 1993; Tsuji et al., 1996). Experimental evidence also suggests that the autonomic nervous system is implicated in the development of vascular atheroma and occlusion (Hamaad et al., 2004). On the other side, cholinergic stimulation protects endothelium by blocking endothelium cells activation and leukocyte recruitment during inflammation (Saeed et al., 2005). This opens a promising area for future research in the effects of common non-cardioactive drugs (Nicolini et al., 2012). In the cardiovascular health study (CHS), greater total leisure-time activity, walking distance, and walking pace were each associated with more favorable HRV indices, supporting cardiovascular benefits (Soares-Miranda et al., 2014).

Stress is the response of the organism to the interoceptive and exteroceptive changes, i.e., to any biological, psychological, or environmental context change in daily life. The stress is most often beneficial but may become deleterious if solicited intensively or for a too long period of time. The regulation from ANS is immediate and even adapts to the perceived risk as well as to the perspective of future risks. This may even alter transgenerational epigenetical modulation of stress (Babenko et al., 2015).

Among the many adaptative changes, the stress mechanism activates the sympathetic nervous activity (ANS), with a mirrored decreased in parasympathetic nervous activity (PNS). This resultant prevailing sympathetic activity sets a multitude of negative side effects, particularly at the vascular level. There is also a biological cost to activate the biological regeneration through mechanisms including the sleep, vagal tone and tissue regeneration (Canini, 2019).

Stress response is traditionally considered to represent the fly or fight response to a significant external variation condition. Today, stress frequently deals with more common changes, such as hunger, thirst, temperature changes, walking, sleeping, speaking, eating, meeting people, listening noise or music, getting up or lying. All these actions require an adaptative answer of ANS to keep the biological equilibrium in spite of an unusual context. In that view, the stress response is present at many occasions and accompanies also many classical cardiovascular risk factors.

Several methods are available to measure ANS activity. Invasive methods include biological catecholamine measurements or direct nerve sympathetic activity measurement using microneurography (Wallin and Sundlöf, 1979). Although providing precise measures, these techniques do not measure parasympathetic activity and cannot be applied to large populations.

Fortunately, ANS activity can be also non-invasively investigated giving access to both the sympathetic and parasympathetic arms of ANS activity. The importance of heart rate behavior in response to exercise is illustrated by a predictive value for sudden death (Jouven et al., 2005). Even the notion of a relationship between longevity and heart rate as a simple measurement of ANS activity, has been raised (Jensen, 2019). Quantification of heart rate variability (HRV) provides more precise measurements than simple heart rate values. REF any change in ANS activity is reflected by HRV due to the very rich ANS innervation of the heart. In that view, the heart is an open window on the neurological regulatory ANS activity. The lack of variability of RR intervals means that there is no ANS activity to regulate heart rate, and often, no ANS activity at all. It means neuronal inactivity. This total lack of variability can be observed when a cerebral death has occurred in ICU, where heart rate becomes absolutely regular (Rapenne et al., 2000).

Analysis of heart rate changes allows quantifying ANS activity. Rapid vanishing changes in RR interval length are induced by the parasympathetic drive, due to the rapid elimination of its neurohormone, acetylcholine. These variations are called high frequency (HF) variations and thus represent the parasympathetic drive. Slower changes of RR intervals length are due to slower changes in catecholamine concentrations and are thus called low frequency (LF), they roughly represent the sympathetic drive which is while this LF frequency band also represents some parasympathetic activity (Brown et al., 1993; Lorenzi-Filho et al., 1999; Pichot et al., 1999).

Only the normal RR intervals are taken into account in HRV measurements, as their length is modulated by the autonomic nervous system, which is not the case for intervals linked to ectopic beats which are due to local reentry or local enhanced automaticity. The HRV evaluation implies first a reading of Holter recordings in order to label beats as normal (N), ventricular ectopic beats (V or VE), or supraventricular ectopic beats (S or SVE). This reading also gives access to the length of each normal to normal (NN) beat. HRV is then based on mathematical calculations on these consecutive NN intervals. Once the set of RR (NN) intervals is established, two classical mathematical approach to quantify the autonomic nervous system activity which modulate the NN length variations, namely the temporal and the frequential approaches (Task Force, 1996).

The temporal approach is based on simple standard deviations (SD) of these NN intervals, usually calculated on 24-h periods. The way the SD will be calculated will give several results. The first result is global autonomic activity calculating the SD of all RR (NN) intervals of the set, and it is called SDNN. Then, to take into account fast RR length variations from one RR interval from the previous, it is calculated the SD of the root mean square of the mean of the successive differences of consecutive RR (NN) intervals squared, giving a representation of the parasympathetic activity. It is called RMSSD. Referring to the sympathetic activity, the SD of RR (NN) intervals are first calculated on consecutive 5 min intervals, the mean of these SD is thus appropriate to reflect sympathetic HRV changes which are observed on longer periods than parasympathetic ones. It is called SDNNIDX. One last measurement which differs slightly from these SD and means, is the percentage of RR intervals differing for more than 50 ms from the previous one. It is a parasympathetic parameter. It is called PNN50.

The second set of mathematical approach is based on the analysis of cyclical variations of RR (NN) as a sinusoidal signal. This approach is most often performed through a Fourier Transform (FT), which identifies regular repetitive patterns that can be described as sinusoids. This is a general law that is applied to many periodic signals including physiological signals. It is a new mathematical space where signal modulations can be characterized by a frequency and amplitude modulation. Entering the Fourier space allows thus to quantify repetitive fast changes by fast sinusoids and repetitive slow changes by slow sinusoids. In RR length modulation physiology, the slow and fast changes are included in bounds calculated using pharmacological blocking of sympathetic and parasympathetic activities (Pomeranz et al., 1985). These bounds are 0.04 – 0.15 Hz for the low frequencies (LF) representing the sympathetic activity and 0.15 – 0.40 Hz for the high frequencies (HF) representing the parasympathetic activity. This gives also the possibility to calculate a ratio between the sympathetic activity and the parasympathetic activity, the ratio LF/HF, which represents the sympathetic predominance.

Indeed, while the representativity of parasympathetic activity by the HF band of Fourier transform is widely accepted, the representativity of sympathetic activity by the LF component is slightly more questionable since the LF band represents both parasympathetic and sympathetic activities, and does not correlate well with the MSNA activity, this latter being the reference value for sympathetic activity (Saul et al., 1990). The values should also be assessed against total spectral power (Ptot). HF and LF values are thus better assessed when compared to each other, and their ratio LF/HF is a good indicator of ANS imbalance (Pagani et al., 1984), when used in normalized units as well, although this last index remains questioned (Billman, 2013). There is also significant respiratory influences on HRV that affect not only the HF component, but could affect LF as well, depending on the breathing pattern (Brown et al., 1993; Lorenzi-Filho et al., 1999).

These temporal and frequential methods share a limitation in averaging ANS activity on the period analyzed, thus missing transitions in ANS modulation. A first answer is to analyze separately diurnal and nocturnal values. The nocturnal values are of particular interest as they are independent of most environmental stimuli and thus better represent the ability of ANS to activate the parasympathetic drive.

It is also possible to pick up transitional values of ANS activity using a specific frequential measurement based on wavelets analysis (Pichot et al., 1999, 2016). This allows to go beyond the limitation of stationarity needed for temporal and frequential methods. Stationarity is rather difficult to obtain but this status benefits from a general tolerance. Wavelet analysis is of particular interest in experimental conditions such as drug assessment, autonomic answer to physical exercise, or stress evaluation under any environmental changes. The wavelet transform (WT) presents other advantages over the FT. First, the shape of the analyzing wavelet can be freely chosen, and thus is not limited to the sinusoid shape of the Fourier Transform, owing to more accurate measurements. Specific analyzing shapes of interest for EKG were published by Daubechies (1992). The second advantage of WT is the localization of the fitting between the analyzing shape and the analyzed signal, allowed by displacing the analyzing signal along the analyzed signal and thus identifying precisely the time where the change occurs (Figure 1).

Beyond these so-called linear approach of HRV, representing its complexity, non-linear approach gained a great interest (Acharya et al., 2004; Stein et al., 2005; Maestri et al., 2007). In fact, RR interval series demonstrating identical statistical linear properties (mean and SD) and power spectra can differ profoundly in terms of the “fine texture” of the rhythm (Nicolini et al., 2012).

These variables are the Poincaré plot (Kamen et al., 1996), the fractal analysis (Peng et al., 1995), the entropy, heart rate turbulence (Bauer et al., 2008), deceleration and acceleration capacities (Bauer et al., 2006), empirical mode decomposition (Balocchi et al., 2004), largest Lyapunov exponent (Wolf et al., 1985), symbolic dynamics (Porta et al., 2001), and empirical mode decomposition (Balocchi et al., 2004), among others. The readers interested may find some details in a dedicated paper from Pichot (Pichot et al., 2016). Unfortunately, these promising variables were seldom chosen due to the lack of available software before the publication of Pichot’s software, HRVanalysis (Pichot et al., 2016). Fortunately, we hope that past data may be reanalyzed using this software. New biomarkers gain a significant place as predictors of stroke as they did in postmyocardial infarction (Stein et al., 2005). Data about HRV in the elderly may be corrected to take into account ECG fragmentation, which may artificially increase variability in that population (Costa et al., 2017).

Spontaneous baroreflex (BRS) measurement is another non-invasive approach to ANS measurement. Smooth muscle in arteries, arterioles, and veins and pericytes in capillaries receive a rich autonomic innervation. The baroreflex measures the parasympathetic response to variations in blood pressure. The test is performed by analyzing the increase or decrease in blood pressure and the corresponding lengthening or shortening response of the following interval RR. This measurement is made possible without pharmaceutical administration due the spontaneous permanent change in systolic blood pressure (SBP) from one beat to the following. To do that, the ECG and blood pressure have to be measured simultaneously to belong to the same time frame. The non-invasive blood pressure is measured continuously non-invasively via fast digital balloon counter pressure (Peňáz, 1973). The interest in baroreflex measurement comes from its strong representation of parasympathetic activity as the measure checks at the same time the quality of the sensor of blood pressure located in the carotid body, and the ANS neuronal complete circuitry going from the sensor to the target, here from the carotid to the brainstem then to the heart (Seravalle et al., 2015). Arterial baroreceptors in the carotid sinuses and aortic arch sense pressure changes, and in response to an increase blood pressure they inhibit efferent sympathetic neurons leading to vasodilatation, and they influence the heart rate. They also decrease renin by limiting sympathetic renal outflow (Kaufmann et al., 2020).

Another approach is to evaluate blood pressure variability (BPV). As for HRV, high frequency and low frequency are very different. High frequency means fine adaptation, pulse to pulse, while low frequency means late adaptation trying to catch up the physiological target, but so late that an excessive adaptation is the rule. What is not continuously and finely adjusted will need later stronger corrections, hence the difference meaning of high frequency signing a permanent fine adaptation and low frequency signing a late adjustment.

Arterial stiffness is another approach of ANS activity. This is used on short term variations as a marker of sleep apnea by measuring the pulse transit time (Contal et al., 2013). On the long term, parameters of arterial stiffness, pulse pressure and its other components, are strong predictors of mortality and cardiovascular outcomes (Gavish et al., 2022). Arterial stiffness takes into account vascular aging and thus endothelium health which depends on ANS activity (Abboud, 2010).

Normal values for ANS measurements are scarce. Guidelines for measurement have been published, as well as some normal values (Shaffer and Ginsberg, 2017), of which nocturnal values are given from the Hypnolaus study (Berger et al., 2022). Various aspects of HRV were explored as short term values (Lee et al., 2018), values in women (Kesek et al., 2009), values in periodic leg movements (Sforza et al., 2005), in patients suffering OSA (Qin et al., 2021), and in those presenting with metabolic syndrome (Assoumou et al., 2012a).

Free software are today available, making possible calculation of HRV from almost any recording source with any available method (Pichot et al., 2016). This illustrates an emerging facilitation of the implication of ANS in cardiovascular risk assessment.

While today’s prediction of stroke risk relies on classical cardiovascular risk factors, adding autonomic biomarkers may significantly increase the prediction of stroke (Bodapati et al., 2017). The association of two HRV parameters significantly increased the predictive power from 0.61 for the CHS-score (Cardiovascular Health Study clinical stroke risk score, Stein et al., 2008) alone to up to 0.68 (p = 0.02). The implication of ANS unbalance in stroke occurrence in the general population is supported by the Framingham cohort. Specifically, a reduced 2-h HRV was independently associated with increased risk of myocardial infarction, congestive heart failure, death from cardiac and cerebral diseases, and total mortality (Kleiger et al., 1987; Bigger et al., 1993; Tsuji et al., 1996). Due to its short-term and long-term neurological interaction with vessels, ANS activity presents a strong relationship with cardiovascular diseases, including stroke. Since many risk factors are shared for MI and for stroke occurrences, the prediction brought through ANS imbalance predicts both vascular diseases as established in the Framingham cohort (Kleiger et al., 1987; Bigger et al., 1993; Tsuji et al., 1996). It should be emphasized that the term cardiovascular disease may be misleading as it focuses our attention on the heart disease while it downplays the cerebrovascular disease. Both terms should be associated to avoid this shadowing effect.

This makes of ANS imbalance a key factor of stroke occurrence. In The Framingham Heart Study, a 1 SD decrement in autonomic activity, as assessed by the biomarker HVR low-frequency power (LF, natural log transformed), was associated with 1.70 times greater hazard for all-cause mortality, including stroke. It is of note that the Holter recordings were obtained from 2-h diurnal recordings during routine examination in a subset of 1082 subjects (Tsuji et al., 1994). In a stepwise analysis including classical cardiovascular risk factors, SNA variable was the first to enter the model. The authors concluded that the estimation of HRV by ambulatory monitoring offers prognostic information beyond that provided by the evaluation of traditional risk factors (Tsuji et al., 1994). Thus HRV appears as a general cardiovascular (CV) risk marker, and that an individual has the age of his/her ANS activity (Tsuji et al., 1994). Recently, the Framingham Offspring cohort third addressed more specifically dementia and stroke prediction. Dementia was predicted by SDNN [HR (Hazard Ratio) per 1 SD, 0.61] and RMSSD (HR per 1 SD, 0.34). High resting heart rate was associated with increased stroke risk (HR per 10 bpm, 1.18).

Normal SDNN values were associated with lower stroke risk in men but not in women (HR per 1 SD, 0.46) (Weinstein et al., 2021). Nighttime HRV parameters are important as they are strong predictors of stroke in the Copenhagen Holter study, where eighty-one percent of the stroke occurred in the subjects with the lower half of nighttime SDNN (less than 38 ms; HR, 4.31) (Binici et al., 2011).

There are also epidemiologic evidences of ANS implication in clinically silent stroke which was found a predictor of patent stroke (AHA/ASA Scientific Statement). This can go from silent brain infarcts (SBI), white matter hyperintensities, or microbleeds (Smith et al., 2017), as established by the historical Hisayama study (Shinkawa et al., 1995). Age was a prominent factor, since in this cohort the percentage of subjects with silent infarcts increased with advancing age, from 4.4% in ages 40–49 to 19.3% in more than 80-year old humans. Other main established factors were hypertension, AF and diabetes mellitus. A recent meta-analysis including 14764 subjects underlined a 2.94 relative risk of clinically patent stroke following SBI, after adjustment for CV risk factors (Gupta et al., 2016).

Antiarrhythmic drugs alter significantly HRV, making HRV measurements different from basal values in these subjects (Zuanetti et al., 1991). However, this determines the exclusion of many subjects in the cohort studies as this may exclude the subjects with the most severe risk, determining some bias.

A study focusing on brain lacunae in elderly hypertensive patients underlined the lacunae to be rather related to ANS activity impairment than specifically to hypertension. As a matter of fact, while nocturnal dippers demonstrated an appropriate autonomic activity, extreme dippers, defined as having more than 20% nocturnal reduction of compared to their daily value, exhibited a markedly suppressed nervous activity during sleep. An extreme dip with a ratio night/day ≤0.8 was associated to lacunar events, and there was a correlation between the decrease of the HF nocturnal value as well as of the increase LF/HF ratio and the asleep/awake SBP ratio (Kario et al., 1997). In other words, an excessive sympathetic activity goes along with extreme nocturnal deep BP and brain lacunae. Non-dippers showed more advanced cerebrovascular disease than normal dippers, but less than extreme dippers. The depression of autonomic activity determining extreme dipping is also associated with brain lacunae (Kario et al., 1997). In a study comparing ANS through HRV, ambulatory blood pressure monitoring (ABPM), brachial artery endothelium-dependent flow-mediated dilation (FMD) and the intima-media thickness (IMT) of the carotid artery, it was shown an association between FMD and extreme dippers, reflecting an endothelial dysfunction and an increase in sympathetic activity (Hamada et al., 2008). Extreme dippers, with a night blood pressure decrease more than 20 percent of the diurnal values, are more prone to stroke, particularly to hemorrhagic stroke (Metoki et al., 2006). It is always important to consider that subclinical events of stroke on imaging and autopsy are much more frequent than clinically patent strokes, in the elevated proportion of 1–14 (Leary and Saver, 2003). Subclinical events are strong predictors of future clinical events (Gupta et al., 2016).

The way the ECG is recorded may influence the results, particularly if the recording covers less than a full nyctohemeral cycle. Indeed, from a day-time recording with only 2-h duration recording, as in the Framingham study, the data did not take into account the HRV nocturnal values, while they may be of great interest as the prevalence of nocturnal autonomic dysfunction is high in lacunar stroke patients even in the absence of the commonest sleep-related disorders. In this respect a full-day HRV ambulatory measurement may better describe the autonomic balance giving both day and night values (Hamada et al., 2008). As already stated, nighttime HRV parameters are strong predictors of stroke in the Copenhagen Holter study (Binici et al., 2011).

An abnormal HRV not only predicts a first-ever stroke but also contributes to increase the risk of stroke recurrence (Buratti et al., 2020). The prediction of stroke occurrence by low HRV parameters is also significant after a hip surgery (Ernst et al., 2021).

Whatever the recording duration, HRV remains a powerful approach for aging evaluation. Even HRV calculated on 12-s ECG recordings, as performed from standard 12-lead recording at bedside, made possible to establish the order in which people of the Zutphen cohort died within a 30-year time frame for any cause of death including cancer. Again, our age is that of our ANS activity (Dekker et al., 1997).

At the other end, in the Copenhagen Heart Study involving longer ECG recording durations up to 48 h, global HRV value represented by night-time SDNN global ANS activity was significantly associated with death prediction, even after additional adjustment for heart rate and other relevant biomarkers including serum triglycerides, hs-CRP, and NT-pro BNP. The hazard ratio reached 4.31, p 0.003, for those in the lower half of nighttime SDNN. In the same study, 24-h HRV variables were predictive of all-cause mortality, including stroke (Binici et al., 2011).

There is not one ANS parameter recognized as the best marker for stroke prediction. This comes from the lack of systematization of HRV measurements parameters, due to choices of duration of recordings, parameters analyzed, and the mathematical choice to assess the RR intervals dispersion. Global parameters as SDNN, are the most often introduced in the predictive algorithms since they are easier to understand and to perform. Within the choice of temporal measurements, RMSSD is also often chosen to assess the parasympathetic drive. Frequential analysis are also often used as they open the possibility to get the LF/HF ratio, which represents well the ANS imbalance. Diurnal recordings enhance the LF components as the daily life is much challenging than the nocturnal sleeping period which in turn better assesses the parasympathetic activity (Berger et al., 2022). Even the ANS evaluation in the Framingham study was conducted on short diurnal recordings. Free ANS software will benefit future, and possibly passed, studies in giving access to every ANS parameters (Pichot et al., 2015).

For many studies, a decreased sympathetic activity was the most prominent predictor of cardiovascular events. This can be explained as this is a worsening of ANS imbalance. Parasympathetic activity is not taken into account in the Framingham study as only diurnal measurement were performed, a time where the parasympathetic activity is spontaneously rather low and so variations in parasympathetic activity cannot be measured easily and if measured will be hardly significant (Tsuji et al., 1994, 1996). Conversely, an increase in parasympathetic activity, as obtained through vagal nerve stimulation (VNS), will decrease the sympathetic drive (Clancy et al., 2014).

Today, prediction of stroke brought through ANS measurement was mostly performed using SDNN, RMSSD, LF, and HF variables. This approach should be improved using more variables available to researchers including baroreflex which considers not only the ANS circuitry but also the quality of the carotid sensors in the baroreflex.

Ischemic stroke and hemorrhagic stroke are both concerned by ANS prediction. There are both related to vascular disease linked to classical risk factors, as hypertension, dyslipidemias, metabolic syndrome, inflammation, endothelial disease, and lack of physical activity, each being strongly associated to ANS imbalance (Jiang et al., 2022). As a matter of fact, prevention of both stroke types relies on the same guidelines (Caldwell et al., 2019).

Stress allows an efficient answer to aggressions, increasing the chances for survival, but an excessive intensity or duration is deleterious. ANS measurement may thus participate in the prediction of vascular events by identifying the excess of adrenergic activity, offering means of stroke prediction. However, no specific study yet describes predictive differences in ANS parameters for predicting ischemic stroke versus haemorrhagic stroke.

In this context, there is nothing surprising that the diseases including the most severe altered ANS values are also those determining the shortest life duration and the more cerebrovascular complications. This is true in many chronic diseases and we will review some of them (Figure 2). These diseases often present multiple factors.

It is important to consider the role of autonomic system in stroke recurrence as it conveys the same predictive value than after a transient ischemic attack (TIA) (Guan et al., 2018). Measuring ANS in TIA allows to identify high risk sub-populations which may benefit from the warning (Guan et al., 2019). This is in concordance with the risk for a first stroke (Kleiger et al., 1987; Bigger et al., 1993; Tsuji et al., 1996).

Endothelial function is highly dependent on ANS activity which regulates blood flow as well as tissue-blood exchanges. During severe biological unbalance, as hypoxia or acidosis, the endothelium function may be severely compromised. Inflammation is a factor common to many pathologies and dysfunctions. Endothelial dysfunction may be found in each of the chronic diseases just described.

Endothelium disease is associated to AF (Corban et al., 2021). The decrease in parasympathetic activity associated with an increase in sympathetic activity plays a key role in vascular vulnerability (Bäck et al., 2019). This triggers several pathways including increased reactive oxygen species (ROS) and increased inflammation (Harada et al., 2015; Bäck et al., 2019). Beyond their high cellular aggressivity and disruptive effects on regulations, ROS further enhance sympathetic activity by stimulating the hypothalamic subfornical centers (Abboud, 2010). By this way, inflammation triggers a large increase in vascular inflammasome (Bäck et al., 2019). The disease further extends to the content of the vessels by activating platelets and many other factors (Harada et al., 2015).

Increased ROS induce microvascular dysfunction including impaired endothelium-dependent vasodilator and enhanced endothelium-dependent vasoconstrictor responses, along with increased vulnerability to thrombus formation (Yu et al., 2019). Increased ROS thus result in enhanced fluid filtration associated with protein extravasation and activation of leukocytes. All of these pathologic microvascular events involve the increased production of ROS, and consecutive induced ischemia reperfusion, which further activates inflammasomes, provokes severe mitochondrial disorders, and determines release of microvesicles in endothelial cells (Bäck et al., 2019). There is a relationship between HRV and endothelial function evaluated through brachial artery flow mediated dilation (Pinter et al., 2012). This approach underlines the strong dependency of endothelium to ANS parasympathetic activity. Chronic baroreceptor stimulation improves endothelium function (Chapleau et al., 2016), as does direct acetylcholine administration (Borovikova et al., 2000). Endothelium health is thus strongly dependent on parasympathetic activity. Rebalancing autonomic activity through VNS attenuates this dysfunction and protects from stroke (Carandina et al., 2021).

Both VNS and renal denervation are intended to increase parasympathetic activity and decrease sympathetic predominance. Acute, or more often chronic, VNS enhances endothelium health which enhances vagal protective activity (Saeed et al., 2005; Chapleau et al., 2016).

The powerful downregulation of inflammatory process by vagal stimulation is a fundamental key of the protection brought by vagal nerve activity. Transcutaneous auricular vagus nerve stimulation (tVNS) was shown to protect rats from the potent lipopolysaccharide inflammatory stimuli, by decreasing TNFα, IL-6, and IL-1β response to the inflammatory stimuli. Conversely, inhibition of the tVNS effects by α7nAChR antagonist injection confirmed this mechanism (Zhao et al., 2012). Using the Shwartzman reaction, nicotine and the CAP55 cholinergic agent decreased substantially both VCAM-1 mRNA and E-selectin mRNA expression by the endothelium, and reduce leukocyte adhesion (Saeed et al., 2005). In vivo VNS in the carrageenan air pouch model induced similar effects (Saeed et al., 2005). Vagal stimulation determines a peripheral vascular protection in a rat model of myocardial ischemia/reperfusion through the cholinergic anti-inflammatory pathway which is dependent on a7nAChR (Zhao et al., 2013).

In CHF, a strong negative correlation was shown between the plasmatic increase in NE and survival (Cohn et al., 1984). This underlines the central role of NE as a highly toxic endocrine factor. On the other hand, the strong protective effect of parasympathetic activity was demonstrated in CHF through vagal stimulation (Zucker et al., 2007). Neurovagal stimulation was shown to correct or help reducing AF (Kiuchi et al., 2016; Stavrakis et al., 2020). Low-intensity vagal stimulation inhibits AF in an animal model of OSA (Gao et al., 2015). In another critical clinical field, CKD, complete denervation of the native diseased kidney by bilateral nephrectomy decreases the cardiovascular risk (Obremska et al., 2016).

After an induced ischemic stroke, infarct size was significantly reduced in response to vagal stimulation in animals (Yang et al., 2018); the infarct size decrease was associated with a decrease in blood-brain transfer in the stimulated group, spatially correlated with the attenuation of the infarct size. It was also shown that vascular tight junctions were protected in microvessels with lower serum proteins leakage, which underlines the protection brought to the endothelium. After stroke, the non-invasive VNS reduces blood-brain barrier disruption in a rat model of ischemic stroke (Yang et al., 2018).

Today, since Hilz et al. (2011) proposed to substitute the NIH Stroke Scale (NIHSS) clinical values score to encompass the lack of ANS variables availability and take advantage of that ANS variables have become readily available through accessible devices and software (Pichot et al., 2016). If either low ANS variables values or ANS severe imbalance is detected, a priority should be to identify the disorder explaining the fall in ANS activity and taking the needed corrective decisions to avoid further disease extension. This includes mainly OSA, hypertension, diabetes, CKD, and inflammation. Recording ANS activity in large populations should be encouraged to measure ANS on large populations, the recordings may be validated through cardiologist teams to ensure the needed quality.

Vagal activity is a key factor which, when maintaining its activity through physical exercise is not possible, may be boosted by non-invasive transcutaneous vagal stimulation.

Obtaining individual values only needs analysis of an ECG recording, preferably on a full nyctohemeral period, which is now easy to perform and repeat. Using growth curves for sympathetic and parasympathetic activity would be straightforward using growth curves similar to children’s weight and height. An annual recording may be a good preventive target. The recording may be performed at young age when unfavorable clinical conditions are present.

The predictive power of ANS activity for cardiovascular diseases may lead to a large utilization of autonomic modulation in preventing the occurrence of ischemic and hemorrhagic stroke and limiting their severity (Carandina et al., 2021). We may well have the age of our autonomic nervous system and we can enhance its protective activity through physical exercise or, if is difficult to exercise, through tVNS.

J-CB, VP, DH, MBe, SC, LM, MBä, J-RL, and FR contributed to conception and design of the study. J-CB wrote the first draft of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.