Transient ischemic attack (TIA) and minor ischemic stroke are two types of cerebrovascular ischemic events with mild or transient symptoms and non-disabling consequences (1, 2). However, they are markers of reduced cerebral blood flow and “warning signals” for the possible occurrence of severe ischemic strokes (2). TIA and minor stroke do, therefore, offer a unique opportunity to forestall the onset of permanent brain injury by initiating early treatment (3, 4). Guidelines recommend urgent treatment to TIA and minor stroke, which may reduce the volume of brain damaged by ischemia, promote recanalization of blocked vessels, and decrease the risk of severe ischemic stroke (5, 6). However, these treatments may generate safety concerns related to minor bleedings (7) and/or fatal intracranial hemorrhage (7, 8). Therefore, an urgent and precise risk stratification for TIA or minor stroke is of the utmost importance for medical caregivers to identify high-risk patients and provide personalized treatment. Current risk stratification tools include scoring systems and imaging techniques, all of which have their own individual limitations that inevitably reduce their clinical utility. Accordingly, currently, it remains a challenge to precisely and easily identify the risk of secondary ischemic events after TIA or minor stroke.

People who live with chronic stroke risk factors and suffer an acute TIA or minor stroke episode are at high risk of developing secondary ischemic events (9, 10). Each identified chronic risk factor and acute trigger of ischemic stroke is considered a source of stress for the body. Given the critical role of the autonomic nervous system (ANS) in regulating stress responses (11), it seems possible to determine the comprehensive effect of different stressors by assessing the status of their ANS function. This article is intended to address this issue by reviewing the existing knowledge and evidence and providing an evidence-based deduction on the association between ischemic stroke risk factors, stress, and ANS function in patients with TIA or minor stroke.

We first provide a description of ischemic stroke and TIA with focus on their risk factors and current risk stratification tools. We then present concepts related to stress and the stress response regulatory system, in particular the ANS, whose function can be assessed through the analyses of heart rate variability (HRV). We demonstrate the progressive shift from “stress adaptation” to “stress-related diseases,” with emphasis on the changes to the ANS response throughout this process. Finally, we review evidence in favor of an association between stroke risk factors and ANS dysfunction indexed by impaired HRV parameters.

Beyond all chronic risk factors, TIAs and minor stroke episodes provide additional risk information for secondary ischemic events. Johnston et al. determined that 90 days after emergency diagnosis of TIA, 428 of 1,707 patients (25.1%) developed adverse events including stroke, recurrent TIAs, cardiovascular hospitalization, and death (10). Moreover, Rothwell and Warlow showed that around 17% of ischemic strokes were preceded by a warning TIA; in 43% of cases, this warning TIA occurred within 1 week of the subsequent stroke (12). Although the stroke rate in the first 90 days after an initial event has dropped to 7–13% in recent randomized control trials (13), this overwhelming risk of severe ischemic events after initial TIA or minor stroke underscores the ongoing need for urgent evaluation and treatment of at-risk patients.

The development of secondary ischemic events is generally predicted by assessing the combination of several risk factors (6, 14). AHA/ASA guidelines (6, 14) propose a list of recognized chronic risk factors for ischemic stroke and TIA that are summarized in Table 1. Apart from the traditional chronic risk factors that predispose to the occurrence of ischemic stroke, some acute triggers may precipitate this process (15, 16) (Table 1). Several scoring systems have been widely used in clinical practice to evaluate the risk of early occurrence of severe ischemic stroke after TIA or minor stroke, including ABCD2 (A for age, B for blood pressure, C for clinical feature, D for duration of the symptoms, and another D for diabetes), ABCD3 (the presence of ≥2 TIA symptoms within 7 days added to the ABCD2 score), and ABCD3-I (the presence of abnormal findings on neuroimaging further added to the ABCD3 score). The predictive ability of ABCD2 score is only moderate with an area under the curve (AUC) between 0.55 and 0.7 (17, 18). This may be attributed to the difficulty to qualify the effect of risk factors on an individual basis due to intrapersonal heterogeneity. For instance, “diabetes” has different degrees of severity; and individuals have different ways of coping with the consequences of chronic metabolic stress. Furthermore, other important risk factors, such as smoking, obesity, sedentary life, and psychological stress, as well as other factors not yet identified, are not considered in the classic clinical assessment. Incorporation of the imaging assessment (ABCD3-I) improves the predictive power for future ischemic stroke after TIA or minor stroke, with AUC > 0.8 (19, 20). However, emergency imaging is costly and technology dependent, therefore affecting the universal use with subsequent delays to the scoring process and associated risk assessment. The limitation of current tools for personal risk prediction calls for the development of new valid, precise, and convenient tools to determine the risk of a secondary ischemic event after initial TIA or minor stroke and to direct appropriate medical care for affected patients.

One approach that seems promising is to consider that most stroke risk factors listed in Table 1 are also body stressors and therefore affect the ANS response. It may then be possible to determine the overall effect of all life stressors on the body in patients after TIA or minor stroke, by assessing their ANS function. The next section will present evidence of this association, using HRV parameters as markers of ANS function.

In the central construct of Selye’s stress theory (11, 21), the generalized definition of “stress” describes a state of threatened homeostasis (refers to the stability of physiological systems that maintain life) caused by any form of internal or external disturbing forces, or “stressors.” The person’s life experiences (i.e., the accumulation of stress experiences) contributes to building an idiosyncratic “stress profile” of the individual. This “stress profile,” measured at one specific time, includes both previous and current stress experiences: physical, physiological, psychological, and environmental (11, 22). The “stress response” or “adaptive response” is a counteracting force initiated to neutralize the effects of stressors and re-establish homeostasis. The stress response is a succession of processes that occur in response to the perception of stress by the brain (23, 24). One main stress regulatory system is the ANS, which plays a particularly critical role in modulating the stress response (25, 26).

The ANS is a part of the peripheral nervous system and regulates physiological processes without conscious control. The two major divisions of ANS comprise the sympathetic nervous system (SNS) and the parasympathetic nervous system (PNS). The ANS innervates most organs and controls important physiological and behavioral processes (27). In many physiological situations, the stress response is regulated by the complementary interaction of SNS and PNS. Activation of either SNS or PNS outflow is accompanied by the relative inhibition of the other, suggesting the concept of “sympathovagal balance” (27). The ANS dynamically controls the body response to a range of external and internal stimuli/stressors, providing physiological stability to the body (28). Typically, when the source of stress is acute [i.e., lasting for a period of minutes to hours (22)], the ANS, via sympathetic and parasympathetic branches, provides an instantaneous physiological/adaptive response that provokes immediate physiological state alterations through neural innervation of the target organs (24, 28). A typical example of stress response is the physiological inflammatory response (29). The anti-inflammatory response is mostly controlled by PNS, with synergistic input from the SNS (25). As illustrated by Tracey (25, 30), the cholinergic anti-inflammatory pathway represents the afferent branch of the neuronal reflex that modulates local inflammatory responses (25, 30). The efferent branch of the vagus nerve produces acetylcholine that effectively reduces the production of pro-inflammatory cytokines. In addition, both SNS and the humoral anti-inflammatory pathway are triggered, releasing stress hormones that include cortisol and catecholamines to elicit anti-inflammatory effects (25, 30). In this situation, the PNS and SNS act synergistically to control the stress response.

This short-term, tightly controlled regulatory response serves to preserve homeostasis. However, when the source of stress persists for days to months, it is considered to be a chronic stress (22). Chronic stressful conditions represent situations in which environmental demand exceeds the natural regulatory capacity of the body (31). Long-term exposure to these chronic stressors leads to a progressive dysfunctional ANS response to stress, and in particular, to a constrained PNS capacity to control the stress response (21, 32), which may lead to an anticipatory stress response (unpredictable) and a reduced control of the neuroendocrine reaction (uncontrollable) (29, 31). This progressive deterioration of the stress response provides a neuromodulation basis to understand the progression from “stress adaptation” to “stress-related disorders” (32, 33).

The established traditional risk factors of ischemic stroke, such as aging, diet, cigarette smoking, excessive alcohol consumption, and psychological stress, are typically chronic stressors that continuously and cumulatively affect the stress systems (ANS and hypothalamic–pituitary–adrenocortical (HPA) axis) (28). The affected neural stress systems will then produce excessive stress hormones such as catecholamines and cortisol, which affect the target tissues and cause various metabolic disorders, such as hypertension, hyperglycemia, and dyslipidemia (28). These metabolic disorders, acting as “secondary” stressors, may further impair the ANS function, creating new pathological cascades, which ultimately leads to cardiovascular and cerebrovascular complications (28). Such disease progression is illustrated in Figure 1. In other words, inappropriate responses to initial stress becomes the source of new stress, leading to a sustained negative cycle of mutual reinforcement toward the development of chronic conditions (28, 33). In this deregulated cascade, it is difficult to distinguish between causes and consequences. The stress system is to a large extent “nonspecific” and meant to interact with internal or external perturbations in a similar manner.

In this chronic stress situation, an additional acute event may extend the overall stress level beyond the range of the physiological and adaptive ANS response. In stroke research, the dynamic nature of stroke development follows such a pattern, in which the acute triggers for ischemic stroke (such as recent infections and TIA episodes) are seen as sources of acute stress to the body that superimpose their effects on the original chronic stress context; and this may increase the overall stress level to a new threshold that precipitates the occurrence of cerebrovascular ischemic events (15, 16, 34).

This framework supports the association between stress, ANS, and development of ischemic stroke as portrayed in Figure 2. Through the negative spiral described in Figure 2, progressive disease development leads to an accumulation of stress that affects the entire body, with ischemic stroke as the “final endpoint” of the overall effects of multiple stressors.

The ANS dynamically controls the response of the body to a range of external and internal stimuli/stressors, providing physiological stability in an individual (28). Because most of ANS actions are not accessible to direct and easy physiological testing, in clinical settings the most widely used techniques entail the assessment of an end-organ response to an ANS physiological provocation (35). Some clinical tests for measuring ANS function (35–38) are summarized in Table 2. Among these tests, HRV assessment is a recognized, non-invasive, convenient, and reliable method to measure the ANS function, which will be mainly described in this article. HRV is defined as the fluctuations in the intervals between normal heartbeats (39), and it is mainly based on three analytic methods: frequency domain method, time domain method, and non-linear method (39). The time and frequency domain analyses of HRV are well-developed methods that are recognized as valid and reliable procedures for assessing autonomic function in both clinical and experimental settings (40, 41). Within each analysis, different parameters reflect different aspects of ANS function (Table 3). HRV is generated and analyzed from the ECG waves, which can be recorded from specific devices/software or using 24-h Holter (or other long-term cardiac telemetry) (39).

Due to the dynamic nature of ANS activity, HRV is constantly changing. A single HRV assessment reflects the instantaneous ANS activity at a specific time. According to the uncoupling theory (42), decreased HRV signifies diminished ANS responses; and this process is correlated with disease severity. Conversely, organ recoupling indexed by increased HRV would represent the return of ANS modulation (42). Therefore, assessing the change in HRV between periods can reflect the dynamic/trend of ANS activity over time when stress is changing (40, 43). Accordingly, HRV may serve as a proxy for the neurological mechanisms that guide flexible control of physiology and behavior in the context of stress (44). Through several decades’ progress in HRV research, today HRV measurement is not only an established tool in cardiology research (45) but also increasingly being used in a wide range of clinical and psychophysiological research (46, 47), including informing cardiovascular risk stratification and ischemic stroke prediction (48, 49). Therefore, the critical idea is that HRV may be more than just an index of cardiac function; it may act as an indicator of central modulation of global stress responses. Accordingly, HRV may serve as an easy measurement of the stress regulatory neural network and may provide useful information on the capacity of the body to effectively respond in a stressful situation.

The relationship between ANS dysfunction and ischemic stroke is complex and bidirectional. ANS dysfunction (a sign of chronic stress) may predict the occurrence of ischemic stroke and, on the other hand, ischemic stroke as a source of new stress affects ANS (50). Ischemic stroke is a source of huge stress characterized by sympathetic predominance, and the associated catecholamine surge may cause cardiac autonomic derangement (51, 52), myocardial damage, and thus possible cardiac dysfunction with increased mortality after ischemic stroke (46, 53). Impaired autonomic function is likely to be a common feature in all ischemic stroke patients (52, 53). Earlier findings showed that: (i) lower HF and/or total power was correlated with a higher risk of incident stroke in adults (49); (ii) other HRV parameters such as dichotomized coefficient of variance of NN intervals (CV%) and power law slope (SLOPE) may also stratify high-risk patients to develop stroke, with 0.68 c-statistic for combined high CV% and high SLOPE (54); (iii) patients with ischemic stroke irrespective of the side of the ischemia in the brain had dysfunctional ANS and decreased HRV [HF, LF and total power (TP)] compared to healthy controls (50, 55); (iv) certain locations of stroke, such as right insular stroke, right middle cerebral artery stroke, and parietal or frontal lobe stroke, were correlated with higher risks of cardiac dysfunction (56), atrial fibrillation (AF) (52, 56), and myocardial injury (57), compared to other sites; (v) acute large strokes, because of the huge stress and catecholamine release, were more likely to cause cardiac dysfunction compared to lacunar strokes; and (vi) poststroke decreased HRV was associated with stroke severity, incidence of early and late complications, and mortality (47, 58). The potential therapeutic effects of parasympathetic activation on ischemic stroke have also been documented (59, 60).

From the perspective of chronic stress leading to disease development (from stress adaptation to stress-related disorders), most risk factors of ischemic stroke can be considered as body stressors (some of them are also consequences of multiple other stressors), with the possible stress cascade as described in previous text. ANS dysfunction assessed by HRV parameters may then reflect the overall effects of different stressors/risk factors (both chronic and acute), including the initial TIA or minor stroke episode. A number of studies (Table 4) report the relationship between autonomic dysfunction measured by impaired HRV and main risk factors of ischemic stroke described in Table 1.

According to the stress theory, and association between stroke risk factors, stress, and ANS/HRV, it is possible to establish a “comprehensive stress model” using HRV as a marker of ANS activity and adaptation to stress. This model would represent the overall effects of stroke risk factors and could be used to identify personalized risk of experiencing a secondary ischemic event after TIA and minor stroke.

The HRV-based comprehensive stress model refers to a model that comprises HRV parameters and multiple dimensions of stress variables, including chronic and acute, physiological, and psychological. The assessment of HRV measures the objective physiological response to stress factors. For an individual, HRV values may represent the comprehensive effect of “multiple stressors” at a given point in time. The HRV-based theoretical model is presented in Figure 3.

It is critical to estimate the risk of stroke occurrence or recurrence after initial TIA and to clearly identify those at a higher risk of developing secondary ischemic events among people with a burden of chronic risk factors/stressors. However, this remains challenging using current criteria, partly because the specific contributions of these risk factors are difficult to quantify given individual heterogeneity and also many other risk factors (unaddressed and unidentified) are not assessed when determining an individual’s risk profile. We have shown that both chronic risk factors and acute triggers of ischemic stroke are sources of stress to the body and are closely associated with ANS dysfunction that supports the neurogenic hypothesis of ischemic stroke development. The usual compensatory stress response of ANS may fail in the context of chronicity, which makes it challenged to face new acute stressors. The improper stress responses render these normally short-term responses prolonged and maladaptive, which relentlessly disrupts normal physiological pathways and progressively contributes to the development of stress-related diseases, such as TIA and ischemic stroke. Accordingly, we advocate that HRV assessment, as a measurement of ANS function, may represent the comprehensive effect of “multiple stressors” and may reflect the overall health condition at a given point in time. This review provides evidence for the use of HRV data to predict the occurrence of secondary ischemic events after initial TIA or minor stroke, as illustrated in Figure 3. This theoretical HRV-based comprehensive stress model and further hypotheses on identification of HRV predictors will initiate studies on identifying an innovative way to stratify the risk of TIA or minor stroke through assessing the effect of ANS and stress.

LG and J-PC proposed the study questions, conducted the literature review, and prepared the first draft of the manuscript. GM improved the study conception and provided a detailed review and editing. VC provided insight on specific aspects of the paper and provided a detailed review and editing. None of the authors received payment for writing the article. They all approve the submission of this version of the manuscript and take full responsibility for the manuscript.

This publication is original: There are no prior publications or submissions with any overlapping information. None of the authors has disclosed any potential conflicts of interest. J-PC is supported in part by a scholarship of the BC Children’s Hospital Research Institute in Vancouver, Canada. The remaining authors have no financial relationships relevant to this article to disclose.