Linking Triglyceride-Glucose Index to Spontaneous Intracerebral Hemorrhage: Mechanisms and Predictive Insights

Introduction

Spontaneous intracerebral hemorrhage (SICH) is a form of non-traumatic parenchymal hemorrhage, accounting for 10% to 20% of all strokes [1]. However, it remains one of the leading causes of stroke-related mortality and disability. Among the various subtypes of SICH, hypertensive intracerebral hemorrhage is the most common. It typically involves deep brain structures, such as the basal ganglia, thalamus, brainstem, and cerebellum. The underlying pathophysiological mechanism is primarily related to chronic hypertension-induced arteriolosclerosis, including lipohyalinosis and the formation of microaneurysms, which eventually lead to vessel rupture. In addition to hypertension, other etiologies of SICH include cerebral amyloid angiopathy, vascular malformations, brain tumors, and the use of anticoagulant medications, each associated with distinct hemorrhagic patterns and clinical features. The pathophysiological mechanisms of SICH are complex, primarily involving hypertensive small artery disease, atherosclerosis, cerebral microbleeds, and other metabolic abnormalities [2–4]. Despite advancements in acute-phase treatment and rehabilitation management in recent years, the overall prognosis of SICH remains poor, with most patients facing a high mortality rate and significant neurological deficits. Therefore, early identification of high-risk populations, risk prediction of disease onset, and exploration of underlying pathological mechanisms are of paramount importance. The triglyceride-glucose (TyG) index is an emerging metabolic abnormality marker used to assess the degree of insulin resistance [5]. It is calculated using the following formula: TyG=ln (triglyceride concentration (mg/dL)×fasting glucose concentration (mg/dL)/2). As it is derived from routinely available laboratory parameters, the TyG index is simple to calculate, readily accessible, and cost-effective, making it widely applicable in clinical practice and epidemiological research. Accumulating evidence indicates that the TyG index is closely associated with metabolic syndrome, type 2 diabetes mellitus, atherosclerosis, and various cardiovascular diseases [6,7]. Moreover, it has demonstrated superior sensitivity and practicality in predicting cardiovascular events when compared with traditional surrogate markers of insulin resistance.

According to Araújo et al [8], the TyG index serves as an effective biomarker for cardiometabolic risk, reflecting underlying metabolic dysregulation and inflammatory status. Recent research suggests a potential link between metabolic disorders and cerebrovascular diseases, including SICH [9]. As an indirect marker of insulin resistance, the TyG index may offer novel insights into the risk prediction of intracerebral hemorrhage. This review aims to evaluate the potential association between the TyG index and SICH, and to analyze its clinical utility in risk prediction, understanding of underlying pathophysiological mechanisms, and disease management.

Role of Hypertension in SICH

Persistent elevation of blood pressure and subsequent vascular pathology are the most critical modifiable risk factors for SICH [10]. Chronic hypertension induces structural alterations in small cerebral vessels, including lipohyalinosis and Charcot-Bouchard aneurysm formation, increasing their susceptibility to rupture and leading to blood extravasation into the deep brain parenchyma [11]. These vascular changes are commonly observed in regions supplied by small penetrating arteries, such as the putamen, thalamus, brainstem, and cerebellum. Animal model studies suggest that arteriosclerosis and dysregulation of matrix metalloproteinases (MMPs) are key mechanisms underlying these vascular abnormalities [12]. Moreover, increased pro-inflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6), along with leukocyte infiltration into perivascular spaces, can further compromise vascular function [13]. An acute hypertensive response, defined as a systolic blood pressure (SBP) ≥140 mmHg peaking within the first 24 h after symptom onset, is associated with poor outcomes. Studies indicate that patients with ICH with an initial SBP ≥196 mmHg have a mortality rate of 44%, significantly higher than those with an SBP ≤196 mmHg (mortality rate of 18%) [14]. The hypertensive response can exacerbate hematoma expansion by increasing pressure on already compromised small arteries. Additionally, oxidative stress and MMP activation triggered by hypertension can contribute to further hemorrhagic propagation. Multivariate analysis has identified an admission SBP ≥200 mmHg as an independent risk factor for hematoma enlargement. Consequently, an SBP threshold of 180 mmHg may be a clinically relevant marker of acute hypertensive response. Rapid blood pressure reduction within the initial hours following ICH onset is a key strategy for mitigating further hemorrhage. Several phase II and III clinical trials, including the INTERACT and ATACH series, have evaluated this approach [15,16]. The INTERACT-1 (phase II) and INTERACT-2 (phase III) trials randomized patients to intensive BP lowering (target SBP 140 mmHg) versus standard treatment (<180 mmHg). Although INTERACT-2 found no significant difference in the primary outcome (modified Rankin scale scores 3–6), secondary analyses suggested a trend toward improved functional outcomes in the 140 mmHg group. This study provided the foundation for current guidelines recommending a target SBP of 140 mmHg [10]. The ATACH-1 (Phase II) and ATACH-2 (Phase III) trials investigated more aggressive BP targets (SBP 110–139 mmHg), compared with standard targets (140–179 mmHg) [16,17]. ATACH-2 demonstrated that while intensive BP lowering achieved faster and more effective BP reduction, it did not result in significant differences in primary outcomes. However, post hoc analysis revealed that patients who received intensive BP control within 2 h of onset exhibited significantly lower hematoma growth rates (18.2% vs 28.4%) [18]. Despite potential benefits, aggressive BP reduction carries certain risks. Among patients with baseline SBP ≥220 mmHg, those who received intensive BP lowering experienced significantly higher rates of neurological deterioration within 24 h (15.5% vs 6.8%) and increased 90-day mortality or severe disability (66.7% vs 29.2%) [19,20]. Additionally, the incidence of renal adverse events was higher in the intensive BP control group (13.6% vs 4.2%) [18,21]. The summary of the INTERACT and ATACH trials is presented in Table 1.

Prehospital BP management also plays a critical role in determining ICH outcomes. Studies indicate that compared with patients with ischemic stroke, patients with ICH exhibit higher and more stable BP levels during ambulance transport [22]. Although prehospital BP is independently associated with admission hematoma volume, there is currently no evidence to suggest a direct influence on hematoma expansion or spot sign occurrence. Based on available data, a prehospital BP target of <180 mmHg is recommended to accommodate the management needs of patients with ischemic stroke and ICH [22].The choice of antihypertensive agents in acute ICH is another crucial consideration. Among the commonly used agents, nicardipine, extensively used in the INTERACT and ATACH trials, has demonstrated significant efficacy in BP control. In contrast, glyceryl trinitrate, when administered before hospitalization, failed to improve patient outcomes and may have exacerbated early hematoma expansion by inhibiting vasoconstrictive responses [23,24]. Additionally, intravenous vasodilators, such as glyceryl trinitrate and sodium nitroprusside, can increase intracranial pressure and reduce cerebral perfusion, potentially leading to perihematomal ischemia. While current trials suggest that reducing SBP to 140 mmHg can be beneficial, excessive BP reduction can have detrimental consequences. Future research should address the following key questions. (1) Optimal BP target: What is the ideal balance between the speed and extent of BP reduction to minimize adverse events in ICH patients? (2) Timing of intervention: How does the time window from symptom onset to treatment initiation affect BP management efficacy? (3) Choice of antihypertensive agents: What are the relative advantages of different drugs in terms of BP control and neuroprotection? Finally, (4) Personalized treatment strategies: Should BP targets be adjusted based on baseline BP levels, hematoma location, and comorbidities?

In conclusion, hypertension is not only a primary risk factor for ICH but also a critical therapeutic target in the acute phase. Optimizing BP management strategies can significantly improve long-term patient outcomes, although further research is needed to refine specific treatment protocols.

Impact of Metabolic Abnormalities on SICH

Metabolic abnormalities play a critical role in the pathophysiology of SICH, which is associated with high morbidity and disability in neurology. The complex pathological process of SICH extends beyond the mechanical compression and hemorrhagic injury caused by acute hematoma, often involving a cascade of metabolic dysregulation that exacerbates secondary brain injury [1]. Cerebrospinal fluid (CSF) circulation is essential for maintaining cerebral hemostasis and metabolic homeostasis. However, when hemorrhage extends into the subarachnoid space (SAH), the perivascular and ventricular flow pathways, along with the brain’s lymphatic drainage system, become disrupted by exogenous stimuli. This results in the accumulation of hemoglobin and hemolytic byproducts in the CSF, significantly inducing neuroinflammation and vasospasm [25]. Animal models have demonstrated that targeting CSF hemoglobin can mitigate delayed cerebral ischemia following SAH and improve neurological outcomes, underscoring the profound impact of hemolytic byproducts on microcirculatory disturbances and neurofunctional prognosis [26]. Hemolytic byproducts also activate caspase-1-dependent inflammasomes and lipid transporter-mediated inflammatory pathways, leading to iron homeostasis disruption and further exacerbating unfavorable outcomes [27,28]. In addition, dynamic fluctuations in CSF metabolites reflect the pathophysiological progression of brain injury. For instance, taurine levels decrease significantly within 24 h after SAH, whereas glutamate and creatine concentrations surge after 1 week [29], highlighting metabolic shifts that could serve as biological indicators for secondary brain injury progression. Over time, neurons release high-mobility group box 1 (HMGB1), and microcirculatory impairment mechanisms become increasingly evident. Notably, intraoperative observations during aneurysm clipping reveal that small arteries exhibit focal or “beaded” multi-segmental vasospasm, leading to profound cortical microcirculatory hypoperfusion. Additionally, prolonged intracerebral circulation time within 24 h after ICH has been strongly correlated with delayed cerebral ischemia [30]. A key observation is that small artery vasospasm is not mediated by endothelin A receptor pathways, distinguishing it from the pathophysiology of large-vessel vasospasm. This distinction may partially explain why clinical trials, such as the CONSCIOUS study, failed to yield expected therapeutic benefits [31]. Furthermore, hemoglobin can induce acute pericyte contraction around capillaries, triggering a “beaded” microcirculatory dysfunction pattern. Hemolysis-associated factors, including bilirubin oxidation end products (BOX), propentdyopents, and free iron, further exacerbate vasoconstriction, microvascular occlusion, and cognitive impairment [32–34]. Microcirculatory dysfunction can be classified into 3 progressive stages: compensation, decompensation, and irreversible collapse. Following vasospasm, platelet and leukocyte aggregation in capillaries [35,36], together with the formation of neutrophil extracellular traps (NETs), create a cycle of thromboinflammation that ultimately impairs lymphatic drainage, leading to an irreversible state of microcirculatory failure [37,38]. Therapeutic strategies in neurocritical care, such as hypervolemia, hemodilution, and hypertension therapy, aim to maintain cerebral perfusion; however, studies suggest that while hypervolemia, hemodilution, and hypertension therapy improves overall cerebral blood flow, it does not significantly alter metabolic markers (eg, microdialysis metabolites), highlighting the necessity of addressing deeper metabolic dysfunctions, such as mitochondrial impairment. Emerging evidence suggests that extracellular mitochondrial content in the CSF can provide novel insights into neurofunctional recovery, while mitochondrial dysfunction itself can serve as a potential therapeutic target in SAH management [39]. Further research is required to delineate the spatial and temporal variations of mitochondrial activity in different brain regions. Beyond SAH, metabolic syndrome has been identified as a major risk factor for SICH (Figure 1). A prospective cohort study in a Japanese population demonstrated a strong association between metabolic syndrome and the development of deep and infratentorial cerebral microbleeds, with hypertension and obesity synergistically promoting small-vessel pathology and substantially increasing the risk of ICH. Cerebral microbleeds are considered reliable precursors of intracranial hemorrhage, and a higher cerebral microbleed burden is associated with an increased risk of recurrence, underscoring the importance of early metabolic syndrome detection and intervention to mitigate hemorrhagic risk. A multicenter study further explored the relationship between pre-stroke and post-stroke glycemic status and acute SICH outcomes. In patients without diabetes, elevated fasting blood glucose and random blood glucose levels at admission were significantly correlated with increased hematoma volume, neurological deficits, and poor 90-day prognosis, whereas this association was not observed in patients with diabetes [40]. This suggests that acute hyperglycemia primarily reflects a stress response or an underlying metabolic vulnerability in non-diabetic individuals. Long-term glycemic markers, such as glycated hemoglobin, while useful for assessing chronic glycemic burden, have demonstrated inconsistent predictive value for acute-phase brain injury risk. The optimal timing and target thresholds for glucose control in acute SICH remain to be determined. Hyperglycemia may exacerbate post-ICH inflammation via oxidative stress and mitochondrial dysfunction. Interestingly, enhanced glucose-lowering therapy after hematoma clearance has been shown to alleviate lactate, pyruvate, and inflammatory cytokine levels in some patients [41]. In vitro and animal models indicate that hyperglycemia downregulates aquaporin-4 expression, disrupts the blood-brain barrier, and exacerbates vasogenic cerebral edema. Consequently, interventions targeting mitochondrial function or reactive oxygen species scavenging could have significant implications for managing ICH in patients with diabetes. Recent evidence suggests that the Sirtuin 3 (Sirt3) pathway plays a crucial role in maintaining mitochondrial homeostasis and antioxidant capacity. Hyperglycemia suppresses Sirt3 expression, potentially accelerating the progression of brain injury. Honokiol, a direct activator of Sirt3, exhibits neuroprotective properties by enhancing its enzymatic activity [42], although its effects in hyperglycemia-associated ICH models require further validation. In summary, metabolic abnormalities significantly contribute to the early pathological progression and prognostic evaluation of SICH. This includes exogenous stimulation-induced microcirculatory dysfunction following SAH, metabolic syndrome-driven small-vessel pathology from hypertension and obesity, oxidative stress and mitochondrial impairment secondary to hyperglycemia, and potential therapeutic targets. Multimodal monitoring, integrating CSF metabolomics, neuroimaging, and electrophysiology, enables a comprehensive assessment of brain injury dynamics. Future research should leverage machine learning and molecular diagnostic platforms to identify key biomarkers and establish personalized intervention frameworks, ultimately advancing precision medicine for different subtypes of intracerebral hemorrhage.

Other Potential Risk Factors

Risk factors for SICH extend beyond traditional modifiable factors, such as hypertension, smoking, and excessive alcohol consumption. Several less recognized but equally critical potential risks include decreased lipid levels (notably excessive reductions in low-density lipoprotein cholesterol [LDL-C] and triglycerides), medication use (anticoagulants, antithrombotic agents, sympathomimetic drugs), and non-modifiable characteristics, such as advanced age, male sex, cerebral amyloid angiopathy, and Asian ethnicity. The summary of risk factors associated with SICH and factors contributing to hematoma expansion is presented in Table 2. In a large international case-control study (INTERSTROKE), which included over 6000 patients from 22 countries, modifiable risk factors – including hypertension, smoking, waist-to-hip ratio, dietary habits, and high alcohol intake – accounted for 88.1% of the population-attributable risk for SICH. Hypertension was identified as the predominant risk factor, with a particularly significant impact on deep cerebral hemorrhages, in which the incidence was nearly twice as high as that of lobar hemorrhages. Similarly, current smoking and heavy alcohol consumption have been independently associated with an increased risk of SICH. In terms of lipid levels, excessively low total cholesterol or LDL-C levels have been linked to more severe ICH presentations, a negative correlation that has been corroborated by case-control studies conducted in Australia and other regions. Regarding anticoagulation therapy, warfarin use has been associated with a 2- to 5-fold increase in the risk of SICH, depending on anticoagulation intensity. With the increasing prevalence of oral anticoagulant use among the aging population, anticoagulation-associated ICH is rising in clinical practice. Antiplatelet therapy also poses similar risks. Although some case-control studies failed to establish a significant association between antiplatelet agents and SICH risk, meta-analyses indicate that antiplatelet therapy modestly but significantly increases ICH risk. Prior use of antiplatelet agents has also been linked to higher post-ICH mortality rates and an increased risk of early hematoma expansion. Dual antiplatelet therapy further amplifies this risk, with the incidence of ICH in atrial fibrillation patients using aspirin and clopidogrel nearly doubling, compared with aspirin monotherapy. Similarly, the abuse of sympathomimetic drugs, including cocaine, heroin, amphetamines, and ephedrine, is frequently observed in younger patients with ICH. High-dose phenylpropanolamine intake has been particularly detrimental in female patients, and even low-dose phenylpropanolamine, found in common cold medications, has been linked to an increased risk of hemorrhagic stroke in women. Additionally, individuals with chronic kidney disease exhibit a significantly increased risk of SICH, even after adjusting for other covariates, possibly due to microvascular pathology and platelet dysfunction.

Hematoma volume has been extensively studied as a determinant of perihematomal edema (PHE) progression, with larger hematomas typically associated with more robust thrombin cascade activation, increased red blood cell lysis, and greater cytotoxic effects [43,44]. Some evidence suggests that surgical hematoma evacuation can slow PHE growth, potentially by reducing the overall burden of hemorrhagic degradation products [45,46]. However, Sprügel et al proposed that hematoma surface area, rather than absolute volume, is the key determinant of PHE progression. Smaller and irregularly shaped hematomas tend to have a higher relative surface area, leading to greater PHE volume per unit of hematoma surface area [47]. Consequently, even small, irregularly shaped ICHs can exhibit disproportionately high PHE, despite their smaller absolute volumes. Emerging neuroimaging markers, including the blend sign, black hole sign, and island sign on computed tomography imaging, have been identified as potential predictors of hematoma expansion [48]. These markers have also been correlated with acute-phase PHE formation [49], although current evidence does not establish a direct linear relationship between hematoma growth and PHE progression. Additionally, differences in PHE volume between lobar and deep ICH remain controversial. Some studies suggest that lobar ICH exhibits faster initial PHE growth [47], while others report no significant differences in peak PHE volume between lobar and deep hemorrhages after adjusting for hematoma size [47]. Given that cerebral amyloid angiopathy is predominantly associated with lobar ICH and exhibits distinct antithrombotic and fibrinolytic characteristics, the PHE response in lobar hemorrhages can vary based on hematoma morphology and patient heterogeneity. Baseline neurological function, assessed via the NIH Stroke Scale or Glasgow Coma Scale, has been strongly associated with PHE progression [44]. The effect of age on PHE remains debated. Some studies identify advanced age as an independent risk factor for PHE [50], while others suggest that younger patients are more prone to delayed PHE, potentially due to age-related differences in cerebral atrophy [51]. Sex-based differences in PHE have also been reported, with some studies suggesting that female patients exhibit smaller or slower-growing PHE, possibly due to estrogen-mediated neuroprotection against iron-induced oxidative stress. However, findings on this topic remain inconsistent [52]. Uncontrolled hypertension is a well-established risk factor for hematoma expansion [53,54] and has been investigated as a potential therapeutic target for PHE. The INTERACT trial demonstrated that a history of hypertension was positively correlated with relative PHE growth, whereas lower admission systolic BP was associated with absolute PHE growth. The ATACH-2 trial further confirmed that intensive BP reduction within 24 h reduced relative PHE growth rates [55]. However, whether this effect directly results from hematoma containment or is mediated through other mechanisms remains unclear. Laboratory biomarkers have also been explored in relation to PHE progression, including hyperglycemia, MMP-9, MMP-3, and leukocyte counts [44,50]. Hyperglycemia has been postulated to exacerbate blood-brain barrier disruption via oxidative stress, although some researchers argue that it primarily reflects a stress response to severe ICH. Elevated red blood cell counts and hematocrit levels have been linked to delayed peak PHE, possibly due to the release of red blood cell degradation products following hematoma lysis, which can aggravate edema formation. Coagulation abnormalities also play a role, with prolonged activated partial thromboplastin time indicating excessive clotting factor consumption, which can impair vascular integrity and exacerbate edema formation [50]. The apolipoprotein E genotype has been associated with lobar ICH, although findings remain inconsistent. In summary, the risk of SICH is influenced by a complex interplay of non-modifiable factors (eg, age, sex, cerebral amyloid angiopathy, and ethnicity) and traditional modifiable risk factors (eg, hypertension, smoking, alcohol consumption, and dyslipidemia). Moreover, medication use (anticoagulants, antiplatelets, and sympathomimetics), chronic kidney disease, and various laboratory biomarkers further contribute to hemorrhagic susceptibility. PHE is a multifactorial process influenced by hematoma volume, surface area, neuroimaging markers, and baseline patient characteristics. Understanding these potential risk factors and their mechanistic roles in PHE development is crucial for improving early intervention strategies and personalized therapeutic approaches, ultimately reducing the morbidity and mortality associated with SICH.

TyG Index and Metabolic Syndrome

CALCULATION PRINCIPLE OF THE TYG INDEX:

The TyG index was first introduced in 2008 as a quantitative assessment of the interaction between triglyceride and glucose metabolism. It is calculated using the formula, TyG index=ln [(triglycerides×fasting glucose)/2], in which triglycerides and fasting glucose are measured in mg/dL. This index has been proposed as a surrogate marker of insulin resistance, as it reflects the metabolic interplay between lipid and glucose homeostasis. A large cross-sectional study conducted in a metabolically healthy population demonstrated that the TyG index exhibited higher sensitivity than the traditional homeostatic model assessment for insulin resistance (HOMA-IR) index in identifying insulin resistance, although its specificity was relatively lower [5]. Subsequently, Guerrero-Romero et al evaluated individuals across different weight categories and glucose tolerance statuses, revealing that the TyG index demonstrated high sensitivity and superior specificity, compared with the “normal glucose-high insulin clamp” criterion standard for assessing insulin resistance. This further supported its clinical feasibility in insulin resistance detection [56]. Since then, a series of longitudinal studies, including the work of Lee et al, have indicated a significant association between the TyG index and the development of diabetes and its complications. These findings underscore its potential utility in evaluating insulin resistance, predicting diabetes onset, and identifying high-risk populations [57]. Moreover, the TyG index has shown strong correlations with various components of metabolic syndrome, including obesity, hypertension, hypertriglyceridemia, and low high-density lipoprotein cholesterol levels. Some researchers have suggested that the TyG index can also serve as a predictive marker for cardiovascular disease. Large-scale prospective cohort studies have confirmed a positive correlation between the TyG index and the incidence of coronary artery disease, cerebrovascular disease, and peripheral arterial disease. In medical diagnostics, a simple and cost-effective biomarker is particularly valuable for early disease screening. Since the TyG index requires only fasting triglyceride and glucose measurements, it presents a practical and straightforward alternative, without necessitating additional insulin assessments. While multiple meta-analyses have summarized its effectiveness in predicting and diagnosing various diseases, methodological discrepancies, sample size variations, and heterogeneity in patient characteristics across different studies remain substantial challenges. Overall, the TyG index stands out as an easily obtainable and practical measure of insulin resistance, with broad relevance to multiple metabolic disorders. However, further large-scale prospective studies and evidence-based analyses are needed to enhance its specificity, reduce false-positive detection rates, and optimize its applicability across diverse populations in clinical practice.

TYG INDEX AS AN EARLY INDICATOR OF METABOLIC ABNORMALITIES:

The TyG index, a composite marker based on triglyceride and fasting blood glucose levels, has recently been recognized as an early indicator of metabolic abnormalities. Its development stems from the increasing prevalence of metabolic syndrome and the clinical need for a simple yet effective method for detecting insulin resistance. Metabolic syndrome is characterized by central obesity, impaired glucose tolerance, hypertension, and dyslipidemia [58], and has a rapidly rising prevalence worldwide [59]. It is closely linked to increased morbidity and mortality from cardiovascular disease, type 2 diabetes, and non-alcoholic fatty liver disease. Since insulin resistance plays a pivotal role in the pathogenesis of metabolic syndrome, the hyperinsulinemic-euglycemic clamp test, despite being the criterion standard for insulin resistance assessment, is impractical for large-scale application, due to its high cost and technical complexity. In this context, the TyG index, which can estimate insulin resistance levels using a simple measurement of fasting glucose and triglycerides, provides significant value in the early identification of individuals at risk for metabolic syndrome. Studies have reported that the TyG index exhibits stronger correlations with the hyperinsulinemic clamp test than traditional insulin resistance markers [60] and has demonstrated robust predictive value for metabolic syndrome and diabetes risk in cohort studies. In a longitudinal study of 5354 middle-aged Koreans, Lee et al found that individuals in the highest quartile of the TyG index had a 4-fold increased risk of developing diabetes, compared with those in the lowest quartile [61]. Additionally, in patients with coronary heart disease, glucose and lipid metabolism dysfunction accelerates the progression of atherosclerosis, leading to greater coronary artery stenosis [62,63]. The TyG index has shown notable accuracy in predicting cardiovascular disease across multiple parameters [6,64,65] and has been strongly associated with carotid plaque formation and multivessel coronary artery disease [66]. Further evidence suggests that in patients with diabetes, the TyG index is particularly effective in identifying multivessel coronary artery stenosis, whereas its predictive value for coronary disease severity is relatively limited in individuals with normal glucose tolerance or impaired glucose tolerance [67]. This difference underscores the need to optimize the clinical application of the TyG index based on individual metabolic status. Meanwhile, insulin resistance is considered a key pathological mechanism in cardiometabolic diseases, contributing to atherosclerosis progression via oxidative stress, chronic inflammation, and endothelial dysfunction [68,69]. Studies indicate that under insulin resistance conditions, increased lipolysis leads to elevated free fatty acid levels, further disrupting glucose-lipid homeostasis and perpetuating hyperglycemia and hypertriglyceridemia in a vicious cycle [70]. Thus, the TyG index can serve as an important clinical tool for identifying high-risk individuals with underlying metabolic dysfunction before overt disease manifestations, facilitating earlier lifestyle interventions and targeted therapeutic strategies. However, despite accumulating evidence supporting its sensitivity and specificity in evaluating cardiovascular disease, diabetes, and various metabolic disorders, methodological heterogeneity and population differences across studies necessitate careful interpretation in clinical practice. The TyG index should be integrated with overall metabolic profiles, BP control status, and other risk factors for comprehensive risk assessment. As large-scale prospective studies and multicenter validations continue to expand, refining the precise application and interpretation of the TyG index across diverse populations and disease contexts remains a critical area for future research and clinical translation.

Potential Association Between SICH and the TyG Index

ADVANCES IN RESEARCH ON THE TYG INDEX IN CEREBROVASCULAR DISEASES:

Cerebrovascular diseases are a leading cause of mortality and disability worldwide, resulting from pathological changes in cerebral vasculature, including vascular occlusion or stenosis, vessel rupture, vascular malformations, endothelial injury, and altered vascular permeability. Reports indicate that healthcare expenditures for cerebrovascular diseases surpass those of other vascular conditions, and without timely prevention, overall healthcare costs are projected to double. Stroke, the most prevalent clinical manifestation of cerebrovascular disease, imposes a substantial economic and social burden on global healthcare systems [71]. According to the Global Burden of Disease Study, stroke accounts for 11.6% of all deaths, ranking as the second leading cause of mortality and the third most common cause of disability worldwide [72]. While stroke mortality rates have declined in some countries, the prevalence and disability-adjusted life years associated with stroke continue to rise [72,73]. Given this global impact, investigating the pathophysiological mechanisms underlying cerebrovascular diseases and identifying novel risk biomarkers are of paramount importance. Emerging evidence has established a strong association between insulin resistance and various cerebrovascular risk factors and pathological mechanisms, including atherosclerosis, carotid plaques, hyperglycemia, dyslipidemia, and coronary artery disease [68,74]. While hyperinsulinemic-euglycemic clamp testing and the HOMA-IR remain standard methods for insulin resistance evaluation, their complexity and high costs limit widespread clinical application. The TyG index has emerged as a simple, cost-effective, and stable surrogate marker for insulin resistance. Several studies have reported associations between the TyG index and stroke, carotid atherosclerosis, microvascular and macrovascular damage, and coronary artery disease [75], although some studies have not found significant correlations between the TyG index and carotid plaques or intracranial hemorrhage [76]. This discrepancy highlights the need for further investigation to clarify the role of the TyG index in cerebrovascular pathology. A recent meta-analysis assessing the relationship between the TyG index and cerebrovascular disease concluded that higher TyG levels are significantly associated with increased cerebrovascular disease risk, with evidence suggesting a potential linear dose-response relationship. The underlying pathophysiological mechanisms linking insulin resistance and cerebrovascular events may involve the activation of inflammatory pathways, disruption of insulin signaling at the endothelial level, oxidative stress, chronic inflammation, and endothelial dysfunction, all of which contribute to vascular remodeling impairment and cerebrovascular events [74]. Additionally, insulin resistance is implicated in platelet aggregation, enhanced pro-inflammatory and pro-thrombotic states, and impaired fibrinolysis, thereby accelerating atherosclerotic plaque formation and rupture [77]. Insulin resistance also exacerbates the detrimental effects of dyslipidemia, diabetes, and smoking on cerebrovascular health [78]. These findings support the potential role of the TyG index as a biomarker for cerebrovascular disease development and progression.

Further studies have demonstrated a direct association between the TyG index and traditional cerebrovascular risk factors, including dyslipidemia, diabetes, smoking, LDL-C levels, and high-sensitivity C-reactive protein [79]. In population-based stratification studies, the association between the TyG index and stroke or carotid plaques was particularly pronounced, with higher TyG levels correlating with significantly increased stroke risk, compared with lower TyG levels [76,80]. In Asian populations, a high TyG index has been linked to an elevated risk of cerebrovascular diseases, potentially due to dietary patterns characterized by high carbohydrate intake and limited insulin secretory capacity [81–83]. Additionally, studies have highlighted that younger individuals with excessive caloric intake and sedentary lifestyles are more prone to insulin resistance and metabolic dysregulation, making the TyG index an even more relevant predictor of cerebrovascular risk in this demographic [84,85]. Conversely, in older adults, the presence of age-related complications, such as hypertension and vascular stiffness, can attenuate the influence of the TyG index on cerebrovascular risk. Beyond its role in cerebrovascular disease onset, the TyG index has been associated with severe neurological impairment and in-hospital mortality. A recent study in critically ill cerebrovascular patients in intensive care units (ICUs) identified the TyG index as a predictor of both the consciousness level and in-hospital mortality [86]. The proposed mechanisms underlying this relationship include hyperviscosity syndrome, increased cerebral edema, and metabolic toxicity, with insulin resistance exacerbating neurological deterioration via multiple signaling pathways, potentially leading to consciousness disturbances ranging from mild somnolence to profound coma. Furthermore, in patients with type 2 diabetes, hyperglycemia is independently associated with an increased cerebrovascular event risk, and both insulin resistance and β-cell dysfunction contribute additively to cardiovascular risk. Thus, using the TyG index as a surrogate for insulin resistance can provide valuable insights for identifying high-risk individuals and facilitating early intervention strategies. However, several limitations must be acknowledged in the current research landscape. First, most studies have been conducted in specific geographic regions (eg, U.S. cohorts), limiting generalizability. Second, confounding variables, such as dietary patterns, physical activity, and long-term medication use, have not been fully accounted for in some studies. Third, the reliance on International Classification of Diseases coding for patient history retrieval can introduce selection bias and incomplete records. Lastly, small sample sizes in certain studies can affect statistical power and reproducibility, underscoring the need for larger cohort studies to validate findings. Despite these limitations, accumulating evidence suggests that the TyG index not only predicts cerebrovascular disease onset but also plays a role in disease progression and prognostic assessment. This presents a novel avenue for clinical decision-making and prevention strategies. Future research should focus on large-scale, multicenter, multi-ethnic prospective studies to refine the clinical applicability and mechanistic understanding of the TyG index in cerebrovascular diseases, ultimately contributing to reducing the global burden of stroke and related vascular disorders through evidence-based approaches.

ASSOCIATION BETWEEN THE TYG INDEX AND THE RISK OF ICH:

Most previous studies on the TyG index have primarily focused on ischemic stroke, demonstrating significant associations with ischemic stroke incidence, recurrence, and mortality [87,88]. However, the relationship between the TyG index and hemorrhagic stroke, particularly in terms of its onset and prognosis, remains insufficiently explored. Existing evidence suggests that insulin resistance can play a critical role in ICH and SAH, two severe forms of hemorrhagic stroke [89]. First, hyperglycemia, a hallmark feature of insulin resistance, has been shown to exacerbate cerebral edema and secondary brain injury in the early stages of ICH and SAH. This occurs through inhibition of aquaporin-4, increased brain water content, and disruption of the blood-brain barrier [90]. More importantly, hyperglycemia induces superoxide production and inflammatory responses, which expand the hemorrhagic lesion, impair neuronal autophagy, and increase neurotoxicity [91,92]. Second, insulin resistance disrupts cerebral autoregulation, leading to increased myogenic tone in distal cerebral arteries, reduced vascular lumen diameter, and subsequent cerebral hypoperfusion [93]. In ICH, the acute elevation of intracranial pressure and hematoma expansion already contribute to a decline in cerebral perfusion pressure; thus, insulin resistance-induced autoregulation dysfunction further exacerbates cerebral hypoperfusion, worsening neurological deficits and clinical outcomes. Moreover, the bidirectional interaction between insulin resistance and chronic inflammation may be a key contributor to secondary brain injury in hemorrhagic stroke. Higher TyG index levels are indicative of more pronounced systemic and central nervous system inflammation [6,88]. Notably, some studies have examined the predictive value of the TyG index in critically ill patients with ICH or SAH, revealing that higher TyG levels are positively associated with in-hospital and ICU all-cause mortality. This association is particularly evident in specific subgroups, such as patients over 60 years old or those with hypertension but without diabetes [89]. This phenomenon may be attributed to age-related decline in cerebrovascular reserve capacity and the absence of systematic metabolic management in non-diabetic individuals, making them more vulnerable to insulin resistance-driven hyperglycemia, inflammation, and vascular pathology [88]. Conversely, among patients with diagnosed diabetes, the predictive ability of the TyG index for adverse outcomes appears weaker, potentially due to the effects of insulin therapy, oral hypoglycemic agents, and lifestyle interventions, which can result in comparable or even better metabolic profiles (eg, fasting blood glucose, fasting triglycerides, and TyG index) than those of non-diabetic individuals [6]. This observation supports the hypothesis of “reverse causality”, wherein the metabolic control in patients with diabetes mitigates the association between the TyG index and clinical outcomes. With the advancement of multimodal monitoring and large-scale clinical databases, researchers have begun investigating the dynamic changes in the TyG index and its correlation with key parameters such as hematoma volume, hemorrhage location, and cerebral perfusion metrics. However, large-scale, multicenter, prospective studies are still lacking to fully elucidate the cumulative effect of the TyG index on ICH outcomes across different stages of disease progression. Additionally, the influence of pharmacological interventions – including insulin therapy, fibrates, and glucose infusion – on TyG index fluctuations requires further well-designed cohort studies for quantitative assessment. In conclusion, retrospective and preliminary prospective studies indicate that the TyG index holds promise as a risk stratification tool for critically ill patients with ICH and SAH. Future research integrating hematoma location, volume, and dynamic changes in the TyG index may further enhance its clinical predictive utility, offering new perspectives for early intervention strategies to improve the prognosis of hemorrhagic stroke patients.

Application of the TyG Index in Early Prediction of SICH

Research Evidence on the TyG Index in Early Prediction of SICH

LARGE-SCALE POPULATION AND CRITICALLY ILL PATIENT STUDIES: Observational studies based on nationwide databases have indicated that elevated TyG index levels are significantly associated with an increased risk of atherosclerotic cardiovascular disease, coronary artery disease, stroke, and other cerebrovascular events [6,94]. In subgroup analyses of ICU and critically ill stroke patients, higher TyG index levels have shown a positive correlation with in-hospital mortality and severe complications, including neurological deterioration and consciousness impairment [76,95].

DYNAMIC OR NONLINEAR RELATIONSHIPS: Several studies suggest that the association between the TyG index and adverse outcomes follows a “U-shaped” or “J-shaped” curve, indicating that excessively high and excessively low fasting glucose or triglyceride levels can negatively impact ICH outcomes [96]. These findings imply that maintaining the TyG index within an optimal range can be more beneficial in reducing ICH risk.

SYNERGISTIC PREDICTION WITH TRADITIONAL RISK FACTORS:

Insulin resistance interacts with hypertension, diabetes, and dyslipidemia, amplifying the detrimental effects on cerebral vasculature and increasing the risk of hemorrhagic stroke. Integrating the TyG index into comprehensive predictive models may enhance the early identification of high-risk ICH populations more effectively than assessing BP or glucose levels alone.

EARLY WARNING AND RISK STRATIFICATION: Monitoring the TyG index can aid in identifying individuals at high risk for hemorrhagic stroke, particularly among patients with hypertension, diabetes, metabolic syndrome, or suspected insulin resistance. In emergency and ICU settings [89], a markedly elevated TyG index should raise concern for hematoma expansion, worsening consciousness impairment, and other complications. Clinically, this warrants enhanced BP control, lipid-lowering interventions, and glucose management strategies to mitigate adverse outcomes.

COMPREHENSIVE INTERVENTION STRATEGIES: With increasing evidence supporting the role of insulin resistance as a key pathological mechanism in cerebrovascular disease, appropriate glucose and lipid regulation has emerged as a potential therapeutic target [97,98]. In critically ill ICH patients, timely and individualized administration of antidiabetic medications or nutritional support may help limit hematoma expansion and improve neurological outcomes.

Research Limitations and Future Directions

Most existing studies are retrospective or observational, making it difficult to establish causal relationships or quantify the differential impact of insulin resistance on various ICH subtypes (eg, lobar hemorrhage vs basal ganglia hemorrhage) [99]. Additionally, ethnic, dietary, and pharmacological variations can influence TyG index levels. Future research should focus on large-scale, multicenter, prospective trials to refine the clinical utility of the TyG index in early ICH prediction and explore its interactions with neuroimaging parameters (eg, hematoma volume and diffusion coefficient) and therapeutic interventions. Current evidence underscores the strong correlation between the TyG index and insulin resistance, highlighting its sensitivity in detecting metabolic dysregulation and its cerebrovascular consequences. In SICH, early assessment of the TyG index may facilitate prediction of hematoma expansion, worsening neurological status, and in-hospital mortality, providing valuable guidance for early intervention and preventive strategies [86]. With further large-scale validation studies, the TyG index could become a widely applicable tool for early risk assessment in spontaneous intracerebral hemorrhage, offering new insights into reducing ICH-related mortality and disability rates.

Conclusions

The TyG index, derived from routine fasting blood glucose and triglyceride levels, is a simple, cost-effective, and reliable surrogate marker of insulin resistance. Growing evidence supports its association with atherosclerotic cardiovascular disease, ischemic stroke, and adverse cerebrovascular outcomes. In the context of SICH, insulin resistance is increasingly recognized as a key contributor to disease progression through mechanisms such as hyperglycemia, dyslipidemia, endothelial dysfunction, and oxidative stress, which aggravate microvascular injury and blood-brain barrier disruption. By reflecting glucose and lipid metabolism abnormalities, the TyG index offers a sensitive marker of vascular vulnerability in these patients. Clinically, the TyG index can complement traditional risk factors, aiding in the early identification of high-risk SICH patients, particularly in acute or ICU settings. Elevated TyG levels can signal increased risks of hematoma expansion, neurological deterioration, and poor outcomes, thereby guiding timely metabolic interventions. Although further prospective multicenter studies are needed to establish causality and define its applicability across diverse populations and hemorrhage subtypes, current evidence supports the TyG index as a promising tool in the early risk assessment and management of SICH. With advancing understanding of insulin resistance, the TyG index is poised to play an increasingly important role in reducing SICH-related morbidity and mortality.