Predictive Value of the Modified Comprehensive Immunoinflammatory Indices for Hemorrhagic Transformation in Ischemic Stroke Patients Undergoing Thrombolysis: A Retrospective Study

Introduction

Cerebral infarction, also known as ischemic stroke, is a localized ischemic necrosis or softening of brain tissue caused by blood circulation disorders in the brain, resulting in ischemia and hypoxia.¹ Its pathogenesis is complex, mainly including atherosclerosis, thrombosis, and embolism. These factors can lead to blockage of cerebral blood vessels, causing local brain tissue to lose blood supply and subsequently triggering neurological deficits.^2,3 Clinically, patients often present with sudden limb weakness, slurred speech, facial numbness, visual impairment, and so on. In severe cases, coma or even death may occur.^4,5 Epidemiological data show that cerebral infarction has become one of the main causes of death and disability worldwide.⁶

Intravenous thrombolysis is currently one of the most effective treatment methods for the early stage of acute cerebral infarction.^7,8 Especially intravenous thrombolysis with recombinant tissue plasminogen activator (rt-PA), by activating plasminogen to convert into plasmin, dissolving thrombus, restoring blood perfusion of brain tissue in the infarcted area, and saving the ischemic penumbra, thereby improving the neurological function of patients.^9,10 However, although thrombolytic therapy has brought new hope to patients with cerebral infarction, the clinical prognosis is still not optimistic. Relevant studies have shown that among patients who receive intravenous thrombolysis, only 30% to 50% can achieve good clinical outcomes.^11–13

Hemorrhagic transformation (HT) after thrombolysis for cerebral infarction refers to the phenomenon where blood exudation or hematoma formation occurs in the infarcted area or surrounding tissues in patients with acute cerebral infarction after thrombolysis therapy.¹⁴ According to whether it is accompanied by neurological deterioration, HT can be classified into asymptomatic hemorrhage transformation (aHT) and symptomatic hemorrhage transformation (sHT).¹⁵ aHT may cause brain tissue edema to worsen and trigger inflammatory responses, leading to long-term decline in cognitive function and delayed recovery of neurological function in patients,¹⁶ while sHT patients often experience acute neurological deterioration such as impaired consciousness and aggravated limb paralysis, with a high mortality rate.¹⁷ The occurrence of HT is a complex pathological process mediated by the imbalance among ischemic injury, the effects of thrombolytic drugs, and vascular repair.¹⁸ After the occurrence of cerebral infarction, the ischemia and hypoxia in the brain tissue will first cause damage to the endothelial cells of the cerebral blood vessels.¹⁹ Excessive activation of the fibrinolytic system significantly reduces the local blood coagulation ability, making it difficult for damaged blood vessels to achieve self-repair through the coagulation mechanism.²⁰ Reperfusion of blood flow will have a “flushing effect” on the damaged blood vessel walls, thereby exacerbating the damage to the vessels.²¹ The occurrence of hemorrhagic transformation after thrombolysis for cerebral infarction is influenced by multiple risk factors.¹⁴

After cerebral infarction occurs, the body immediately initiates an inflammatory response.¹⁹ This process plays a complex and crucial role in the pathological process of cerebral infarction and is closely related to the HT after thrombolysis.²² In the acute stage of cerebral infarction, ischemia and hypoxia trigger a local inflammatory cascade reaction. A large number of inflammatory cells, such as neutrophils and monocytes, rapidly recruit to the infarcted area and release pro-inflammatory cytokines such as tumor necrosis factor -α (TNF-α) and interleukin-6 (IL-6).²³ These cytokines not only aggravate local brain tissue damage, but also disrupt the integrity of the blood-brain barrier, laying hidden dangers for HT.

The dynamic balance of inflammatory response, immune status, and nutritional status plays a crucial role in the occurrence, development and prognosis of cerebral vessel disease.²⁴ And the thrombolytic treatment process can lead to inflammatory responses, coagulation dysfunction and changes in the patient’s nutritional status within their body.^25,26 Some composite immune-inflammation indices integrate the counts of different immune cell subsets, coagulation-related parameters, or organ function indicators to more systematically capture the interaction between the immune system and inflammation in the body, providing a more comprehensive biological basis for disease risk assessment. A series of new inflammatory immune indices based on the combination of peripheral blood cell counts and laboratory indicators have emerged, such as the modified pan-immune-inflammation-value (mPIV), modified systemic immune-inflammatory index (mSII), and modified systemic inflammatory response index (mSIRI), have gradually become research hotspots.^27,28 The pathological mechanisms of stroke and hemorrhagic transformation after thrombolysis (such as ischemia-reperfusion injury, disruption of the blood-brain barrier, and inflammatory-coagulation interaction activation) are highly consistent with the dimensions of the modified immune index (such as the synergistic effect of nutritional status - coagulation - inflammation).^29–31 As new inflammatory immune indicators, at present, the predictive value of mPIV, mSII, and mSIRI in the hemorrhagic transformation of patients with ischemic stroke undergoing thrombolysis remains unclear. The purpose of this study is to solve this problem.

Materials and Methods

Participants

A retrospective analysis was conducted on 894 patients with acute cerebral infarction who received intravenous thrombolysis and were continuously recorded in Meizhou People’s Hospital from January 2019 to May 2024. All the subjects received intravenous thrombolytic therapy within 5 hours. The intravenous thrombolysis method refers to the “Chinese Stroke Association guidelines for clinical management of ischaemic cerebrovascular diseases”.³²

Inclusion criteria: (1) patients diagnosed with CI accordance with the criteria of the Chinese Guidelines for Ischemic Stroke;³³ (2) age ≥18 years old; (3) patients who meet the indications for intravenous thrombolysis in the “Chinese Stroke Association guidelines for clinical management of ischaemic cerebrovascular diseases”³² (4) patients who underwent cranial CT or MRI reexamination after thrombolysis; and (5) the patients’ admission information were complete. Exclusion criteria: (1) patients who undergo arterial thrombolysis or arterial thrombectomy through cerebral vascular intervention; (2) patients received bridging therapy or surgical decompression; (3) patients without subsequent imaging or insufficient clinical data for analysis; and (4) patients whose laboratory indicators are significantly affected due to severe diseases or organ function impairment. This study was supported by the Ethics Committee of the Meizhou People’s Hospital. The flowchart of present study is shown in Figure 1.

Figure 1 The flowchart of this study.

Data Collection

The clinical data of the patients were collected, including gender, age, hypertension, diabetes mellitus, laboratory data (triglyceride, albumin, platelet, neutrophil, and lymphocyte) and imaging data.

The calculation of mPIV, mSII, and mSIRI:

mPIV=triglyceride×neutrophil×platelet/lymphocyte;

mSII=platelet×neutrophil/lymphocyte×ln(albumin);

mSIRI=platelet×neutrophil/lymphocyte.

Hemorrhagic transformation:³⁴ No hemorrhage was found in the first head computed tomography (CT)/magnetic resonance imaging (MRI) after cerebral infarction, but intracranial hemorrhage was detected in the second head CT/MRI examination, or hemorrhagic infarction can be determined based on the first head CT/MRI.

Statistical Analysis

All statistical analysis were performed using SPSS statistical software version 26.0 (IBM Inc., USA). Continuous variables were compared using t-test or Mann–Whitney U-test. The comparison of categorical variables was conducted using the Chi-square test. The specificity and sensitivity of mPIV, mSII, and mSIRI were described using the receiver operating characteristic (ROC) curve analysis. The accuracy of mPIV, mSII, and mSIRI in differentiating HT was evaluated by calculating the area under the ROC curve (AUC), and the optimal cut-off values of mPIV, mSII, and mSIRI were determined using the Youden index. Logistic regression analysis was used to evaluate the relationship between mPIV, mSII, mSIRI and HT adjusting for other influencing factors, such as gender, age, hypertension, and diabetes mellitus p<0.05.

Results

Clinical Features of the Ischemic Stroke Patients Performed Thrombolysis

A total of 894 ischemic stroke patients were included in this study, including 648 (72.5%) male and 246 (27.5%) female patients. Among them, 663 (74.2%), and 293 (32.8%) patients had hypertension, and diabetes mellitus, respectively. The mean levels of triglyceride, neutrophil count, platelet count, lymphocyte count, and albumin was 1.37 (0.96, 1.96) mmol/L, 5.80 (4.30, 7.76) ×10⁹/L, 214.50 (179.00, 249.25) ×10⁹/L, 1.63 (1.20, 2.21) ×10⁹/L, and 40.90 (38.08, 43.60) g/L, respectively. The median levels of mPIV, mSII, and mSIRI was 1041.12 (617.55, 2073.74), 2657.62 (1703.10, 4524.08), and 722.37 (463.49, 1239.76) in all patients, respectively. There were 685 (76.6%) patients without HT and 209 (23.4%) with HT (Table 1).

Table 1 The Clinical Features of the Ischemic Stroke Patients Performed Thrombolysis

Comparison of Clinical Features Among HT and Non-HT Patients

The cases with HT had higher mPIV (1337.71 (698.79, 2511.19) vs 992.37 (599.30, 1884.53), p=0.001), mSII (3418.31 (1895.87, 7112.89) vs 2574.81 (1630.46, 4006.18), p<0.001), and mSIRI level (963.60 (517.86, 1947.87) vs 698.75 (446.99, 1100.62), p<0.001) than those without HT, respectively (Table 2 and Figure 2). There was no statistically significant difference in the distribution of gender, age, hypertension and diabetes between the two groups of patients (Table 2).

Table 2 Comparison of Clinical Features Among Hemorrhagic Transformation (HT) and Non-HT Patients

Figure 2 Comparison of mPIV (A), mSII (B), and mSIRI (C) in ischemic stroke patients with or without hemorrhagic transformation. Abbreviations: mPIV, modified pan-immune-inflammation-value; mSII, modified systemic immune-inflammatory index; mSIRI, modified systemic inflammatory response index.

ROC Analysis

ROC analysis showed that the cutoff value of mPIV was 1302.4 (sensitivity 50.7%, specificity 64.7%, area under the ROC curve (AUC): 0.575) (95% confidence interval (CI), 0.529–0.620), the mSII cutoff value was 3186.5 (sensitivity 54.5%, specificity 63.8%, AUC: 0.605) (95% CI, 0.558–0.652), and the mSIRI cutoff value was 996.5 (sensitivity 49.8%, specificity 70.2%, AUC: 0.610) (95% CI, 0.563–0.657) when mPIV, mSII, and mSIRI were used as predictive indicators of HT (Figure 3).

Figure 3 ROC analysis of mPIV, mSII, and mSIRI used in the prediction of hemorrhagic transformation in ischemic stroke patients performed thrombolysis. Abbreviations: mPIV, modified pan-immune-inflammation-value; mSII, modified systemic immune-inflammatory index; mSIRI, modified systemic inflammatory response index.

Logistic Regression Analysis of the Relationship Between mPIV, mSII, mSIRI and Hemorrhagic Transformation

Univariate analysis showed that high mPIV (odds ratio (OR): 1.884, 95% confidence interval (CI): 1.377–2.577, p<0.001), high mSII (OR: 2.115, 95% CI: 1.545–2.894, p<0.001), and high mSIRI (OR: 2.335, 95% CI: 1.701–3.206, p<0.001) were significantly associated with hemorrhagic transformation. Multivariate logistic regression analysis showed that high mPIV (OR: 1.901, 95% CI: 1.381–2.617, p<0.001), high mSII (OR: 2.081, 95% CI: 1.517–2.854, p<0.001), and high mSIRI (OR: 2.290, 95% CI: 1.664–3.151, p<0.001) were significantly associated with hemorrhagic transformation (Table 3).

Table 3 Logistic Regression Analysis of the Relationship Between mPIV, mSII, mSIRI and Hemorrhagic Transformation

Discussion

These modified immunoinflammatory indices is a comprehensive indices that combines nutritional status, coagulation, and inflammation. This study aimed to explore the associations between mPIV, mSII, mSIRI and hemorrhagic transformation in patients with acute ischemic stroke who received thrombolytic therapy. And the results found that the cases with HT had higher mPIV, mSII, and mSIRI levels than those without HT. After adjusting for other influencing factors, such as gender, age, hypertension, and diabetes mellitus, this study found that mPIV, mSII, and mSIRI still maintained their independent predictive value for HT, and there were significant interaction effects among these factors. It provides a new perspective for clinical risk assessment.

During thrombolytic therapy for ischemic stroke, the interaction between inflammation and thrombosis constitutes an important pathological basis for the occurrence and development of hemorrhagic transformation.^35,36 When embolism occurs in the cerebral blood vessels, local tissue ischemia and hypoxia rapidly activate the inflammatory response.³⁷ A large amount of pro-inflammatory cytokines are released, such as TNF-α and IL-6,^38,39 promoting the expression of adhesion molecules by vascular endothelial cells,⁴⁰ attracting the aggregation of inflammatory cells such as neutrophils and monocytes,^41,42 and destroying the integrity of the blood-brain barrier.⁴³ The injury of the blood-brain barrier makes the blood components in the recanalized blood vessels after thrombolysis more likely to leak out, directly increasing the risk of HT.^18,44

The dynamic process of thrombosis and dissolution in ischemic stroke further exacerbates the imbalance of the inflammatory response. In the early stage of thrombosis, platelets are activated and release substances such as thromboxane A₂ and adenosine diphosphate,⁴⁵ which not only promote the progression of thrombosis but also activate the complement system and trigger an inflammatory cascade reaction.^46–48 After thrombolytic therapy, plasminogen is activated and converted into fibrinolytic protein, and fibrinolytic protein dissolves blood clots and generates fibrin degradation products (FDP) with anticoagulant effects.⁴⁹ At the same time, it can also stimulate inflammatory cells to secrete more pro-inflammatory factors, leading to a vicious cycle between the coagulation-fibrinolysis system and the inflammatory system,⁵⁰ and ultimately promoting HT at the originally stable thrombi site.

Neutrophils and platelets, as core participants in the inflammatory and coagulation processes,⁵¹ play a key role in the predictive mechanism of mPIV. Neutrophils can release toxic substances such as myeloperoxidase (MPO) and neutrophil elastase (NE), directly damaging the vascular basement membrane.⁵² Simultaneously activate the complement system, induce the inflammatory cascade reaction, and create pathological conditions for HT.^53,54 Platelets play a procoagulant role in the early stage of thrombosis formation. However, their excessive activation can lead to the consumption of coagulation factors and hyperfibrinolysis, and reperfusion injury is prone to occur after thrombolysis.⁵⁵ In this study, the elevated mPIV, mSII, and mSIRI suggested an enhanced synergistic pro-inflammatory and pro-coagulant effect between neutrophils and platelets, indicating a significant increase in the risk of hemorrhagic transformation.

Lymphocytes, as important cells for immune regulation in the body, a decrease in their quantity reflects the state of suppressed immune function.⁵⁶ During the pathological process of ischemic stroke, impaired lymphocyte function can lead to insufficient anti-inflammatory response and fail to effectively curb vascular damage caused by excessive inflammation.⁵⁷ The inclusion of lymphocyte count in mPIV can inversely evaluate the anti-inflammatory repair ability of the body. When the relative value of lymphocytes decreases, the elevated mPIV, mSII, and mSIRI value, further highlighting the intensification of the risk of hemorrhagic transformation.

In this study, mPIV, as a novel parameter integrating lipid metabolism and inflammatory immune indicators, has shown unique value in predicting bleeding transformation in thrombolytic patients with ischemic stroke. Triglycerides (TG) in the mPIV index reflect the lipid metabolism status of the body. High levels of TG can aggravate the dysfunction of vascular endothelial cells and disrupt the integrity of the blood-brain barrier through pathways such as activating protein kinase C and promoting the release of inflammatory factors.⁵⁸ After thrombolytic therapy, the damaged vascular wall is more prone to blood extravasation, thereby increasing the risk of bleeding transformation. It explains the correlation between the TG component in mPIV and bleeding transformation. Albumin is not only a key indicator reflecting the nutritional status of individual,⁵⁹ but also an important vascular endothelial protective factor.⁶⁰ Albumin has the functions of antioxidation, anti-inflammation and maintaining the integrity of the vascular wall.⁶¹ Hypoalbuminemia is often accompanied by intensified inflammatory responses and increased vascular permeability in the body.⁶² After thrombolytic therapy for ischemic stroke, such patients are more prone to exudation of blood components, which in turn leads to HT.⁶³ The mSII provides a new quantitative tool for predicting HT in thrombolytic patients with ischemic stroke by integrating indicators related to coagulation, immunity and nutritional status.

Elevated systemic immune-inflammation index (SII) and systemic inflammatory response index (SIRI) increased the risk of some cardiovascular diseases.⁶⁴ There are some research reports on the relationship between SII, SIRI, pan-immune-inflammation value (PIV) and ischemic stroke. Xu et al found that a high SIRI is associated with an increased risk of stroke among middle-aged and elderly adults in China.⁶⁵ SIRI is a risk factor for ischemic stroke in patients with rheumatoid arthritis.⁶⁶ Elevated PIV and SIRI increase stroke risk in hypertensive individuals.²⁸ Some studies suggested that high SII,^67–69 and SIRI^69–71 are associated with adverse clinical outcomes in ischemic stroke patients. SII,^72–74 SIRI,^72–74 and PIV⁷³ are also associated with the risk of adverse outcomes in patients with acute ischemic stroke after intravenous thrombolytic therapy. This study investigated the relationship between mPIV, mSII, mSIRI and the risk of HT after intravenous thrombolysis in ischemic stroke, while no related research reports had been seen before.

Although high levels of mPIV, mSII, and mSIRI showed association with HT in this study, there are still certain limitations. Firstly, the combination and weights of each parameter in the mPIV, mSII, and mSIRI calculation formula lack clear evidence-based medical evidence support. The influence degree of each index on mPIV, mSII, and mSIRI under different disease backgrounds may vary, and its scientificity awaits further verification. Secondly, this study was a retrospective one, with sample selection bias. Moreover, the synergistic effect of mPIV, mSII, and mSIRI with other important clinical factors (such as patient age, underlying diseases, thrombolysis timing, blood pressure control, and so on) was not fully considered, which may affect the universality of the prediction results. Thirdly, at present, the optimal critical value of mPIV, mSII, and mSIRI in patients with ischemic stroke has not been unified, and there are significant differences among different research results, which limits its wide application in clinical diagnosis and treatment.

Conclusion

Overall, in patients with ischemic stroke who received intravenous thrombolysis treatment, high levels of mPIV, mSII, and mSIRI may be associated with hemorrhagic transformation. Of course, this result still requires more research to be verified. Moreover, these comprehensive indices based on hematological indicators need to be combined with other clinical indicators to improve the efficacy of risk prediction.