Predictors of Symptomatic Intracranial Hemorrhage after Endovascular Thrombectomy in Acute Ischemic Stroke: A Systematic Review and Meta-Analysis

Incidence of intracranial hemorrhagic complications after anterior circulation endovascular thrombectomy in relation to occlusion site: a nationwide observational register study

BACKGROUND

Intracranial hemorrhage (ICH) is a potentially severe complication of endovascular thrombectomy (EVT). However, the relationship between the incidence and severity of ICH and vascular occlusion location is not well described.

OBJECTIVE

To present a comprehensive analysis of subtypes of ICHs and their relationship to the occlusion site following EVT in the anterior circulation.

METHODS

All patients with anterior circulation vessel occlusion stroke (internal carotid (ICA) and middle cerebral artery's first (M1) and later segments (M2 and beyond)) registered in the two Swedish national quality registers for stroke care and endovascular therapy during 2015-2020 were included. Hemorrhagic complications identified on imaging within 36 hours post-EVT were classified according to Heidelberg Bleeding Classification and further divided into symptomatic (sICH) or non-symptomatic (non-sICH).

RESULTS

Of the 3077 patients, ICH frequency was 24.2%, which included 4.5% sICH. Subarachnoid hemorrhage (SAH) was the most frequent subtype of hemorrhage (10.9%). The hemorrhagic subtypes differed significantly by occlusion site, but the frequency of any bleed did not. EVT performed in and beyond the M2 more often resulted in SAH, frequently classified as non-sICH. EVT performed in the ICA was associated with more severe hemorrhages, such as intraventricular and large parenchymal hematomas, that were more often classified as sICH.

CONCLUSION

In this nationwide unselected EVT cohort we found that ICH severity significantly differed between different vessel occlusion sites.

Radiomics of intrathrombus and perithrombus regions for Post-EVT intracranial hemorrhage risk Prediction: A multicenter CT study

OBJECTIVES

This study aimed to assess the predictive performance of radiomics derived from computed tomography (CT) images of thrombus regions in predicting the risk of intracranial hemorrhage (ICH) following endovascular thrombectomy (EVT).

MATERIALS AND METHODS

This retrospective multicenter study included 336 patients who underwent admission CT and EVT for acute anterior-circulation large vessel occlusion between December 2018 and December 2023. Follow-up imaging was performed 24 h post-procedure to evaluate the occurrence of ICH. 230 patients from centers A and B were randomly allocated into training and test groups in a 7:3 ratio, while the remaining 106 patients from center C comprised the validation cohort. Radiologists manually segmenting the thrombus on CT images, and the perithrombus region was defined by expanding the initial region of interest (ROI). A total of 428 radiomics features were extracted from both intrathrombus and perithrombus regions on CT images. The Mann-Whitney U test was used for feature selection, and least absolute shrinkage and selection operator (LASSO) regression was employed for model development, followed by validation using a 5-fold cross-validation approach. Model performance was assessed using the area under the curve (AUC) of the receiver operating characteristic (ROC).

RESULTS

Among the eligible patients, 128 (38.1 %) experienced ICH after EVT. The combined model exhibited superior performance in the training cohort (AUC: 0.913, 95 % CI: 0.861-0.965), test cohort (AUC: 0.868, 95 % CI: 0.775-0.962), and validation cohort (AUC: 0.850, 95 % CI: 0.768-0.912). Notably, in the validation group, both the perithrombus and combined models demonstrated higher predictive accuracy compared to the intrathrombus model (0.837 vs. 0.684, p = 0.02; AUC: 0.850 vs. 0.684, p = 0.01).

CONCLUSIONS

Radiomics features derived from the perithrombus region significantly enhance the prediction of ICH after EVT, providing valuable insights for optimizing post-procedural clinical decisions.

CLINICAL RELEVANCE STATEMENT

This study highlights the importance of radiomics extracted from intrathrombus and perithrombus region in predicting intracranial hemorrhagefollowing endovascular thrombectomy, which can aid in improving patient outcomes.

Predictors of symptomatic intracerebral hemorrhage after endovascular treatment for acute ischemic stroke due to tandem lesion in anterior circulation

BACKGROUND

Endovascular treatment (EVT) of tandem lesion (TL) in the anterior circulation acute ischemic stroke (IS) usually requires periprocedural antithrombotic treatment and early initiation of dual antiplatelet therapy (DAPT) after carotid stenting. However, it may contribute to an occurrence of symptomatic intracerebral hemorrhage (SICH) in some cases. We investigated factors influencing the SICH occurrence and assessed the possible predictors of SICH after EVT.

METHODS

IS patients with TL in the anterior circulation treated with EVT were enrolled in the multicenter retrospective ASCENT study. A good three-month clinical outcome was scored as 0-2 points in modified Rankin Scale (mRS) and recanalization using the TICI scale. SICH was assessed using the SITS-MOST criteria. Logistic regression analysis was used for the assessment of possible predictors of SICH with adjustment for potential confounders.

RESULTS

In total, 300 (68.7 % males, mean age 67.3 ± 10.2 years) patients with median of admission NIHSS 17 were analyzed. Recanalization (TICI 2b-3) was achieved in 290 (96.7 %) patients and 176 (58.7 %) had mRS 0-2. SICH occurred in 25 (8.3 %) patients. Patients with SICH did not differ from those without SICH in the rate of periprocedural antithrombotic treatment (64 vs. 57.5 %, p = 0.526) and in the rate of DAPT started within the first 12 h after EVT (20 vs. 42.2 %, p = 0.087). After adjustment, admission NIHSS and admission glycemia were found as the only predictors of SICH after EVT.

CONCLUSION

Admission NIHSS and glycemia were found as the only predictors of SICH after EVT for TL. No associations between periprocedural antithrombotic treatment, early start of DAPT after EVT and SICH occurrence were found.

The differences of fibrinogen levels in various types of hemorrhagic transformations

Introduction

Hemorrhagic transformation (HT) is a serious complication that can occur spontaneously after an acute ischemic stroke (AIS) or after a thrombolytic/mechanical thrombectomy. Our study aims to explore the potential correlations between fibrinogen levels and the occurrence of spontaneous HT (sHT) and HT after mechanical thrombectomy (tHT).

Methods

A total of 423 consecutive AIS patients diagnosed HT who did not undergone thrombolysis and 423 age- and sex-matched patients without HT (non-HT) were enrolled. Fibrinogen levels were measured within 24 h of admission after stroke. The cohorts were trisected according to fibrinogen levels. The HT were further categorized into hemorrhagic infarction (HI) or parenchymal hematoma (PH) based on their imaging characteristics.

Results

In sHT cohort, fibrinogen levels were higher in HT patients than non-HT patients (p < 0.001 versus p = 0.002). High fibrinogen levels were associated with the severity of HT. HT patients without atrial fibrillation (AF) had higher levels of fibrinogen compared to non-HT (median 3.805 vs. 3.160, p < 0.001). This relationship did not differ among AF patients. In tHT cohort, fibrinogen levels were lower in HT patients than non-HT patients (p = 0.002). Lower fibrinogen levels were associated with the severity of HT (p = 0.004). The highest trisection of fibrinogen both in two cohorts were associated with HT [sHT cohort: OR = 2.515 (1.339-4.725), p = 0.016; that cohort: OR = 0.238 (0.108-0.523), p = 0.003].

Conclusion

Our study suggests that lower fibrinogen level in sHT without AF and higher fibrinogen level in tHT are associated with more severe HT.

Mechanical thrombectomy using the retrograde semi-retrieval technique for patients with underlying intracranial atherosclerotic stenosis

Background

The retrograde semi-retrieval technique (RESET) has been described as a modified technique for endovascular thrombectomy (EVT) whose safety and efficacy for intracranial atherosclerosis stenosis (ICAS) patients remain uncertain. This article presents our single-center experience, comparing RESET vs. non-RESET in ICAS patients.

Materials and methods

We analyzed 327 consecutive ICAS patients who underwent EVT at Tianjin Huanhu Hospital from January 2018 and December 2022. Patients were categorized into two groups: RESET and non-RESET. The primary outcome was the first-pass effect (FPE). Secondary outcomes included successful reperfusion, functional independence at 90 days, mortality, and symptomatic intracranial hemorrhage (sICH).

Results

RESET was significantly associated with FPE [adjusted odds ratio (aOR) 2.00, 95% confidence interval (CI) 1.03-3.87, p = 0.040]. RESET was not significantly associated with successful reperfusion (aOR 1.5, CI 0.55-4.06, p = 0.425), an mRS of 0-2 at 90 days (aOR 1.36, CI 0.83-2.21, p = 0.223), sICH (aOR 0.39, CI 0.12-1.23, p = 0.108), and mortality (aOR 0.49, CI 0.16-1.44, p = 0.193). After propensity score matching, the results were consistent with the primary analysis.

Conclusion

Compared to non-RESET, patients treated with RESET showed increased FPE incidence and significantly decreased puncture-to-reperfusion time. RESET was proven to be safe and effective in enhancing reperfusion for LVO patients receiving EVT with underlying ICAS.

Risk prediction models for intracranial hemorrhage in acute ischemic stroke patients receiving intravenous alteplase treatment: a systematic review

Objectives

To identify and compare published models that use related factors to predict the risk of intracranial hemorrhage (ICH) in acute ischemic stroke patients receiving intravenous alteplase treatment.

Methods

Risk prediction models for ICH in acute ischemic stroke patients receiving intravenous alteplase treatment were collected from PubMed, Embase, Web of Science, and the Cochrane Library up to April 7, 2023. A meta-analysis was performed using Stata 13.0, and the included models were evaluated using the Prediction Model Risk of Bias Assessment Tool (PROBAST).

Results

A total of 656 references were screened, resulting in 13 studies being included. Among these, one was a prospective cohort study. Ten studies used internal validation; five studies used external validation, with two of them using both. The area under the receiver operating characteristic (ROC) curve for subjects reported in the models ranged from 0.68 to 0.985. Common predictors in the prediction models include National Institutes of Health Stroke Scale (NIHSS) (OR = 1.17, 95% CI 1.09-1.25, p < 0.0001), glucose (OR = 1.54, 95% CI 1.09-2.17, p < 0.05), and advanced age (OR = 1.50, 95% CI 1.15-1.94, p < 0.05), and the meta-analysis shows that these are independent risk factors. After PROBAST evaluation, all studies were assessed as having a high risk of bias but a low risk of applicability concerns.

Conclusion

This study systematically reviews available evidence on risk prediction models for ICH in acute ischemic stroke patients receiving intravenous alteplase treatment. Few models have been externally validated, while the majority demonstrate significant discriminative power.

Machine learning-based prediction of symptomatic intracerebral hemorrhage after intravenous thrombolysis for stroke: a large multicenter study

Background

This study aimed to compare the performance of different machine learning models in predicting symptomatic intracranial hemorrhage (sICH) after thrombolysis treatment for ischemic stroke.

Methods

This multicenter study utilized the Shenyang Stroke Emergency Map database, comprising 8,924 acute ischemic stroke patients from 29 comprehensive hospitals who underwent thrombolysis between January 2019 and December 2021. An independent testing cohort was further established, including 1,921 patients from the First People's Hospital of Shenyang. The structured dataset encompassed 15 variables, including clinical and therapeutic metrics. The primary outcome was the sICH occurrence post-thrombolysis. Models were developed using an 80/20 split for training and internal validation. Performance was assessed using machine learning classifiers, including logistic regression with lasso regularization, support vector machine (SVM), random forest, gradient-boosted decision tree (GBDT), and multilayer perceptron (MLP). The model boasting the highest area under the curve (AUC) was specifically employed to highlight feature importance.

Results

Baseline characteristics were compared between the training cohort (n = 6,369) and the external validation cohort (n = 1,921), with the sICH incidence being slightly higher in the training cohort (1.6%) compared to the validation cohort (1.1%). Among the evaluated models, the logistic regression with lasso regularization achieved the highest AUC of 0.87 (95% confidence interval [CI]: 0.79-0.95; p < 0.001), followed by the MLP model with an AUC of 0.766 (95% CI: 0.637-0.894; p = 0.04). The reference model and SVM showed AUCs of 0.575 and 0.582, respectively, while the random forest and GBDT models performed less optimally with AUCs of 0.536 and 0.436, respectively. Decision curve analysis revealed net benefits primarily for the SVM and MLP models. Feature importance from the logistic regression model emphasized anticoagulation therapy as the most significant negative predictor (coefficient: -2.0833) and recombinant tissue plasminogen activator as the principal positive predictor (coefficient: 0.5082).

Conclusion

After a comprehensive evaluation, the MLP model is recommended due to its superior ability to predict the risk of symptomatic hemorrhage post-thrombolysis in ischemic stroke patients. Based on decision curve analysis, the MLP-based model was chosen and demonstrated enhanced discriminative ability compared to the reference. This model serves as a valuable tool for clinicians, aiding in treatment planning and ensuring more precise forecasting of patient outcomes.

Thrombectomy-Capable Stroke Centre-A Key to Acute Stroke Care System Improvement? Retrospective Analysis of Safety and Efficacy of Endovascular Treatment in Cardiac Cathlab

The optimal structure of the acute ischaemic stroke treatment network is unknown and eagerly sought. To make it most effective, different treatment and transportation strategies have been developed and investigated worldwide. Since only a fraction of acute stroke patients with large vessel occlusion are treated, a new entity-thrombectomy-capable stroke centre (TCSC)-was introduced to respond to the growing demand for timely endovascular treatment. The purpose of this study was to present the early experience of the first 70 patients treated by mechanical means in a newly developed cardiac Cathlab-based TCSC. The essential safety and efficacy measures were recorded and compared with those reported in the invasive arm of the HERMES meta-analysis-the largest published dataset on the subject. We found no significant differences in terms of clinical and safety outcomes, such as early neurological recovery, level of functional independence at 90 days, symptomatic intracranial haemorrhage, parenchymal haematoma type 2, and mortality. These encouraging results obtained in the small endovascular centre may be an argument for the introduction of the TCSC into operating stroke networks to increase patient access to timely treatment and to improve clinical outcomes.