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Factors Influencing Recanalization After Mechanical Thrombectomy With First-Pass Effect for Acute Ischemic Stroke: A Systematic Review and Meta-Analysis.

ABSTRACT: Background: First-pass effect (FPE) is increasingly recognized as a predictor of good outcome in large vessel occlusion (LVO). This systematic review and meta-analysis aimed to elucidate the factors influencing recanalization after mechanical thrombectomy (MT) with FPE in treating acute ischemic stroke (AIS). Methods: Main databases were searched for relevant randomized controlled trials (RCTs) and observational studies reporting influencing factors of MT with FPE in AIS. Recanalization was assessed by the modified thrombolysis in cerebral ischemia (mTICI) score. Both successful (mTICI 2b-3) and complete recanalization (mTICI 2c-3) were observed. Risk of bias was assessed through different scales according to study design. The I ² statistic was used to evaluate the heterogeneity, while subgroup analysis, meta-regression, and sensitivity analysis were performed to investigate the source of heterogeneity. Visual measurement of funnel plots was used to evaluate publication bias. Results: A total of 17 studies and 6,186 patients were included. Among them, 2,068 patients achieved recanalization with FPE. The results of meta-analyses showed that age [mean deviation (MD):1.21,95% confidence interval (CI): 0.26-2.16; p = 0.012], female gender [odds ratio (OR):1.12,95% CI: 1.00-1.26; p = 0.046], diabetes mellitus (DM) (OR:1.17,95% CI: 1.01-1.35; p = 0.032), occlusion of internal carotid artery (ICA) (OR:0.71,95% CI: 0.52-0.97; p = 0.033), occlusion of M2 segment of middle cerebral artery (OR:1.36,95% CI: 1.05-1.77; p = 0.019), duration of intervention (MD: -27.85, 95% CI: -42.11-13.58; p < 0.001), time of onset to recanalization (MD: -34.63, 95% CI: -58.45-10.81; p = 0.004), general anesthesia (OR: 0.63,95% CI: 0.52-0.77; p < 0.001), and use of balloon guide catheter (BGC) (OR:1.60,95% CI: 1.17-2.18; p = 0.003) were significantly associated with successful recanalization with FPE. At the same time, age, female gender, duration of intervention, general anesthesia, use of BGC, and occlusion of ICA were associated with complete reperfusion with FPE, but M2 occlusion and DM were not. Conclusion: Age, gender, occlusion site, anesthesia type, and use of BGC were influencing factors for both successful and complete recanalization after first-pass thrombectomy. Further studies with more comprehensive observations indexes are need in the future.

SUBMITTER: Bai X

PROVIDER: S-EPMC8062801 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundTo evaluate the predictive value of radiomics features extracted from the thrombus on preoperative computed tomography images to identify successful recanalization after stent retrieve (SR) treatment in patients with acute ischemic stroke (AIS).MethodsTwo hundred fifty-six patients newly diagnosed AIS between March 2017 and September 2020 from two institutes, including the first affiliated hospital of Soochow university (institute I) and Northern Jiangsu People's hospital (institute II), were enrolled continuously and retrospectively. Patients with unsatisfactory image quality were excluded. The remaining patients of institute I were randomly divided into the training and internal validation cohorts at a ratio of 7 to 3, and patients of institute II were collected as the external validation cohort. After extraction and selection of the optimal radiomics features from training cohort, six machine learning (ML) classifiers including naïve Bayes (NB), random forest (RF), logistic regression (LR), linear support vector machine (L.SVM), radial SVM (R.SVM), and an artificial neural network (ANN) were developed to predict successful recanalization with SR treatment and compared. A combined model based on the optimal ML classifier was constructed using the optimal radiomics model and clinical-radiological risk variables. Finally, the performance of the model was selected based on the Matthews correlation coefficient (MCC) and the area under the receiver operating (AUC) and independently evaluated on the internal validation and external validation cohorts.ResultsWe automatically extracted 1,130 radiomics features from the voxel of interest (VOI) using PyRadiomics. The eight most relevant radiomics features were identified using Intraclass coefficient, single-factor logistic regression analysis, and least absolute shrinkage and selection operator algorithm in the training cohort. Among the six ML classifiers, the ANN classifier using thrombus radiomics features achieved the best prediction of early recanalization under SR with MCCs of 0.913, 0.693 and 0.505 in training, internal and external validation cohorts, respectively. Moreover, receiver operating characteristic curves showed that the combined model [AUC =0.860, 95% confidence interval (CI): 0.731-0.936; AUC =0.849, 95% CI: 0.759-0.831] was not significantly better than radiomics model based on the ANN classifier alone (AUC =0.873, 95% CI: 0.803-0.891; AUC =0.805, 95% CI: 0.864-0.971) (P>0.05, Delong test) in internal and external validation cohorts.ConclusionsA radiomics model based on the ANN classifier has the ability to predict successful recanalization after SR in patients with AIS, thus allowing a potentially better selection of mechanical thrombectomy treatment.

Project description:BackgroundFutile recanalization (FR) continues to raise concern despite the success of endovascular thrombectomy (EVT) in acute ischemic stroke (AIS). Understanding the prevalence of FR and identifying associated factors are crucial for refining patient prognoses and optimizing management strategies.ObjectivesThis study aims to comprehensively assess the pooled prevalence of FR, explore the diverse factors connected with FR, and establish the association of FR with long-term clinical outcomes among AIS patients undergoing EVT.Materials and methodsIncorporating studies focusing on FR following EVT in AIS patients, we conducted a random-effect meta-analysis to assess the pooled prevalence and its association with various clinical and imaging risk factors linked to FR. Summary estimates were compiled and study heterogeneity was explored.ResultsOur comprehensive meta-analysis, involving 11,700 AIS patients undergoing EVT, revealed a significant pooled prevalence of FR at 51%, with a range of 48% to 54% (Effect Size [ES]: 51%; 95% Confidence Interval [CI]: 48-54%; z = 47.66; p < 0.001). Numerous clinical factors demonstrated robust correlations with FR, including atrial fibrillation (Odds Ratio [OR]: 1.39, 95% CI 1.22 1.59; p < 0.001), hypertension (OR 1.65, 95% CI 1.41 1.92; p < 0.001), diabetes mellitus (OR 1.71, 95% CI 1.47 1.99; p < 0.001), previous stroke or transient ischemic attack (OR 1.298, 95% CI 1.06 1.59; p = 0.012), prior anticoagulant usage (OR 1.33, 95% CI 1.08 1.63; p = 0.007), cardioembolic strokes (OR 1.34, 95% CI 1.10 1.63; p = 0.003), and general anesthesia (OR 1.53, 95% CI 1.35 1.74; p < 0.001). Conversely, FR exhibited reduced likelihoods of smoking (OR 0.66, 95% CI 0.57 0.77; p < 0.001), good collaterals (OR 0.33, 95% CI 0.23 0.49; p < 0.001), male sex (OR 0.87, 95% CI 0.77 0.97; p = 0.016), and intravenous thrombolysis (IVT) (OR 0.75, 95% CI 0.66 0.86; p < 0.001). FR was strongly associated with increasing age (standardized mean difference [SMD] 0.49, 95% CI 0.42 0.56; p < 0.0001), baseline systolic blood pressure (SMD 0.20, 95% CI 0.13 0.27; p < 0.001), baseline National Institute of Health Stroke Severity Score (SMD 0.75, 95% CI: 0.65 0.86; p < 0.001), onset-to-treatment time (SMD 0.217, 95% CI 0.13 0.30; p < 0.001), onset-to-recanalization time (SMD 0.38, 95% CI 0.19; 0.57; p < 0.001), and baseline blood glucose (SMD 0.31, 95% CI 0.22 0.41; p < 0.001), while displaying a negative association with reduced baseline Alberta Stroke Program Early CT Score (ASPECTS) (SMD -0.37, 95% CI -0.46 -0.27; p < 0.001). Regarding clinical outcomes, FR was significantly associated with increased odds of symptomatic intracranial hemorrhages (OR 7.37, 95% CI 4.89 11.12; p < 0.001), hemorrhagic transformations (OR 2.98, 95% CI 2.37 3.75; p < 0.001), and 90-day mortality (OR 19.24, 95% CI 1.57 235.18; p = 0.021).ConclusionsThe substantial prevalence of FR, standing at approximately 51%, warrants clinical consideration. These findings underscore the complexity of FR in AIS patients and highlight the importance of tailoring management strategies based on individual risk factors and clinical profiles.

Project description:BackgroundEosinophils contribute to antibacterial defense by releasing mitochondrial DNA, which are decreased in patients with acute ischemic stroke (AIS). However, the impact of eosinophils on stroke-associated pneumonia (SAP) among patients with AIS remains unclear. Moreover, whether SAP is in the path of the association between eosinophils and clinical outcomes also remains unclear. We aimed to assess the relationships between eosinophils, SAP, and clinical outcome after mechanical thrombectomy in patients with AIS.MethodsA total of 328 consecutive patients with AIS who underwent mechanical thrombectomy between May 2017 and March 2021 were analyzed. Their baseline data and peripheral eosinophil counts were recorded on admission. Regression analysis was used to assess the effect of eosinophils on SAP, and its effect on poor outcome is defined as a modified Rankin Scale score of 3-6 at month 3 after admission. Mediation analysis was utilized to assess the proportion of the total effect of SAP on the association between eosinophils and poor outcomes.ResultsMultivariate analysis revealed that eosinophils was independently associated with SAP after adjusting for potential confounders (odds ratio, 0.00; 95% CI, 0.00-0.38; P = 0.0267), which are consistent with the result of eosinophils (dichotomous) as a categorical variable (odds ratio, 0.54; 95% CI, 0.31-0.96; P = 0.0342). A non-linear relationship was detected between eosinophils and SAP, whose inflection point was 0.06. Subgroup analyses further confirmed these associations. Eosinophils were also associated with poor outcomes (odds ratio, 0.00; 95% CI, 0.00-0.14; P = 0.0124). Additionally, mediation analysis found that SAP partially mediated the negative relationship between eosinophils and poor outcome (indirect effect = -0.169; 95% CI:-0.339 --0.040, P < 0.001).ConclusionOur findings suggested that a lower eosinophil level was associated with higher SAP and poorer outcome, and SAP might play an important effect in the association between eosinophils and poor outcomes.

Project description:BackgroundThe beneficial effects of endovascular treatment with new-generation mechanical thrombectomy devices compared with intravenous thrombolysis alone to treat acute large-artery ischemic stroke have been shown in randomized controlled trials (RCTs). This study aimed to estimate the cost utility of mechanical thrombectomy compared with the established standard of care.MethodsWe developed a Markov decision process analytic model to assess the cost-effectiveness of treatment with mechanical thrombectomy plus intravenous thrombolysis versus treatment with intravenous thrombolysis alone from the public payer perspective in Canada. We conducted comprehensive literature searches to populate model inputs. We estimated the efficacy of mechanical thrombectomy plus intravenous thrombolysis from a meta-analysis of 5 RCTs, and we used data from the Oxford Vascular Study to model long-term clinical outcomes. We calculated incremental cost-effectiveness ratios (ICER) using a 5-year time horizon.ResultsThe base case analysis showed the cost and effectiveness of treatment with mechanical thrombectomy plus intravenous thrombolysis to be $126?939 and 1.484 quality-adjusted life-years (QALYs), respectively, and the cost and effectiveness of treatment with intravenous thrombolysis alone to be $124?419 and 1.273 QALYs, respectively. The mechanical thrombectomy plus intravenous thrombolysis strategy was associated with an ICER of $11?990 per QALY gained. Probabilistic sensitivity analysis showed that the probability of treatment with mechanical thrombectomy plus intravenous thrombolysis being cost-effective was 57.5%, 89.7% and 99.6% at thresholds of $20?000, $50?000 and $100?000 per QALY gained, respectively. The main factors influencing the ICER were time horizon, extra cost of mechanical thrombectomy treatment and age of the patient.InterpretationMechanical thrombectomy as an adjunct therapy to intravenous thrombolysis is cost-effective compared with treatment with intravenous thrombolysis alone for patients with acute large-artery ischemic stroke.

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Factors Influencing Recanalization After Mechanical Thrombectomy With First-Pass Effect for Acute Ischemic Stroke: A Systematic Review and Meta-Analysis.

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