Analysis of Risk Factors for Futile Recanalization Following Mechanical Thrombectomy in Acute Ischemic Stroke

Analysis of Risk Factors for Futile Recanalization Following Mechanical Thrombectomy in Acute Ischemic Stroke | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Analysis of Risk Factors for Futile Recanalization Following Mechanical Thrombectomy in Acute Ischemic Stroke Hongyang Guo, Tanggui Sun, Zhongchen Li, Tengkun Yin, Jiheng Hao, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7932870/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background and Purpose Mechanical thrombectomy (MT), while effectively enhancing recanalization in acute ischemic stroke (AIS), still results in futile recanalization (FR) — absent functional recovery despite reperfusion success — in approximately 50% of cases. This study investigates FR-associated risk factors, refines patient selection and thrombectomy procedures, and explores targeted therapies addressing FR pathophysiology, ultimately aiming to reduce FR incidence and improve outcomes in MT-treated AIS patients. Methods This retrospective cohort study included 597 AIS patients with anterior circulation LVO undergoing MT (2020–2023). Patients were stratified by 90-day mRS into ER (mRS < 3, n = 291) and FR (mRS ≥ 3, n = 306) groups. Demographic, clinical, and intraoperative imaging data were analyzed. Univariate and multivariate logistic regression (P < 0.1 threshold) identified independent FR risk factors. Results Multivariate analysis identified coronary artery disease(OR = 2.209, 95% CI 1.272–3.835), higher preoperative NIHSS scores(OR = 1.067, 95% CI 1.040–1.094), symptomatic intracranial hemorrhage(OR = 12.721, 95% CI 3.358–48.185), Malignant cerebral edema (OR = 3.350, 95% CI 1.833–6.121), ASITN/SIR collateral grade (OR = 1.013, 95% CI 1.001–1.026), and elevated admission SBP (1.013[1.001–1.026]) as independent predictors of futile recanalization. The nomogram prediction model based on the above factors shows that the area under the subject operating characteristic curve (AUC) is 0.829, which shows a good prediction effect. Conclusion This study identified key determinants of futile recanalization (FR) after mechanical thrombectomy (MT) in acute large vessel occlusion stroke. The validated nomogram demonstrated robust predictive utility for post-MT FR, offering translational insights and actionable therapeutic targets to optimize endovascular outcomes. Acute ischemic stroke Large vessel occlusion Mechanical thrombectomy Futile recanalization Risk factors Figures Figure 1 Figure 2 1. Introduction Acute ischemic stroke (AIS) is an acute disease that results from reduced cerebral blood flow and brain cell damage caused by cerebrovascular stenosis or occlusion. Typical of high incidence, disability and fatality, it poses a serious threat to patients' lives and health 1 . Large vessel occlusion (LVO), predominantly in the anterior circulation, accounts for over one-third of AIS cases and represents a critical etiological target 2 . Prior to the clinical application of Mechanical Thrombectomy (MT), intravenous thrombolysis was the main recanalization therapy for AIS, and the proportion of patients with clinical benefit was limited due to strict time window (usually ≤ 4.5 h) and contraindications such as bleeding transformation 3 . With the advancement of endovascular therapy technology, intravenous thrombolysis combined with mechanical thrombolysis has become the main means of AIS reperfusion therapy. Compared with standard drug therapy alone, mechanical thrombectomy combined with standard drug therapy can significantly improve the functional outcomes of AIS patients 4 . Therefore, mechanical thrombectomy (MT) has been established as the treatment of choice for large vessel occlusive AIS (LVO-AIS) due to its advantages of direct removal of thrombus. A number of studies have confirmed that MT can not only significantly improve the neurological function prognosis of patients compared with drug therapy alone, but also has good safety 5 . However, about 50% of patients with acute anterior circulation large vessel occlusion still have functional disability at 3 months after MT treatment. In 2013, some scholars defined successful vascular recanalization with modified Rankin scale (mRS) score ≥ 3 points 3 months after surgery as futile recanalization (FR) 6 . Endovascular therapy for anterior circulation large vessel occlusion (LVO) yields futile recanalization (FR) rates of 45%-54% 7 . Emerging evidence implicates multifactorial mechanisms including no-reflow phenomenon, collateral insufficiency, venous drainage impairment, and neuroinflammatory cascades in FR pathogenesis 8 . Identifying modifiable FR predictors could optimize patient selection and adjuvant therapies, ultimately enhancing long-term MT outcomes. While prior studies have predominantly examined factors influencing futile recanalization (FR) post-mechanical thrombectomy (MT) 9 – 11 , predictive model development remains underexplored 12 , 13 . This study aims to identify FR risk factors in AIS patients achieving successful recanalization (mTICI grades 2b-3) 7 and develop a multivariate predictive model, thereby advancing translational strategies for optimizing endovascular treatment outcomes. 2. Data and methods 2.1 General information: This retrospective analysis included 597 anterior circulation large vessel occlusion patients (male:female =373:224; age range 23-99 years, mean 65.8) undergoing mechanical thrombectomy at Liaocheng Brain Hospital Stroke Center between January 2020 and June 2023. 2.1.1 Inclusion criteria: Inclusion criteria: Age ≥18 years; Confirmed anterior circulation large vessel occlusion (LVO) involving internal carotid, middle cerebral, or anterior cerebral arteries; Successful recanalization (mTICI grade 2b-3) post-mechanical thrombectomy (MT). 2.1.2 Exclusion criteria: Recent stroke (≤1 year); unsuccessful recanalization (mTICI <2b); severe systemic comorbidities (infection, hepatorenal dysfunction, hematologic disorders, malignancies); traumatic brain injury/intracranial hemorrhage; contrast/intervention device allergies; major psychiatric disorders; incomplete clinical data. 2.2 Futile Recanalization and Related Definitions: Ineffective recanalization is clinically defined as a functional outcome of modified Rankin Scale (mRS) score ≥3 at 90 days post-intervention, despite achieving successful arterial recanalization (defined as mTICI or eTICI grades ≥2b) through mechanical thrombectomy. This outcome assessment applies specifically to patients demonstrating adequate angiographic reperfusion (mTICI 2b-3) following the procedure 6,10,14,15 . Malignant cerebral edema (MBE) is defined as life-threatening brain swelling developing within 24-48 hours of major cerebral infarction (e.g., in the MCA territory), characterized by cerebral herniation or ≥5 mm midline shift secondary to mass effect 16,17 . For collateral circulation evaluation, the ASITN/SIR collateral grading system classifies perfusion in ischemic territories into 0-4 grades based on digital subtraction angiography (DSA) findings, where grades 3-4 indicate robust collateral flow (associated with favorable outcomes) and grades 0-2 reflect inadequate compensation (predicting poorer prognosis) 18,19 . Similarly, the Tan collateral scoring system stratifies patients (0-3 grades) using CTA source images, with grades 2-3 correlating with preserved tissue viability and grades 0-1 denoting insufficient collateral recruitment 20 . The hyperdense vessel sign (HVS) on non-contrast CT manifests as focal hyperattenuation (CT values exceeding adjacent tissues) along occluded cerebral arteries (e.g., the MCA), serving as an early radiological indicator of major vessel occlusion 21 . 2.3 Vascular Recanalization Assessment: Recanalization outcomes following endovascular therapy (including mechanical thrombectomy) were assessed using the modified Thrombolysis in Cerebral Infarction (mTICI) grading system 22 . Two to three experienced neurointerventionalists independently evaluated the results, with discrepancies resolved through consensus. Successful recanalization was defined as mTICI grades 2b–3, while grades 0–2a were classified as incomplete recanalization 7 . 2.4 Statistical Analysis: Data analysis and processing were performed using SPSS 26.0, R 4.3.3, and Microsoft Excel 365. Missing values were imputed via the expectation-maximization (EM) algorithm. Normally distributed continuous variables were expressed as mean ± standard deviation (±S), with intergroup comparisons using the independent-samples t-test. Non-normally distributed continuous variables and ordinal data were presented as median and interquartile range [M(P25, P75)], and compared using the Wilcoxon Mann-Whitney U test. Categorical variables were described as n(%), with intergroup comparisons conducted via the χ² test. Univariate analysis was performed to screen influencing factors of futile recanalization (FR) after mechanical thrombectomy. Multicollinearity among factors with P<0.1 was assessed, and all variance inflation factors (VIF) were <10, confirming collinearity was within an acceptable range. Subsequent multivariate logistic regression analysis identified independent predictors of FR (P<0.05). A nomogram for predicting post-thrombectomy FR probability was constructed based on the regression results. The nomogram’s predictive performance was evaluated using the receiver operating characteristic (ROC) curve, with results reported as the area under the curve (AUC). A two-tailed P<0.05 was considered statistically significant. 3. Result 3.1 Patient Characteristics: The study enrolled 597 patients, with futile recanalization (FR) occurring in 306 cases (51.3%) and successful recanalization (SR) in 291 cases. The FR group comprised 183 males (59.8%) and 123 females (40.2%), with a median age of 70 years (IQR 62-76). The SR group included 190 males (65.3%) and 101 females (34.7%), showing a younger median age of 65 years (IQR 55-73). 3.2 Univariate Analysis of Factors Associated with Futile Recanalization Following Mechanical Thrombectomy in Acute Anterior Circulation Large Vessel Occlusion ： This study included 597 patients, with futile recanalization (FR) observed in 306 cases (51.3%) and successful recanalization in 291 (48.7%). Univariate analysis identified significant differences ( P <0.05) in the following variables: 3.2.1 Baseline clinical data: Including demographic factors (age), vascular pathology (occlusive site, TOAST classification), comorbidities (coronary heart disease, atrial fibrillation), lifestyle factors (smoking history, alcohol consumption), therapeutic interventions (intravenous thrombolysis, anticoagulation, thrombectomy parameters), and clinical indicators (preoperative NIHSS score, admission blood pressure). Procedural details such as first thrombolysis technique, aspiration stent combination, mTICI grades, thrombectomy frequency (>3 attempts), and adjunctive techniques (balloon dilation, stent implantation) were also analyzed, along with postoperative complications (ICH, HT, sICH, cerebral edema) and interventions (decompressive craniectomy). Detailed data are presented in Table 1. 3.2.2 Biomarkers/Imaging Metrics ： This study further identified significant intergroup differences in preoperative imaging parameters (Tan score, high-density sign, ASITN/SIR grade, venous visualization) and laboratory biomarkers, including inflammatory indices (neutrophil/lymphocyte counts, NLR, CRP), coagulation profiles (prothrombin time, INR, D-dimer), metabolic markers (blood glucose, LDL-C, prealbumin), cardiac function (NT-proBNP [pg/mL]), and neuroimaging severity (ASPECTS scores). Complete statistical comparisons are presented in Table 2. 3.3 Multivariate Predictors of Futile Recanalization After Mechanical Thrombectomy in Acute Anterior Circulation Large Vessel Occlusion Variables with P<0.1 in univariate analysis were defined as independent variables, and ineffective recanalization as the dependent variable. Multicollinearity assessment was conducted for these independent variables, with results showing all variance inflation factors (VIF) <10, confirming multicollinearity was controlled within an acceptable range. Subsequent multivariate Logistic regression analysis indicated that history of coronary heart disease, preoperative National Institutes of Health Stroke Scale (NIHSS) score, symptomatic intracerebral hemorrhage (sICH), malignant cerebral edema within 24 h post-operation, American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology (ASITN/SIR) grade, and admission systolic blood pressure were independent influencing factors for ineffective recanalization (Table 3). 3.4 Predictive Performance of a Multifactorial Model for Futile Recanalization Post-Mechanical Thrombectomy Independent predictors with P<0.05 were identified via multivariate Logistic regression, and a nomogram prediction model was constructed based on these factors (Fig. 1). Internal validation was conducted to assess the model’s predictive performance: calibration curve analysis (Fig. 2a) showed good agreement between predicted probabilities and actual observations, with the fitting curve highly overlapping the ideal reference line, indicating excellent calibration. Receiver operating characteristic (ROC) curve analysis (Fig. 2b) yielded an area under the curve (AUC) of 0.829, demonstrating good discriminative ability. Clinical impact curve analysis (Fig. 2c) revealed that when the risk threshold exceeded 0.5, the model’s predictive accuracy significantly improved in high-risk populations. Decision curve analysis (Fig. 2d) further confirmed that the nomogram provided higher net benefit than other strategies across the 0–1.0 probability range, highlighting its substantial value in clinical decision-making. 4.Discussion This study analyzed predictors of futile recanalization (FR) following mechanical thrombectomy (MT) in patients with anterior circulation large vessel occlusion-related acute ischemic stroke (AIS-LVO), revealing an FR incidence of 51.3%. While prior studies have identified associations between FR and baseline NIHSS scores, neutrophil-to-lymphocyte ratio (NLR), and other parameters 23 , existing prediction models remain limited by insufficient integration of multimodal data. To address this gap, we innovatively synthesized baseline clinical characteristics (e.g., coronary artery disease history, admission systolic blood pressure), temporal metrics (onset-to-recanalization time), procedural details (thrombectomy attempts/techniques), preoperative biomarkers (NLR, blood glucose, D-dimer), and imaging signatures (venous prominence, ASITN/SIR collateral grading) for multidimensional risk assessment. Multivariable analysis identified six independent FR predictors: elevated preoperative NIHSS scores, coronary artery disease history, symptomatic intracranial hemorrhage (sICH), malignant cerebral edema, abnormal ASITN/SIR grading, and elevated admission systolic blood pressure. The derived predictive model demonstrated robust discriminative performance (AUC=0.829), establishing a quantifiable tool for stratifying post-MT FR risk in clinical practice. Endovascular recanalization through mechanical thrombectomy (MT) remains the cornerstone of acute ischemic stroke (AIS) management, particularly for anterior circulation large vessel occlusion (LVO), with randomized trials demonstrating significant prognostic benefits 3,23 . However, approximately 60% of patients experience futile recanalization (FR), defined as modified Rankin Scale (mRS) scores ≥3 at 90 days post-procedure despite successful revascularization 9 . The pathophysiology of FR remains incompletely characterized, though current evidence implicates a multifactorial pathophysiology involving impaired collateral circulation, microvascular injury, and no-reflow phenomena 24–26 . Baseline NIHSS score, a validated prognostic marker in stroke, emerged as an independent predictor of futile recanalization (FR) in our analysis (OR=1.067, 95%CI=1.040–1.094, p <0.001). This aligns with prior evidence: Hussein et al. 27 demonstrated stronger FR association with NIHSS (OR=1.3, p =0.001) versus sex (OR=7.7) or treatment latency (OR=1.2) in the IMS III cohort. Kim et al. 28 identified an 18.1% FR risk increase per 1-point NIHSS increment (OR=1.181, p =0.012) in large infarcts. Notably, Pan et al. 29 highlighted a critical NIHSS threshold (≥12) for FR risk escalation in multicenter data, underscoring its clinical utility for preprocedural risk stratification. Elevated admission systolic blood pressure (SBP) is an established independent risk factor for futile recanalization (FR) in acute ischemic stroke (AIS) patients undergoing mechanical thrombectomy 30 . Data from the DIRECT-MT multicenter trial demonstrated a significant FR association with elevated SBP (OR=4.98, 95%CI 1.87–8.09) 8 . Pathophysiological studies suggest that hypertension exacerbates FR risk through infarct expansion and reduced tissue salvage efficiency in perfusion-diffusion mismatch regions 15,31 , a mechanism further corroborated by our findings. Collateral failure is a critical predictor of futile recanalization (FR) in acute ischemic stroke. Compromised microvascular reperfusion and reperfusion injury underlie ischemia-reperfusion pathology, while robust collaterals preserve penumbral viability until revascularization, improving outcomes 26,32 . Our study, utilizing ASITN/SIR collateral grading, demonstrated a significant inverse association between collateral adequacy and FR risk (OR=0.754, 95%CI=0.597–0.953; p =0.018). ASITN/SIR grades 0–1 (poor), 2 (moderate), and 3–4 (robust) stratify FR risk, with grades <2 conferring significantly higher FR susceptibility 33 , aligning with Pan et al. 29 and Espinosa de Rueda et al. 34 .Current grading systems suffer from interobserver variability, necessitating objective multimodal assessment. Future studies aim to integrate CTA and DSA for three objectives: refining collateral scoring, optimizing thrombectomy candidacy criteria, and enhancing FR risk stratification 29 . MCE, a recognized independent risk factor for neurological deterioration and poor functional outcomes 30 , was independently associated with futile recanalization (FR) post-thrombectomy (OR=3.350, 95%CI:1.833–6.121; p <0.001). Patients with MCE exhibited significantly worse neurological outcomes versus controls ( p <0.001). Notably, while MCE represents a nonmodifiable predictor, persistent challenges in early detection due to limited sensitivity and timeliness of current imaging modalities underscore the need for advanced biomarkers or dynamic imaging protocols to refine clinical risk stratification. Symptomatic intracranial hemorrhage (sICH) was identified as an independent risk factor for futile recanalization post-mechanical thrombectomy (OR=12.721, 95%CI:3.358-48.185, p<0.001). The 24-hour post-stroke window represents a critical monitoring period, as complications—particularly sICH—significantly impact neurological outcomes. Per ECASS II criteria, sICH was defined as radiologically confirmed intracranial hemorrhage within 24 hours post-procedure accompanied by ≥4-point NIHSS score increase 35 . Heitkamp et al.'s cohort 36 further validated sICH’s independent association with neurological deterioration, potentially mediated through blood-brain barrier disruption, oxidative stress, and inflammatory cascade activation. Systematic evidence synthesis indicates that atrial fibrillation (AF) exhibits distinct pathogenic features in ischemic stroke, particularly among elderly populations. As a key risk factor for cardioembolic stroke, AF-associated strokes demonstrate greater neurological severity and poorer clinical outcomes 37 . Epidemiological evidence demonstrates significant associations between atrial fibrillation (AF) and modifiable risk factors (obesity, smoking, hypertension, diabetes) as well as pre-existing cardiovascular conditions (coronary artery disease, heart failure) 37 . Notably, atherosclerotic pathology—common in advanced age and coronary artery disease—exacerbates ischemic injury by impairing early compensatory mechanisms, particularly reduced ASITN/SIR-graded collateral circulation 38 . Multivariable logistic regression identified coronary artery disease history (OR=2.209, 95%CI=1.272-3.835, p=0.005) as the strongest independent predictor of futile recanalization, outperforming collateral circulation status (ASITN/SIR grade OR=0.754, 95%CI=0.597-0.953, p=0.018) and hemodynamic parameters (admission systolic blood pressure OR=1.013, 95%CI=1.001-1.026, p=0.039). Multivariable analysis revealed that while atrial fibrillation (AF) showed significant intergroup differences, it was not independently associated with futile recanalization. This discrepancy may reflect detection bias, as routine intermittent ECG monitoring likely underestimates paroxysmal/asymptomatic AF prevalence, contributing to diagnostic underascertainment 37 . These findings underscore that cardioembolic stroke prevention strategies should prioritize integrated management of atherosclerotic comorbidities (e.g., coronary artery disease) and enhanced screening for subclinical atrial fibrillation, critical for improving clinical outcomes in these high-disability, high-mortality strokes. The nomogram prediction model developed in this study demonstrated robust clinical utility for FR risk stratification post-mechanical thrombectomy, enabling clinicians to stratify FR risk and implement targeted preventive interventions. This model facilitates FR risk stratification through multivariable integration. High-risk patients identified via scoring may receive preemptive interventions to mitigate FR risk, while targeted monitoring enables rapid therapeutic escalation when FR occurs, ultimately improving clinical outcomes. This study explored the age-dependent association with futile recanalization (FR). While multiple cohorts suggest advanced age increases FR risk in stroke patients 7,26,39 , potential mechanisms may involve cerebral hypoperfusion (brain atrophy, metabolic dysregulation, reduced cardiac output), impaired cerebrovascular autoregulation, and compromised collateral compensation 40,41 . Beyond aging-related physiological changes, the elevated FR risk may also stem from higher cerebrovascular disease burden in the elderly [26]. However, multivariable analysis failed to identify age as an independent FR predictor. Our findings align with Heitkamp’s cohort 36 , where advancing endovascular reperfusion techniques partially mitigated age-related neurological prognosis. Notably, the cohort’s pronounced age stratification (70% [n=175] aged <60 years) introduces confounding effects (e.g., higher baseline vasculopathy in older subgroups) that may influence outcome interpretation. Although no independent association between age and FR was identified, future studies should control for baseline vasculopathy, stratify participants into age subgroups (e.g., ≥80 years), and extend the follow-up period to systematically evaluate age-dependent temporal effects on neurological outcomes following recanalization. This study has certain limitations: firstly, the single-center retrospective design carries inherent selection bias; secondly, despite routine postoperative rehabilitation, long-term follow-up data on rehabilitation after discharge are lacking, which may interfere with the assessment of long-term prognosis. To further identify the core influencing factors of futile recanalization (FR), the following studies should be prioritized: expanding the sample size and conducting multi-center cohort validation; establishing controlled studies on different anesthesia modes and vascular recanalization strategies; developing multi-dimensional prediction models incorporating radiomics, molecular biomarkers, and standardized secondary prevention; and elucidating the pathophysiological mechanism of FR and exploring novel intervention targets through basic research. 5. Conclusion This study identified coronary artery disease, elevated preprocedural NIHSS scores, symptomatic intracranial hemorrhage (sICH), malignant cerebral edema (MCE), ASITN/SIR collateral grading, and increased admission systolic blood pressure as independent predictors of futile recanalization (FR) post-mechanical thrombectomy. The multivariable model incorporating these predictors enables early FR risk quantification, facilitating personalized clinical decision-making. Abbreviations Abbreviation Full Term ACA Anterior Cerebral Artery AIS Acute Ischemic Stroke APC Article Processing Charge APTT Activated Partial Thromboplastin Time ASPECTS Alberta Stroke Program Early CT Score ASITN/SIR American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology AUC Area Under the Curve CI Confidence Interval CRP C-Reactive Protein DBP Diastolic Blood Pressure DSA Digital Subtraction Angiography DTP Door-to-Puncture Time FR Futile Recanalization HT Hemorrhagic Transformation ICA Internal Carotid Artery ICH Intracranial Hemorrhage INR International Normalized Ratio LDL-C Low-Density Lipoprotein Cholesterol LVO Large Vessel Occlusion MCA Middle Cerebral Artery MCE Malignant Cerebral Edema MRI Magnetic Resonance Imaging mRS modified Rankin Scale mTICI modified Thrombolysis in Cerebral Infarction NIHSS National Institutes of Health Stroke Scale NLR Neutrophil-to-Lymphocyte Ratio NT-proBNP N-terminal pro-B-type Natriuretic Peptide OR Odds Ratio OTD Onset-to-Door Time OTP Onset-to-Puncture Time OTR Onset-to-Recanalization Time PTR Puncture-to-Recanalization Time ROC Receiver Operating Characteristic SBP Systolic Blood Pressure sICH Symptomatic Intracranial Hemorrhage TOAST Trial of Org 10172 in Acute Stroke Treatment TIA Transient Ischemic Attack WBC White Blood Cell Declarations The authors declared no conflict of interest. Ethical approval This retrospective study adhered to the Helsinki Declaration and was approved by the Ethics Committee of Liaocheng People’s Hospital, Shandong Province. Written informed consent was obtained from all participants or their legal guardians. Generative AI and AI-assisted technologies were NOT used in the preparation of this work. Author Contribution Author Contributions:Hongyang Guo: Conceptualization, Methodology, Writing – Original DraftTanggui Sun: Data Curation, Formal Analysis, VisualizationZhongchen Li: Review & EditingTengkun Yin: Supervision, Writing – ReviewJiheng Hao: ReviewWenyu Zhang: Data Curation, Formal Analysis, VisualizationXu Zan: Data CurationLiyong Zhang: Review & Editing References Walter K. What Is Acute Ischemic Stroke? JAMA . 2022;327(9):885. doi:10.1001/jama.2022.1420 Jia B, Ren Z, Mokin M, et al. Current Status of Endovascular Treatment for Acute Large Vessel Occlusion in China: A Real-World Nationwide Registry. 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Neuron . 2024;112(9):1456-1472.e6. doi:10.1016/j.neuron.2024.01.031 Higashida RT, Furlan AJ. Trial Design and Reporting Standards for Intra-Arterial Cerebral Thrombolysis for Acute Ischemic Stroke. Stroke . 2003;34(8). doi:10.1161/01.STR.0000082721.62796.09 Espinosa De Rueda M, Parrilla G, Manzano-Fernández S, et al. Combined Multimodal Computed Tomography Score Correlates With Futile Recanalization After Thrombectomy in Patients With Acute Stroke. Stroke . 2015;46(9):2517-2522. doi:10.1161/STROKEAHA.114.008598 Hacke W, Kaste M, Fieschi C, et al. Randomised double-blind placebo-controlled trial of thrombolytic therapy with intravenous alteplase in acute ischaemic stroke (ECASS II). The Lancet . 1998;352(9136):1245-1251. doi:10.1016/S0140-6736(98)08020-9 Heitkamp C, Heitkamp A, Winkelmeier L, et al. Predictors of futile recanalization in ischemic stroke patients with low baseline NIHSS. International Journal of Stroke . 2024;19(10):1102-1112. doi:10.1177/17474930241264737 Pistoia F, Sacco S, Tiseo C, Degan D, Ornello R, Carolei A. The Epidemiology of Atrial Fibrillation and Stroke. Cardiology Clinics . 2016;34(2):255-268. doi:10.1016/j.ccl.2015.12.002 Ritvonen J, Sairanen T, Silvennoinen H, et al. Comatose With Basilar Artery Occlusion: Still Odds of Favorable Outcome With Recanalization Therapy. Front Neurol . 2021;12:665317. doi:10.3389/fneur.2021.665317 Heitkamp C, Winkelmeier L, Heit JJ, et al. Unfavorable cerebral venous outflow is associated with futile recanalization in acute ischemic stroke patients. Euro J of Neurology . 2023;30(9):2684-2692. doi:10.1111/ene.15898 Mokhber N, Shariatzadeh A, Avan A, et al. Cerebral blood flow changes during aging process and in cognitive disorders: A review. Neuroradiol J . 2021;34(4):300-307. doi:10.1177/19714009211002778 Reinhard M, Rutsch S, Lambeck J, et al. Dynamic cerebral autoregulation associates with infarct size and outcome after ischemic stroke: Cerebral autoregulation in ischemic stroke. Acta Neurologica Scandinavica . 2012;125(3):156-162. doi:10.1111/j.1600-0404.2011.01515.x Tables Table 1. General and Clinical Characteristics of Successful Recanalization Group and Failed Recanalization Group Recanalization Group Factor Successful Recanalization Group (n=291) Failed Recanalization Group (n=306) P-value Sex [n (%)] 0.166 - Male 190 (65.3%) 183 (59.8%) - Female 101 (34.7%) 123 (40.2%) Age [M (P25, P75)] 65 (55, 73) 70 (62, 76) <0.001 Occlusion Site [n (%)] 0.084 - Internal carotid artery 92 (31.6%) 121 (39.5%) - Tandem lesion 159 (54.6%) 153 (50.0%) - Middle cerebral artery 37 (12.7%) 26 (8.5%) - Other arteries 3 (1.0%) 6 (2.0%) Side [n (%)] 0.683 - Left 158 (54.3%) 172 (56.2%) - Right 133 (45.7%) 134 (43.8%) Intravenous Thrombolysis [n (%)] 172 (59.1%) 153 (50.0%) 0.026 TOAST Classification [n (%)] <0.001 - Intracranial artery stenosis/occlusion 142 (48.8%) 100 (32.7%) - Extracranial tandem lesion 24 (8.2%) 24 (7.8%) - Cardioembolic 78 (26.8%) 134 (43.8%) - Other 47 (16.2%) 48 (15.7%) Hypertension [n (%)] 189 (64.9%) 215 (70.3%) 0.165 Diabetes [n (%)] 63 (21.6%) 74 (24.2%) 0.462 Hyperlipidemia [n (%)] 105 (36.1%) 100 (32.7%) 0.381 Coronary Artery Disease [n (%)] 42 (14.4%) 81 (26.5%) <0.001 Atrial Fibrillation [n (%)] 73 (25.1%) 138 (45.1%) <0.001 Myocardial Infarction [n (%)] 1 (0.3%) 3 (1.0%) 0.652 Smoking History [n (%)] 90 (30.9%) 73 (23.9%) 0.053 Alcohol History [n (%)] 100 (34.4%) 75 (24.5%) 0.008 Stroke History [n (%)] 51 (17.5%) 63 (20.6%) 0.341 Anticoagulation [n (%)] 6 (2.1%) 14 (4.6%) 0.088 Anti-platelet [n (%)] 35 (12.0%) 43 (14.1%) 0.463 Preoperative NIHSS [M (P25, P75)] 13 (8, 20) 22 (15, 30) <0.001 Postoperative 24h ICH [n (%)] 62 (21.3%) 156 (51.0%) <0.001 Hemorrhagic Transformation (HT) [n (%)] 55 (18.9%) 146 (47.7%) <0.001 Symptomatic ICH (sICH) [n (%)] 3 (1.0%) 63 (20.6%) <0.001 Postoperative 72h ICH [n (%)] 4 (1.4%) 8 (2.6%) 0.281 Cerebral Edema [n (%)] 111 (38.1%) 83 (27.1%) 0.004 Malignant Cerebral Edema [n (%)] 38 (13.1%) 152 (49.7%) <0.001 Anesthesia [n (%)] 0.487 - Local anesthesia 1 (0.3%) 0 (0.0%) - General anesthesia 290 (99.7%) 306 (100%) Initial mTICI Post-thrombectomy [n (%)] 0.012 - 0 37 (12.7%) 69 (22.5%) - 1 10 (3.4%) 9 (2.9%) - 2a 70 (24.1%) 53 (17.3%) - 2b 57 (19.6%) 48 (15.7%) - 3 117 (40.2%) 127 (41.5%) Total Thrombectomy Attempts [M (P25, P75)] 1 (1, 2) 2 (1, 3) 3 [n (%)] 47 (16.2%) 79 (25.8%) 0.004 Rescue Techniques [n (%)] 168 (57.7%) 111 (36.3%) <0.001 Balloon Angioplasty [n (%)] <0.001 - 0 149 (51.2%) 210 (68.6%) - 1 131 (45.0%) 94 (30.7%) - 2 9 (3.1%) 2 (0.7%) - 3 2 (0.7%) 0 (0.0%) Stent Placement [n (%)] 149 (51.2%) 99 (32.4%) <0.001 Intra-arterial Medication [n (%)] 55 (18.9%) 53 (17.3%) 0.616 Final mTICI Post-procedure [n (%)] 0.049 - 2b 11 (3.8%) 23 (7.5%) - 3 280 (96.2%) 283 (92.5%) Early Venous Filling [n (%)] 26 (8.9%) 34 (11.1%) 0.377 OTD (Onset-to-Door Time) [min; M (P25, P75)] 180 (113, 295) 177 (103, 270) 0.556 DTP (Door-to-Puncture Time) [min; M (P25, P75)] 109 (89, 151) 109 (87, 148) 0.661 OTP (Onset-to-Puncture Time) [min; M (P25, P75)] 310 (227, 430) 300 (219, 406) 0.419 PTR (Puncture-to-Recanalization Time) [min; M (P25, P75)] 81 (58, 108) 78 (58, 110) 0.984 OTR (Onset-to-Recanalization Time) [min; M (P25, P75)] 403 (313, 544) 395.5 (299.5, 530.25) 0.601 Postoperative Decompressive Craniectomy [n (%)] 1 (0.3%) 15 (4.9%) 0.001 Bifurcation Occlusion [n (%)] 178 (61.2%) 196 (64.1%) 0.467 Preoperative Tan Score [M (P25, P75)] 2 (1, 2) 1 (1, 2) <0.001 Preoperative Hyperdense Sign [n (%)] 85 (29.2%) 139 (45.4%) <0.001 ASITN/SIR Grade [M (P25, P75)] 1 (0, 2) 1 (0, 1) <0.001 Admission SBP [mmHg; M (P25, P75)] 147 (135, 162) 155.5 (142, 168) <0.001 Admission DBP [mmHg; M (P25, P75)] 86 (78, 96) 89 (80, 98) 0.022 Notes: M (P25, P75): Median (25th percentile, 75th percentile). NIHSS: National Institutes of Health Stroke Scale. ICH: Intracranial hemorrhage. mTICI: Modified Thrombolysis in Cerebral Infarction scale. Data presented as n (%) or median (interquartile range). Statistical significance set at P < 0.05. Table 2. Laboratory and Imaging Data of Successful Recanalization Group and Ineffective Recanalization Group Factor Successful Recanalization Group (n=291) Failed Recanalization Group (n=306) P-value Preoperative WBC [×10⁹/L; M (P25, P75)] 7.45 (6.11, 9.25) 7.83 (6.33, 9.79) 0.153 Preoperative Neutrophil [×10⁹/L; M (P25, P75)] 5.22 (3.97, 7.08) 5.66 (4.27, 7.72) 0.024 Preoperative Lymphocyte [×10⁹/L; M (P25, P75)] 1.50 (1.10, 2.00) 1.31 (0.91, 1.83) 0.001 Preoperative NLR [M (P25, P75)] 3.69 (2.16, 5.90) 4.44 (2.74, 7.54) 0.001 Preoperative Platelet [×10⁹/L; M (P25, P75)] 200.00 (170.00, 235.00) 190.00 (159.00, 223.00) 0.010 Preoperative Glucose [mmol/L; M (P25, P75)] 7.00 (6.07, 8.35) 7.61 (6.49, 9.42) <0.001 Preoperative CRP [mg/L; M (P25, P75)] 1.30 (0.60, 4.31) 1.70 (0.70, 6.80) 0.019 Prothrombin Time [s; M (P25, P75)] 11.30 (10.80, 11.90) 11.40 (10.90, 12.10) 0.014 INR [M (P25, P75)] 1.05 (1.01, 1.11) 1.07 (1.02, 1.13) 0.006 APTT [s; M (P25, P75)] 31.2 (29.20, 33.0) 31.10 (28.80, 33.80) 0.561 APTT Ratio [M (P25, P75)] 1.01 (0.94, 1.09) 1.00 (0.93, 1.09) 0.222 D-dimer [mg/L; M (P25, P75)] 0.50 (0.30, 1.00) 0.80 (0.40, 2.00) <0.001 LDL-C [mmol/L; M (P25, P75)] 2.63 (2.15, 3.26) 2.55 (1.98, 3.09) 0.029 Prealbumin [mg/L; M (P25, P75)] 252.00 (207.00, 287.00) 234.00 (198.75, 274.00) 0.012 Preoperative NT-proBNP [pg/mL; M (P25, P75)] 152.00 (81.00, 341.00) 292.50 (115.33, 983.84) <0.001 Preoperative ASPECTS Score [M (P25, P75)] 8 (6, 9) 7 (4, 8) <0.001 Preoperative Tan Score [M (P25, P75)] 2 (1, 2) 1 (1, 2) <0.001 Preoperative Hyperdense Sign [n (%)] 85 (29.2) 139 (45.4) <0.001 ASITN/SIR Grade [M (P25, P75)] 1 (0, 2) 1 (0, 1) <0.001 Bifurcation Occlusion [n (%)] 178 (61.2) 196 (64.1) 0.467 Early Venous Filling [n (%)] 26 (8.9) 34 (11.1) 0.377 Notes: ASITN/SIR: American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology. ASPECTS: Alberta Stroke Program Early CT Score. CRP: C-reactive protein. INR: International normalized ratio. APTT: Activated partial thromboplastin time. LDL-C: Low-density lipoprotein cholesterol. NT-proBNP: N-terminal pro-B-type natriuretic peptide. Data presented as n (%) or median (interquartile range). Statistical significance set at P < 0.05. Table 3. Multivariate Logistic Regression Analysis of Predictors of Failed Recanalization After Mechanical Thrombectomy Predictor Regression Coefficient P-value Odds Ratio (OR) 95% CI History of Coronary Artery Disease 0.792 0.005 2.209 1.272–3.835 Preoperative NIHSS Score 0.065 <0.001 1.067 1.040–1.094 sICH (Symptomatic Intracranial Hemorrhage) 2.543 <0.001 12.721 3.358–48.185 Malignant Cerebral Edema 1.209 <0.001 3.350 1.833–6.121 ASITN/SIR Grade -0.282 0.018 0.754 0.597–0.953 Admission Systolic Blood Pressure 0.013 0.039 1.013 1.001–1.026 Notes: NIHSS: National Institutes of Health Stroke Scale. sICH: Symptomatic intracranial hemorrhage. ASITN/SIR: American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology. CI: Confidence interval. Data presented as regression coefficients, odds ratios (OR), and 95% confidence intervals (CI). Statistical significance set at P < 0.05. Additional Declarations No competing interests reported. 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1","display":"","copyAsset":false,"role":"figure","size":38587,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNomogram Predicting Futile Recanalization After Mechanical Thrombectomy \u003c/strong\u003eThe nomogram assigns points for each predictor via the upper point scale. Total points (summed from individual predictors) are aligned with the bottom probability axis to estimate futile recanalization risk.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7932870/v1/39f9a782724b0531238775b2.jpeg"},{"id":95939060,"identity":"d4710bc7-f9bf-4889-9d55-da164ed9d5b7","added_by":"auto","created_at":"2025-11-14 16:06:18","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":109460,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eValidation of the Nomogram for Predicting Futile Recanalization (FR)\u003c/strong\u003e \u003cstrong\u003e(a)\u003c/strong\u003e Calibration plot: X-axis (predicted probability) vs. Y-axis (observed probability). Both apparent (internal) and bias-corrected (external) curves align closely with the ideal reference line, indicating excellent calibration.\u003cstrong\u003e(b)\u003c/strong\u003e ROC curve: AUC = 0.829, demonstrating strong discriminative performance.\u003cstrong\u003e(c)\u003c/strong\u003e Clinical impact curve: Blue line (predicted high-risk cases) and red line (actual FR cases) converge at thresholds \u0026gt;0.5 (dashed line), confirming clinical utility.\u003cstrong\u003e(d)\u003c/strong\u003e Decision curve: The nomogram provides higher net benefit across the 0–1 probability range than alternative strategies.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7932870/v1/a10fea491106179c51b86781.jpeg"},{"id":108105254,"identity":"878ffa8e-e3cf-4369-bf92-a665ec738d3d","added_by":"auto","created_at":"2026-04-29 11:41:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":726493,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7932870/v1/355d1841-9df2-49ce-ace6-b3fbf956562d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analysis of Risk Factors for Futile Recanalization Following Mechanical Thrombectomy in Acute Ischemic Stroke","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAcute ischemic stroke (AIS) is an acute disease that results from reduced cerebral blood flow and brain cell damage caused by cerebrovascular stenosis or occlusion. Typical of high incidence, disability and fatality, it poses a serious threat to patients' lives and health\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Large vessel occlusion (LVO), predominantly in the anterior circulation, accounts for over one-third of AIS cases and represents a critical etiological target\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Prior to the clinical application of Mechanical Thrombectomy (MT), intravenous thrombolysis was the main recanalization therapy for AIS, and the proportion of patients with clinical benefit was limited due to strict time window (usually\u0026thinsp;\u0026le;\u0026thinsp;4.5 h) and contraindications such as bleeding transformation\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. With the advancement of endovascular therapy technology, intravenous thrombolysis combined with mechanical thrombolysis has become the main means of AIS reperfusion therapy. Compared with standard drug therapy alone, mechanical thrombectomy combined with standard drug therapy can significantly improve the functional outcomes of AIS patients\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Therefore, mechanical thrombectomy (MT) has been established as the treatment of choice for large vessel occlusive AIS (LVO-AIS) due to its advantages of direct removal of thrombus. A number of studies have confirmed that MT can not only significantly improve the neurological function prognosis of patients compared with drug therapy alone, but also has good safety\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. However, about 50% of patients with acute anterior circulation large vessel occlusion still have functional disability at 3 months after MT treatment. In 2013, some scholars defined successful vascular recanalization with modified Rankin scale (mRS) score\u0026thinsp;\u0026ge;\u0026thinsp;3 points 3 months after surgery as futile recanalization (FR)\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Endovascular therapy for anterior circulation large vessel occlusion (LVO) yields futile recanalization (FR) rates of 45%-54%\u003csup\u003e7\u003c/sup\u003e. Emerging evidence implicates multifactorial mechanisms including no-reflow phenomenon, collateral insufficiency, venous drainage impairment, and neuroinflammatory cascades in FR pathogenesis\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Identifying modifiable FR predictors could optimize patient selection and adjuvant therapies, ultimately enhancing long-term MT outcomes.\u003c/p\u003e\u003cp\u003eWhile prior studies have predominantly examined factors influencing futile recanalization (FR) post-mechanical thrombectomy (MT)\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, predictive model development remains underexplored\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. This study aims to identify FR risk factors in AIS patients achieving successful recanalization (mTICI grades 2b-3)\u003csup\u003e7\u003c/sup\u003e and develop a multivariate predictive model, thereby advancing translational strategies for optimizing endovascular treatment outcomes.\u003c/p\u003e"},{"header":"2. Data and methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 General information:\u0026nbsp;\u003c/strong\u003eThis retrospective analysis included 597 anterior circulation large vessel occlusion patients (male:female\u0026nbsp;=373:224; age range 23-99 years, mean 65.8) undergoing mechanical thrombectomy at Liaocheng Brain Hospital Stroke Center between January 2020 and June 2023.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1.1 Inclusion criteria:\u0026nbsp;\u003c/strong\u003eInclusion criteria: Age \u0026ge;18 years; Confirmed anterior circulation large vessel occlusion (LVO) involving internal carotid, middle cerebral, or anterior cerebral arteries; Successful recanalization (mTICI grade 2b-3) post-mechanical thrombectomy (MT).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1.2 Exclusion criteria:\u0026nbsp;\u003c/strong\u003eRecent stroke (\u0026le;1 year); unsuccessful recanalization (mTICI \u0026lt;2b); severe systemic comorbidities (infection, hepatorenal dysfunction, hematologic disorders, malignancies); traumatic brain injury/intracranial hemorrhage; contrast/intervention device allergies; major psychiatric disorders; incomplete clinical data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Futile Recanalization and Related Definitions:\u0026nbsp;\u003c/strong\u003eIneffective recanalization is clinically defined as a functional outcome of modified Rankin Scale (mRS) score \u0026ge;3 at 90 days post-intervention, despite achieving successful arterial recanalization (defined as mTICI or eTICI grades \u0026ge;2b) through mechanical thrombectomy. This outcome assessment applies specifically to patients demonstrating adequate angiographic reperfusion (mTICI 2b-3) following the procedure\u003csup\u003e6,10,14,15\u003c/sup\u003e. Malignant cerebral edema (MBE) is defined as life-threatening brain swelling developing within 24-48 hours of major cerebral infarction (e.g., in the MCA territory), characterized by cerebral herniation or \u0026ge;5 mm midline shift secondary to mass effect\u003csup\u003e16,17\u003c/sup\u003e. For collateral circulation evaluation, the ASITN/SIR collateral grading system classifies perfusion in ischemic territories into 0-4 grades based on digital subtraction angiography (DSA) findings, where grades 3-4 indicate robust collateral flow (associated with favorable outcomes) and grades 0-2 reflect inadequate compensation (predicting poorer prognosis)\u003csup\u003e18,19\u003c/sup\u003e. Similarly, the Tan collateral scoring system stratifies patients (0-3 grades) using CTA source images, with grades 2-3 correlating with preserved tissue viability and grades 0-1 denoting insufficient collateral recruitment\u003csup\u003e20\u003c/sup\u003e. The hyperdense vessel sign (HVS) on non-contrast CT manifests as focal hyperattenuation (CT values exceeding adjacent tissues) along occluded cerebral arteries (e.g., the MCA), serving as an early radiological indicator of major vessel occlusion\u003csup\u003e21\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Vascular Recanalization Assessment:\u0026nbsp;\u003c/strong\u003eRecanalization outcomes following endovascular therapy (including mechanical thrombectomy) were assessed using the modified Thrombolysis in Cerebral Infarction (mTICI) grading system\u003csup\u003e22\u003c/sup\u003e. Two to three experienced neurointerventionalists independently evaluated the results, with discrepancies resolved through consensus. Successful recanalization was defined as mTICI grades 2b\u0026ndash;3, while grades 0\u0026ndash;2a were classified as incomplete recanalization\u003csup\u003e7\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Statistical Analysis:\u0026nbsp;\u003c/strong\u003eData analysis and processing were performed using SPSS 26.0, R 4.3.3, and Microsoft Excel 365. Missing values were imputed via the expectation-maximization (EM) algorithm. Normally distributed continuous variables were expressed as mean\u0026nbsp;\u0026plusmn;\u0026nbsp;standard deviation (\u0026plusmn;S), with intergroup comparisons using the independent-samples t-test. Non-normally distributed continuous variables and ordinal data were presented as median and interquartile range [M(P25, P75)], and compared using the Wilcoxon Mann-Whitney U test. Categorical variables were described as n(%), with intergroup comparisons conducted via the\u0026nbsp;\u0026chi;\u0026sup2;\u0026nbsp;test.\u003c/p\u003e\n\u003cp\u003eUnivariate analysis was performed to screen influencing factors of futile recanalization (FR) after mechanical thrombectomy. Multicollinearity among factors with P\u0026lt;0.1 was assessed, and all variance inflation factors (VIF) were \u0026lt;10, confirming collinearity was within an acceptable range. Subsequent multivariate logistic regression analysis identified independent predictors of FR (P\u0026lt;0.05). A nomogram for predicting post-thrombectomy FR probability was constructed based on the regression results. The nomogram\u0026rsquo;s predictive performance was evaluated using the receiver operating characteristic (ROC) curve, with results reported as the area under the curve (AUC). A two-tailed P\u0026lt;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"3. Result","content":"\u003cp\u003e\u003cstrong\u003e3.1 Patient Characteristics:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study enrolled 597 patients, with futile recanalization (FR) occurring in 306 cases (51.3%) and successful recanalization (SR) in 291 cases. The FR group comprised 183 males (59.8%) and 123 females (40.2%), with a median age of 70 years (IQR 62-76). The SR group included 190 males (65.3%) and 101 females (34.7%), showing a younger median age of 65 years (IQR 55-73).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Univariate Analysis of Factors Associated with Futile Recanalization Following Mechanical Thrombectomy in Acute Anterior Circulation Large Vessel Occlusion\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study included 597 patients, with futile recanalization (FR) observed in 306 cases (51.3%) and successful recanalization in 291 (48.7%). Univariate analysis identified significant differences (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05) in the following variables:\u003cbr\u003e\u003cstrong\u003e3.2.1 Baseline clinical data:\u0026nbsp;\u003c/strong\u003eIncluding demographic factors (age), vascular pathology (occlusive site, TOAST classification), comorbidities (coronary heart disease, atrial fibrillation), lifestyle factors (smoking history, alcohol consumption), therapeutic interventions (intravenous thrombolysis, anticoagulation, thrombectomy parameters), and clinical indicators (preoperative NIHSS score, \u0026nbsp; admission blood pressure). \u0026nbsp; Procedural details such as first thrombolysis technique, aspiration stent combination, mTICI grades, thrombectomy frequency (\u0026gt;3 attempts), and adjunctive techniques (balloon dilation, stent implantation) were also analyzed, along with postoperative complications (ICH, HT, sICH, cerebral edema) and interventions (decompressive craniectomy). \u0026nbsp;Detailed data are presented in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.2 Biomarkers/Imaging Metrics\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003eThis study further identified significant intergroup differences in preoperative imaging parameters (Tan score, high-density sign, ASITN/SIR grade, venous visualization) and laboratory biomarkers, including inflammatory indices (neutrophil/lymphocyte counts, NLR, CRP), coagulation profiles (prothrombin time, INR, D-dimer), metabolic markers (blood glucose, LDL-C, prealbumin), cardiac function (NT-proBNP [pg/mL]), and neuroimaging severity (ASPECTS scores). Complete statistical comparisons are presented in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Multivariate Predictors of Futile Recanalization After Mechanical Thrombectomy in Acute Anterior Circulation Large Vessel Occlusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVariables with P\u0026lt;0.1 in univariate analysis were defined as independent variables, and ineffective recanalization as the dependent variable. Multicollinearity assessment was conducted for these independent variables, with results showing all variance inflation factors (VIF) \u0026lt;10, confirming multicollinearity was controlled within an acceptable range. Subsequent multivariate Logistic regression analysis indicated that history of coronary heart disease, preoperative National Institutes of Health Stroke Scale (NIHSS) score, symptomatic intracerebral hemorrhage (sICH), malignant cerebral edema within 24 h post-operation, American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology (ASITN/SIR) grade, and admission systolic blood pressure were independent influencing factors for ineffective recanalization (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Predictive Performance of a Multifactorial Model for Futile Recanalization Post-Mechanical Thrombectomy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIndependent predictors with P\u0026lt;0.05 were identified via multivariate Logistic regression, and a nomogram prediction model was constructed based on these factors (Fig. 1). Internal validation was conducted to assess the model\u0026rsquo;s predictive performance: calibration curve analysis (Fig. 2a) showed good agreement between predicted probabilities and actual observations, with the fitting curve highly overlapping the ideal reference line, indicating excellent calibration. Receiver operating characteristic (ROC) curve analysis (Fig. 2b) yielded an area under the curve (AUC) of 0.829, demonstrating good discriminative ability. Clinical impact curve analysis (Fig. 2c) revealed that when the risk threshold exceeded 0.5, the model\u0026rsquo;s predictive accuracy significantly improved in high-risk populations. Decision curve analysis (Fig. 2d) further confirmed that the nomogram provided higher net benefit than other strategies across the 0\u0026ndash;1.0 probability range, highlighting its substantial value in clinical decision-making.\u003c/p\u003e"},{"header":"4.Discussion","content":"\u003cp\u003eThis study analyzed predictors of futile recanalization (FR) following mechanical thrombectomy (MT) in patients with anterior circulation large vessel occlusion-related acute ischemic stroke (AIS-LVO), revealing an FR incidence of 51.3%. While prior studies have identified associations between FR and baseline NIHSS scores, neutrophil-to-lymphocyte ratio (NLR), and other parameters\u003csup\u003e23\u003c/sup\u003e, existing prediction models remain limited by insufficient integration of multimodal data. To address this gap, we innovatively synthesized baseline clinical characteristics (e.g., coronary artery disease history, admission systolic blood pressure), temporal metrics (onset-to-recanalization time), procedural details (thrombectomy attempts/techniques), preoperative biomarkers (NLR, blood glucose, D-dimer), and imaging signatures (venous prominence, ASITN/SIR collateral grading) for multidimensional risk assessment. Multivariable analysis identified six independent FR predictors: elevated preoperative NIHSS scores, coronary artery disease history, symptomatic intracranial hemorrhage (sICH), malignant cerebral edema, abnormal ASITN/SIR grading, and elevated admission systolic blood pressure. The derived predictive model demonstrated robust discriminative performance (AUC=0.829), establishing a quantifiable tool for stratifying post-MT FR risk in clinical practice.\u003c/p\u003e\n\u003cp\u003eEndovascular recanalization through mechanical thrombectomy (MT) remains the cornerstone of acute ischemic stroke (AIS) management, particularly for anterior circulation large vessel occlusion (LVO), with randomized trials demonstrating significant prognostic benefits\u003csup\u003e3,23\u003c/sup\u003e. However, approximately 60% of patients experience futile recanalization (FR), defined as modified Rankin Scale (mRS) scores \u0026ge;3 at 90 days post-procedure despite successful revascularization\u003csup\u003e9\u003c/sup\u003e. The pathophysiology of FR remains incompletely characterized, though current evidence implicates a multifactorial pathophysiology involving impaired collateral circulation, microvascular injury, and no-reflow phenomena\u003csup\u003e24\u0026ndash;26\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eBaseline NIHSS score, a validated prognostic marker in stroke, emerged as an independent predictor of futile recanalization (FR) in our analysis (OR=1.067, 95%CI=1.040\u0026ndash;1.094, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001). This aligns with prior evidence: Hussein et al.\u003csup\u003e27\u003c/sup\u003edemonstrated stronger FR association with NIHSS (OR=1.3, \u003cem\u003ep\u003c/em\u003e=0.001) versus sex (OR=7.7) or treatment latency (OR=1.2) in the IMS III cohort. Kim et al.\u0026nbsp;\u003csup\u003e28\u003c/sup\u003eidentified an 18.1% FR risk increase per 1-point NIHSS increment (OR=1.181, \u003cem\u003ep\u003c/em\u003e=0.012) in large infarcts. Notably, Pan et al.\u0026nbsp;\u003csup\u003e29\u003c/sup\u003ehighlighted a critical NIHSS threshold (\u0026ge;12) for FR risk escalation in multicenter data, underscoring its clinical utility for preprocedural risk stratification.\u003c/p\u003e\n\u003cp\u003eElevated admission systolic blood pressure (SBP) is an established independent risk factor for futile recanalization (FR) in acute ischemic stroke (AIS) patients undergoing mechanical thrombectomy\u003csup\u003e30\u003c/sup\u003e. Data from the DIRECT-MT multicenter trial demonstrated a significant FR association with elevated SBP (OR=4.98, 95%CI 1.87\u0026ndash;8.09)\u003csup\u003e8\u003c/sup\u003e. Pathophysiological studies suggest that hypertension exacerbates FR risk through infarct expansion and reduced tissue salvage efficiency in perfusion-diffusion mismatch regions\u003csup\u003e15,31\u003c/sup\u003e, a mechanism further corroborated by our findings.\u003c/p\u003e\n\u003cp\u003eCollateral failure is a critical predictor of futile recanalization (FR) in acute ischemic stroke. Compromised microvascular reperfusion and reperfusion injury underlie ischemia-reperfusion pathology, while robust collaterals preserve penumbral viability until revascularization, improving outcomes\u003csup\u003e26,32\u003c/sup\u003e. Our study, utilizing ASITN/SIR collateral grading, demonstrated a significant inverse association between collateral adequacy and FR risk (OR=0.754, 95%CI=0.597\u0026ndash;0.953; \u003cem\u003ep\u003c/em\u003e=0.018). ASITN/SIR grades 0\u0026ndash;1 (poor), 2 (moderate), and 3\u0026ndash;4 (robust) stratify FR risk, with grades \u0026lt;2 conferring significantly higher FR susceptibility\u003csup\u003e33\u003c/sup\u003e, aligning with Pan et al.\u0026nbsp;\u003csup\u003e29\u003c/sup\u003eand Espinosa de Rueda et al.\u0026nbsp;\u003csup\u003e34\u003c/sup\u003e.Current grading systems suffer from interobserver variability, necessitating objective multimodal assessment. Future studies aim to integrate CTA and DSA for three objectives: refining collateral scoring, optimizing thrombectomy candidacy criteria, and enhancing FR risk stratification\u003csup\u003e29\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eMCE, a recognized independent risk factor for neurological deterioration and poor functional outcomes\u003csup\u003e30\u003c/sup\u003e, was independently associated with futile recanalization (FR) post-thrombectomy (OR=3.350, 95%CI:1.833\u0026ndash;6.121; \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001). Patients with MCE exhibited significantly worse neurological outcomes versus controls (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001). Notably, while MCE represents a nonmodifiable predictor, persistent challenges in early detection due to limited sensitivity and timeliness of current imaging modalities underscore the need for advanced biomarkers or dynamic imaging protocols to refine clinical risk stratification.\u003c/p\u003e\n\u003cp\u003eSymptomatic intracranial hemorrhage (sICH) was identified as an independent risk factor for futile recanalization post-mechanical thrombectomy (OR=12.721, 95%CI:3.358-48.185, p\u0026lt;0.001). The 24-hour post-stroke window represents a critical monitoring period, as complications\u0026mdash;particularly sICH\u0026mdash;significantly impact neurological outcomes. Per ECASS II criteria, sICH was defined as radiologically confirmed intracranial hemorrhage within 24 hours post-procedure accompanied by \u0026ge;4-point NIHSS score increase\u003csup\u003e35\u003c/sup\u003e. Heitkamp et al.\u0026apos;s cohort\u003csup\u003e36\u003c/sup\u003e further validated sICH\u0026rsquo;s independent association with neurological deterioration, potentially mediated through blood-brain barrier disruption, oxidative stress, and inflammatory cascade activation.\u003c/p\u003e\n\u003cp\u003eSystematic evidence synthesis indicates that atrial fibrillation (AF) exhibits distinct pathogenic features in ischemic stroke, particularly among elderly populations. As a key risk factor for cardioembolic stroke, AF-associated strokes demonstrate greater neurological severity and poorer clinical outcomes\u003csup\u003e37\u003c/sup\u003e.\u0026nbsp;Epidemiological evidence demonstrates significant associations between atrial fibrillation (AF) and modifiable risk factors (obesity, smoking, hypertension, diabetes) as well as pre-existing cardiovascular conditions (coronary artery disease, heart failure)\u003csup\u003e37\u003c/sup\u003e. Notably, atherosclerotic pathology\u0026mdash;common in advanced age and coronary artery disease\u0026mdash;exacerbates ischemic injury by impairing early compensatory mechanisms, particularly reduced ASITN/SIR-graded collateral circulation\u003csup\u003e38\u003c/sup\u003e.\u0026nbsp;Multivariable logistic regression identified coronary artery disease history (OR=2.209, 95%CI=1.272-3.835, p=0.005) as the strongest independent predictor of futile recanalization, outperforming collateral circulation status (ASITN/SIR grade OR=0.754, 95%CI=0.597-0.953, p=0.018) and hemodynamic parameters (admission systolic blood pressure OR=1.013, 95%CI=1.001-1.026, p=0.039).\u0026nbsp;Multivariable analysis revealed that while atrial fibrillation (AF) showed significant intergroup differences, it was not independently associated with futile recanalization. This discrepancy may reflect detection bias, as routine intermittent ECG monitoring likely underestimates paroxysmal/asymptomatic AF prevalence, contributing to diagnostic underascertainment\u003csup\u003e37\u003c/sup\u003e.\u0026nbsp;These findings underscore that cardioembolic stroke prevention strategies should prioritize integrated management of atherosclerotic comorbidities (e.g., coronary artery disease) and enhanced screening for subclinical atrial fibrillation, critical for improving clinical outcomes in these high-disability, high-mortality strokes.\u003c/p\u003e\n\u003cp\u003eThe nomogram prediction model developed in this study demonstrated robust clinical utility for FR risk stratification post-mechanical thrombectomy, enabling clinicians to stratify FR risk and implement targeted preventive interventions.\u0026nbsp;This model facilitates FR risk stratification through multivariable integration. High-risk patients identified via scoring may receive preemptive interventions to mitigate FR risk, while targeted monitoring enables rapid therapeutic escalation when FR occurs, ultimately improving clinical outcomes.\u003c/p\u003e\n\u003cp\u003eThis study explored the age-dependent association with futile recanalization (FR). While multiple cohorts suggest advanced age increases FR risk in stroke patients\u003csup\u003e7,26,39\u003c/sup\u003e, potential mechanisms may involve cerebral hypoperfusion (brain atrophy, metabolic dysregulation, reduced cardiac output), impaired cerebrovascular autoregulation, and compromised collateral compensation\u003csup\u003e40,41\u003c/sup\u003e.\u0026nbsp;Beyond aging-related physiological changes, the elevated FR risk may also stem from higher cerebrovascular disease burden in the elderly [26]. However, multivariable analysis failed to identify age as an independent FR predictor.\u0026nbsp;Our findings align with Heitkamp\u0026rsquo;s cohort\u003csup\u003e36\u003c/sup\u003e, where advancing endovascular reperfusion techniques partially mitigated age-related neurological prognosis. Notably, the cohort\u0026rsquo;s pronounced age stratification (70% [n=175] aged \u0026lt;60 years) introduces confounding effects (e.g., higher baseline vasculopathy in older subgroups) that may influence outcome interpretation.\u0026nbsp;Although no independent association between age and FR was identified, future studies should control for baseline vasculopathy, stratify participants into age subgroups (e.g., \u0026ge;80 years), and extend the follow-up period to systematically evaluate age-dependent temporal effects on neurological outcomes following recanalization.\u003c/p\u003e\n\u003cp\u003eThis study has certain limitations: firstly, the single-center retrospective design carries inherent selection bias; secondly, despite routine postoperative rehabilitation, long-term follow-up data on rehabilitation after discharge are lacking, which may interfere with the assessment of long-term prognosis. To further identify the core influencing factors of futile recanalization (FR), the following studies should be prioritized: expanding the sample size and conducting multi-center cohort validation; establishing controlled studies on different anesthesia modes and vascular recanalization strategies; developing multi-dimensional prediction models incorporating radiomics, molecular biomarkers, and standardized secondary prevention; and elucidating the pathophysiological mechanism of FR and exploring novel intervention targets through basic research.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study identified coronary artery disease, elevated preprocedural NIHSS scores, symptomatic intracranial hemorrhage (sICH), malignant cerebral edema (MCE), ASITN/SIR collateral grading, and increased admission systolic blood pressure as independent predictors of futile recanalization (FR) post-mechanical thrombectomy. The multivariable model incorporating these predictors enables early FR risk quantification, facilitating personalized clinical decision-making.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFull Term\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eACA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAnterior Cerebral Artery\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAcute Ischemic Stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAPC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eArticle Processing Charge\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAPTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eActivated Partial Thromboplastin Time\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eASPECTS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAlberta Stroke Program Early CT Score\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eASITN/SIR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAmerican Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eArea Under the Curve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eConfidence Interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eC-Reactive Protein\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDiastolic Blood Pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDigital Subtraction Angiography\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDTP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDoor-to-Puncture Time\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eFutile Recanalization\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHemorrhagic Transformation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eICA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInternal Carotid Artery\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eICH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eIntracranial Hemorrhage\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eINR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInternational Normalized Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLDL-C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLow-Density Lipoprotein Cholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLVO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLarge Vessel Occlusion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMiddle Cerebral Artery\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMCE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMalignant Cerebral Edema\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMRI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMagnetic Resonance Imaging\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003emRS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003emodified Rankin Scale\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003emTICI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003emodified Thrombolysis in Cerebral Infarction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNIHSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNational Institutes of Health Stroke Scale\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNeutrophil-to-Lymphocyte Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNT-proBNP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eN-terminal pro-B-type Natriuretic Peptide\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOdds Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOTD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOnset-to-Door Time\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOTP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOnset-to-Puncture Time\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOTR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOnset-to-Recanalization Time\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePTR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePuncture-to-Recanalization Time\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eROC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eReceiver Operating Characteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSystolic Blood Pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003esICH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSymptomatic Intracranial Hemorrhage\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTOAST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTrial of Org 10172 in Acute Stroke Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTransient Ischemic Attack\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eWhite Blood Cell\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors declared no conflict of interest.\u003c/p\u003e\n\u003ch2\u003eEthical approval\u003c/h2\u003e\n\u003cp\u003eThis retrospective study adhered to the Helsinki Declaration and was approved by the Ethics Committee of Liaocheng People\u0026rsquo;s Hospital, Shandong Province. Written informed consent was obtained from all participants or their legal guardians.\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGenerative AI and AI-assisted technologies were NOT used in the preparation of this work.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthor Contributions:Hongyang Guo: Conceptualization, Methodology, Writing \u0026ndash; Original DraftTanggui Sun: Data Curation, Formal Analysis, VisualizationZhongchen Li: Review \u0026amp; EditingTengkun Yin: Supervision, Writing \u0026ndash; ReviewJiheng Hao: ReviewWenyu Zhang: Data Curation, Formal Analysis, VisualizationXu Zan: Data CurationLiyong Zhang: Review \u0026amp; Editing\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWalter K. What Is Acute Ischemic Stroke? \u003cem\u003eJAMA\u003c/em\u003e. 2022;327(9):885. doi:10.1001/jama.2022.1420\u003c/li\u003e\n\u003cli\u003eJia B, Ren Z, Mokin M, et al. 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Predictors of malignant cerebral edema in cerebral artery infarction: A meta-analysis. \u003cem\u003eJournal of the Neurological Sciences\u003c/em\u003e. 2020;409:116607. doi:10.1016/j.jns.2019.116607\u003c/li\u003e\n\u003cli\u003eHigashida RT, Furlan AJ. Trial Design and Reporting Standards for Intra-Arterial Cerebral Thrombolysis for Acute Ischemic Stroke. \u003cem\u003eStroke\u003c/em\u003e. 2003;34(8). doi:10.1161/01.STR.0000082721.62796.09\u003c/li\u003e\n\u003cli\u003eRan N, Wang H. Predictive value of early serum ACSL4 and ASITN/SIR grade for motor function recovery in patients with post-ischemic stroke lower limb neurological sequelae after modified constraint-induced movement therapy. \u003cem\u003eClinical Neurology and Neurosurgery\u003c/em\u003e. 2024;245:108464. doi:10.1016/j.clineuro.2024.108464\u003c/li\u003e\n\u003cli\u003eBaydemir R, Ayka\u0026ccedil; \u0026Ouml;, Acar BA, et al. Role of modified TAN score in predicting prognosis in patients with acute ischemic stroke undergoing endovascular therapy. \u003cem\u003eClinical Neurology and Neurosurgery\u003c/em\u003e. 2021;210:106978. doi:10.1016/j.clineuro.2021.106978\u003c/li\u003e\n\u003cli\u003eChieng J, Singh D, Chawla A, Peh W. The hyperdense vessel sign in cerebral computed tomography: pearls and pitfalls. \u003cem\u003esmedj\u003c/em\u003e. 2020;61(5):230-237. doi:10.11622/smedj.2020074\u003c/li\u003e\n\u003cli\u003eShiraz Bhurwani MM, Snyder KV, Waqas M, et al. Use of quantitative angiographic methods with a data-driven model to evaluate reperfusion status (mTICI) during thrombectomy. \u003cem\u003eNeuroradiology\u003c/em\u003e. 2021;63(9):1429-1439. doi:10.1007/s00234-020-02598-3\u003c/li\u003e\n\u003cli\u003eWang LR, Li BH, Zhang Q, et al. Predictors of futile recanalization after endovascular treatment of acute ischemic stroke. \u003cem\u003eBMC Neurol\u003c/em\u003e. 2024;24(1):207. doi:10.1186/s12883-024-03719-8\u003c/li\u003e\n\u003cli\u003eShi Z, Duckwiler GR, Jahan R, et al. Early Blood‐Brain Barrier Disruption after Mechanical Thrombectomy in Acute Ischemic Stroke. \u003cem\u003eJournal of Neuroimaging\u003c/em\u003e. 2018;28(3):283-288. doi:10.1111/jon.12504\u003c/li\u003e\n\u003cli\u003eWeiss D, Kraus B, Rubbert C, et al. Systematic evaluation of computed tomography angiography collateral scores for estimation of long-term outcome after mechanical thrombectomy in acute ischaemic stroke. \u003cem\u003eNeuroradiol J\u003c/em\u003e. 2019;32(4):277-286. doi:10.1177/1971400919847182\u003c/li\u003e\n\u003cli\u003eNie X, Pu Y, Zhang Z, Liu X, Duan W, Liu L. Futile Recanalization after Endovascular Therapy in Acute Ischemic Stroke. \u003cem\u003eBioMed Research International\u003c/em\u003e. 2018;2018:1-5. doi:10.1155/2018/5879548\u003c/li\u003e\n\u003cli\u003eHussein HM, Saleem MA, Qureshi AI. Rates and predictors of futile recanalization in patients undergoing endovascular treatment in a multicenter clinical trial. \u003cem\u003eNeuroradiology\u003c/em\u003e. 2018;60(5):557-563. doi:10.1007/s00234-018-2016-2\u003c/li\u003e\n\u003cli\u003eKim H, Kim JT, Choi KH, et al. Futile recanalization after endovascular treatment in acute ischemic stroke with large ischemic core. \u003cem\u003eBMC Neurol\u003c/em\u003e. 2024;24(1):395. doi:10.1186/s12883-024-03912-9\u003c/li\u003e\n\u003cli\u003ePan H, Lin C, Chen L, et al. Multiple-Factor Analyses of Futile Recanalization in Acute Ischemic Stroke Patients Treated With Mechanical Thrombectomy. \u003cem\u003eFront Neurol\u003c/em\u003e. 2021;12:704088. doi:10.3389/fneur.2021.704088\u003c/li\u003e\n\u003cli\u003eZeng W, Li W, Huang K, et al. Predicting futile recanalization, malignant cerebral edema, and cerebral herniation using intelligible ensemble machine learning following mechanical thrombectomy for acute ischemic stroke. \u003cem\u003eFront Neurol\u003c/em\u003e. 2022;13:982783. doi:10.3389/fneur.2022.982783\u003c/li\u003e\n\u003cli\u003eNeuberger U, Vollmuth P, Nagel S, et al. Optimal thresholds to predict long-term outcome after complete endovascular recanalization in acute anterior ischemic stroke. \u003cem\u003eJ NeuroIntervent Surg\u003c/em\u003e. 2021;13(12):1124-1127. doi:10.1136/neurintsurg-2020-016997\u003c/li\u003e\n\u003cli\u003eBinder NF, El Amki M, Gl\u0026uuml;ck C, et al. Leptomeningeal collaterals regulate reperfusion in ischemic stroke and rescue the brain from futile recanalization. \u003cem\u003eNeuron\u003c/em\u003e. 2024;112(9):1456-1472.e6. doi:10.1016/j.neuron.2024.01.031\u003c/li\u003e\n\u003cli\u003eHigashida RT, Furlan AJ. Trial Design and Reporting Standards for Intra-Arterial Cerebral Thrombolysis for Acute Ischemic Stroke. \u003cem\u003eStroke\u003c/em\u003e. 2003;34(8). doi:10.1161/01.STR.0000082721.62796.09\u003c/li\u003e\n\u003cli\u003eEspinosa De Rueda M, Parrilla G, Manzano-Fern\u0026aacute;ndez S, et al. Combined Multimodal Computed Tomography Score Correlates With Futile Recanalization After Thrombectomy in Patients With Acute Stroke. \u003cem\u003eStroke\u003c/em\u003e. 2015;46(9):2517-2522. doi:10.1161/STROKEAHA.114.008598\u003c/li\u003e\n\u003cli\u003eHacke W, Kaste M, Fieschi C, et al. Randomised double-blind placebo-controlled trial of thrombolytic therapy with intravenous alteplase in acute ischaemic stroke (ECASS II). \u003cem\u003eThe Lancet\u003c/em\u003e. 1998;352(9136):1245-1251. doi:10.1016/S0140-6736(98)08020-9\u003c/li\u003e\n\u003cli\u003eHeitkamp C, Heitkamp A, Winkelmeier L, et al. Predictors of futile recanalization in ischemic stroke patients with low baseline NIHSS. \u003cem\u003eInternational Journal of Stroke\u003c/em\u003e. 2024;19(10):1102-1112. doi:10.1177/17474930241264737\u003c/li\u003e\n\u003cli\u003ePistoia F, Sacco S, Tiseo C, Degan D, Ornello R, Carolei A. The Epidemiology of Atrial Fibrillation and Stroke. \u003cem\u003eCardiology Clinics\u003c/em\u003e. 2016;34(2):255-268. doi:10.1016/j.ccl.2015.12.002\u003c/li\u003e\n\u003cli\u003eRitvonen J, Sairanen T, Silvennoinen H, et al. Comatose With Basilar Artery Occlusion: Still Odds of Favorable Outcome With Recanalization Therapy. \u003cem\u003eFront Neurol\u003c/em\u003e. 2021;12:665317. doi:10.3389/fneur.2021.665317\u003c/li\u003e\n\u003cli\u003eHeitkamp C, Winkelmeier L, Heit JJ, et al. Unfavorable cerebral venous outflow is associated with futile recanalization in acute ischemic stroke patients. \u003cem\u003eEuro J of Neurology\u003c/em\u003e. 2023;30(9):2684-2692. doi:10.1111/ene.15898\u003c/li\u003e\n\u003cli\u003eMokhber N, Shariatzadeh A, Avan A, et al. Cerebral blood flow changes during aging process and in cognitive disorders: A review. \u003cem\u003eNeuroradiol J\u003c/em\u003e. 2021;34(4):300-307. doi:10.1177/19714009211002778\u003c/li\u003e\n\u003cli\u003eReinhard M, Rutsch S, Lambeck J, et al. Dynamic cerebral autoregulation associates with infarct size and outcome after ischemic stroke: Cerebral autoregulation in ischemic stroke. \u003cem\u003eActa Neurologica Scandinavica\u003c/em\u003e. 2012;125(3):156-162. doi:10.1111/j.1600-0404.2011.01515.x\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. General and Clinical Characteristics of Successful Recanalization Group and Failed Recanalization Group\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRecanalization Group\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"567\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eFactor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eSuccessful Recanalization Group (n=291)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eFailed Recanalization Group (n=306)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.166\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e190 (65.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e183 (59.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e101 (34.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e123 (40.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge [M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e65 (55, 73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e70 (62, 76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOcclusion Site [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- Internal carotid artery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e92 (31.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e121 (39.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- Tandem lesion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e159 (54.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e153 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- Middle cerebral artery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e37 (12.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e26 (8.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- Other arteries\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e3 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e6 (2.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSide [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.683\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- Left\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e158 (54.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e172 (56.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- Right\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e133 (45.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e134 (43.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntravenous Thrombolysis [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e172 (59.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e153 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOAST Classification [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- Intracranial artery stenosis/occlusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e142 (48.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e100 (32.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- Extracranial tandem lesion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e24 (8.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e24 (7.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- Cardioembolic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e78 (26.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e134 (43.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e47 (16.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e48 (15.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e189 (64.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e215 (70.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.165\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e63 (21.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e74 (24.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.462\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHyperlipidemia [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e105 (36.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e100 (32.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.381\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoronary Artery Disease [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e42 (14.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e81 (26.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAtrial Fibrillation [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e73 (25.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e138 (45.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMyocardial Infarction [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e3 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.652\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking History [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e90 (30.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e73 (23.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol History [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e100 (34.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e75 (24.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStroke History [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e51 (17.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e63 (20.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.341\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnticoagulation [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e6 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e14 (4.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnti-platelet [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e35 (12.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e43 (14.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.463\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative NIHSS [M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e13 (8, 20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e22 (15, 30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePostoperative 24h ICH [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e62 (21.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e156 (51.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHemorrhagic Transformation (HT) [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e55 (18.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e146 (47.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptomatic ICH (sICH) [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e3 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e63 (20.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePostoperative 72h ICH [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e4 (1.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e8 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCerebral Edema [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e111 (38.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e83 (27.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMalignant Cerebral Edema [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e38 (13.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e152 (49.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnesthesia [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.487\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- Local anesthesia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- General anesthesia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e290 (99.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e306 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInitial mTICI Post-thrombectomy [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e37 (12.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e69 (22.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e10 (3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e9 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- 2a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e70 (24.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e53 (17.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- 2b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e57 (19.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e48 (15.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e117 (40.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e127 (41.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Thrombectomy Attempts [M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1 (1, 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e2 (1, 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eThrombectomy Attempts \u0026gt;3 [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e47 (16.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e79 (25.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRescue Techniques [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e168 (57.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e111 (36.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBalloon Angioplasty [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e149 (51.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e210 (68.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e131 (45.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e94 (30.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e9 (3.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e2 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e2 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStent Placement [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e149 (51.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e99 (32.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntra-arterial Medication [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e55 (18.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e53 (17.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.616\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFinal mTICI Post-procedure [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- 2b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e11 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e23 (7.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e- 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e280 (96.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e283 (92.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEarly Venous Filling [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e26 (8.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e34 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.377\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOTD (Onset-to-Door Time) [min; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e180 (113, 295)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e177 (103, 270)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.556\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDTP (Door-to-Puncture Time) [min; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e109 (89, 151)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e109 (87, 148)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.661\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOTP (Onset-to-Puncture Time) [min; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e310 (227, 430)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e300 (219, 406)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.419\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePTR (Puncture-to-Recanalization Time) [min; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e81 (58, 108)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e78 (58, 110)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.984\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOTR (Onset-to-Recanalization Time) [min; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e403 (313, 544)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e395.5 (299.5, 530.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.601\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePostoperative Decompressive Craniectomy [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1 (0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e15 (4.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBifurcation Occlusion [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e178 (61.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e196 (64.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.467\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative Tan Score [M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e2 (1, 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1 (1, 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative Hyperdense Sign [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e85 (29.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e139 (45.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eASITN/SIR Grade [M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1 (0, 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1 (0, 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdmission SBP [mmHg; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e147 (135, 162)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e155.5 (142, 168)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdmission DBP [mmHg; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e86 (78, 96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e89 (80, 98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eM (P25, P75):\u003c/strong\u003e Median (25th percentile, 75th percentile).\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eNIHSS:\u003c/strong\u003e National Institutes of Health Stroke Scale.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eICH:\u003c/strong\u003e Intracranial hemorrhage.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003emTICI:\u003c/strong\u003e Modified Thrombolysis in Cerebral Infarction scale.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cem\u003eData presented as n (%) or median (interquartile range). Statistical significance set at P \u0026lt; 0.05.\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Laboratory and Imaging Data of Successful Recanalization Group and Ineffective Recanalization Group\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"567\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eFactor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eSuccessful Recanalization Group (n=291)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eFailed Recanalization Group (n=306)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative WBC [\u0026times;10⁹/L; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e7.45 (6.11, 9.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e7.83 (6.33, 9.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.153\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative Neutrophil [\u0026times;10⁹/L; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e5.22 (3.97, 7.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e5.66 (4.27, 7.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative Lymphocyte [\u0026times;10⁹/L; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e1.50 (1.10, 2.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e1.31 (0.91, 1.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative NLR [M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e3.69 (2.16, 5.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e4.44 (2.74, 7.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative Platelet [\u0026times;10⁹/L; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e200.00 (170.00, 235.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e190.00 (159.00, 223.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative Glucose [mmol/L; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e7.00 (6.07, 8.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e7.61 (6.49, 9.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative CRP [mg/L; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e1.30 (0.60, 4.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e1.70 (0.70, 6.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProthrombin Time [s; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e11.30 (10.80, 11.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e11.40 (10.90, 12.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eINR [M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e1.05 (1.01, 1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e1.07 (1.02, 1.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAPTT [s; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e31.2 (29.20, 33.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e31.10 (28.80, 33.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.561\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAPTT Ratio [M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e1.01 (0.94, 1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e1.00 (0.93, 1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.222\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eD-dimer [mg/L; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.50 (0.30, 1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.80 (0.40, 2.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLDL-C [mmol/L; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e2.63 (2.15, 3.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e2.55 (1.98, 3.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrealbumin [mg/L; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e252.00 (207.00, 287.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e234.00 (198.75, 274.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative NT-proBNP [pg/mL; M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e152.00 (81.00, 341.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e292.50 (115.33, 983.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative ASPECTS Score [M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e8 (6, 9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e7 (4, 8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative Tan Score [M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e2 (1, 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e1 (1, 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative Hyperdense Sign [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e85 (29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e139 (45.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eASITN/SIR Grade [M (P25, P75)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e1 (0, 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e1 (0, 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBifurcation Occlusion [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e178 (61.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e196 (64.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.467\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEarly Venous Filling [n (%)]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e26 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e34 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0.377\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eASITN/SIR:\u003c/strong\u003e American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eASPECTS:\u003c/strong\u003e Alberta Stroke Program Early CT Score.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eCRP:\u003c/strong\u003e C-reactive protein.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eINR:\u003c/strong\u003e International normalized ratio.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAPTT:\u003c/strong\u003e Activated partial thromboplastin time.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eLDL-C:\u003c/strong\u003e Low-density lipoprotein cholesterol.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eNT-proBNP:\u003c/strong\u003e N-terminal pro-B-type natriuretic peptide.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cem\u003eData presented as n (%) or median (interquartile range). Statistical significance set at P \u0026lt; 0.05.\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Multivariate Logistic Regression Analysis of Predictors of Failed Recanalization After Mechanical Thrombectomy\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"605\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003ePredictor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eRegression Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eOdds Ratio (OR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of Coronary Artery Disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e2.209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1.272\u0026ndash;3.835\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative NIHSS Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1.040\u0026ndash;1.094\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003esICH (Symptomatic Intracranial Hemorrhage)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e2.543\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e12.721\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e3.358\u0026ndash;48.185\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMalignant Cerebral Edema\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1.209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e3.350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1.833\u0026ndash;6.121\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eASITN/SIR Grade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e-0.282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.597\u0026ndash;0.953\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdmission Systolic Blood Pressure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1.001\u0026ndash;1.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eNIHSS:\u003c/strong\u003e National Institutes of Health Stroke Scale.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003esICH:\u003c/strong\u003e Symptomatic intracranial hemorrhage.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eASITN/SIR:\u003c/strong\u003e American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eCI:\u003c/strong\u003e Confidence interval.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cem\u003eData presented as regression coefficients, odds ratios (OR), and 95% confidence intervals (CI). Statistical significance set at P \u0026lt; 0.05.\u003c/em\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Acute ischemic stroke, Large vessel occlusion, Mechanical thrombectomy, Futile recanalization, Risk factors","lastPublishedDoi":"10.21203/rs.3.rs-7932870/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7932870/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground and Purpose\u003c/h2\u003e\u003cp\u003eMechanical thrombectomy (MT), while effectively enhancing recanalization in acute ischemic stroke (AIS), still results in futile recanalization (FR) \u0026mdash; absent functional recovery despite reperfusion success \u0026mdash; in approximately 50% of cases. This study investigates FR-associated risk factors, refines patient selection and thrombectomy procedures, and explores targeted therapies addressing FR pathophysiology, ultimately aiming to reduce FR incidence and improve outcomes in MT-treated AIS patients.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis retrospective cohort study included 597 AIS patients with anterior circulation LVO undergoing MT (2020\u0026ndash;2023). Patients were stratified by 90-day mRS into ER (mRS\u0026thinsp;\u0026lt;\u0026thinsp;3, n\u0026thinsp;=\u0026thinsp;291) and FR (mRS\u0026thinsp;\u0026ge;\u0026thinsp;3, n\u0026thinsp;=\u0026thinsp;306) groups. Demographic, clinical, and intraoperative imaging data were analyzed. Univariate and multivariate logistic regression (P\u0026thinsp;\u0026lt;\u0026thinsp;0.1 threshold) identified independent FR risk factors.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eMultivariate analysis identified coronary artery disease(OR\u0026thinsp;=\u0026thinsp;2.209, 95% CI 1.272\u0026ndash;3.835), higher preoperative NIHSS scores(OR\u0026thinsp;=\u0026thinsp;1.067, 95% CI 1.040\u0026ndash;1.094), symptomatic intracranial hemorrhage(OR\u0026thinsp;=\u0026thinsp;12.721, 95% CI 3.358\u0026ndash;48.185), Malignant cerebral edema (OR\u0026thinsp;=\u0026thinsp;3.350, 95% CI 1.833\u0026ndash;6.121), ASITN/SIR collateral grade (OR\u0026thinsp;=\u0026thinsp;1.013, 95% CI 1.001\u0026ndash;1.026), and elevated admission SBP (1.013[1.001\u0026ndash;1.026]) as independent predictors of futile recanalization. The nomogram prediction model based on the above factors shows that the area under the subject operating characteristic curve (AUC) is 0.829, which shows a good prediction effect.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThis study identified key determinants of futile recanalization (FR) after mechanical thrombectomy (MT) in acute large vessel occlusion stroke. The validated nomogram demonstrated robust predictive utility for post-MT FR, offering translational insights and actionable therapeutic targets to optimize endovascular outcomes.\u003c/p\u003e","manuscriptTitle":"Analysis of Risk Factors for Futile Recanalization Following Mechanical Thrombectomy in Acute Ischemic Stroke","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-14 16:06:13","doi":"10.21203/rs.3.rs-7932870/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"42f232bc-0bc0-450d-b897-0c060666572b","owner":[],"postedDate":"November 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-29T11:40:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-14 16:06:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7932870","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7932870","identity":"rs-7932870","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}