The Role of Thrombin Time as an Independent Variable in Predicting In-Stent Stenosis Risk After Flow Diverter Treatment for Intracranial Aneurysms: A Retrospective Cohort Study

The Role of Thrombin Time as an Independent Variable in Predicting In-Stent Stenosis Risk After Flow Diverter Treatment for Intracranial Aneurysms: A Retrospective Cohort Study | 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 The Role of Thrombin Time as an Independent Variable in Predicting In-Stent Stenosis Risk After Flow Diverter Treatment for Intracranial Aneurysms: A Retrospective Cohort Study Zhikun Jia, Jiayin Ma, Qile He, Jialin Gao, Qiyu Xie, Zhichao Wu, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6384391/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Oct, 2025 Read the published version in Neurosurgical Review → Version 1 posted 9 You are reading this latest preprint version Abstract Unruptured intracranial aneurysms are common neurovascular diseases, and flow diverters (FD) are emerging as a key treatment modality. However, in-stent stenosis (ISS) remains a frequent complication following FD treatment, increasing thromboembolic risks. Thrombin time (TT), a critical coagulation indicator, has potential associations with ISS risk. To investigate the relationship between TT and ISS risk, focusing on potential threshold effects. This multicenter retrospective cohort study included 394 patients with unruptured intracranial aneurysms treated with FD between March 2016 and October 2024. The primary exposure was preoperative TT, and the primary outcome was ISS occurrence during follow-up. Generalized additive models explored non-linear relationships, with segmented linear regression determining threshold points. ISS occurred in 22.84% (90/394) of patients. TT exhibited a non-linear relationship with ISS risk, with a threshold of 19.2 seconds. For TT values below this threshold, each unit increase was linked to a 59% higher likelihood of developing ISS (OR = 1.59, 95% CI: 1.19–2.13, p = 0.002). These findings may assist in identifying patients at greater risk for ISS who could benefit from more intensive intervention. intracranial aneurysm flow diverter thrombin time stenosis Figures Figure 1 INTRODUCTION Intracranial aneurysms represent a significant neurological issue, with global prevalence rates ranging from 3–5%, and notable geographic variation, as indicated by the higher 7% rate found in Chinese populations[ 1 – 4 ]. Flow diverter (FD) interventions, while demonstrating validated safety and therapeutic success in the treatment of intracranial aneurysms[ 5 ], remain associated with the substantial post-procedural complication of in-stent stenosis (ISS)[ 6 ]. In a study involving 240 patients with intracranial aneurysms who underwent 252 FD implantation procedures, ISS was identified in 135 (53.6%) lesions, with severity categorized as mild in 66 (48.9%), moderate in 52 (38.5%), and severe in 17 (12.6%) cases[ 7 ]. This complication not only jeopardizes long-term treatment efficacy but also elevates the risk of thromboembolic events and requires extended anti-platelet therapy. Thrombin time (TT) is a coagulation assay measuring the conversion of fibrinogen to fibrin in the common pathway of blood coagulation, specifically reflecting the final stage of clot formation[ 8 ]. Prolonged TT values indicate decreased thrombin activity or fibrinogen dysfunction, while shortened values suggest hypercoagulability states[ 9 ]. Recent studies have demonstrated significant associations between TT and the incidence of adverse outcomes of various pathologies. In hypercholesterolemic hamster models of vascular stenosis[ 10 ], researchers identified mechanisms whereby elevated low-density lipoprotein (LDL) levels promote thrombosis and vascular narrowing through alterations in coagulation parameters, specifically TT. A separate investigation examining microplastic effects on stenosis revealed significantly prolonged TT in the ECAS cohort compared to control subjects[ 11 ]. These established correlations underscore the clinical significance of monitoring and managing TT parameters in medical practice. Available evidence suggests that alterations in TT may serve as predictive indicators for ISS risk. In a comparative investigation of bivalirudin versus heparin in percutaneous coronary intervention[ 12 ], findings indicated that bivalirudin potentially reduces post-procedural vascular stenosis and thrombotic events by stabilizing coagulation parameters, including TT. When examining various stent materials' influence on platelet reactivity and coagulation activation[ 13 ], researchers determined through TT assessment that heparin-coated stents mitigate post-implantation thrombosis and vascular stenosis risks via modulation of coagulation profiles. Nevertheless, the literature currently lacks reports evaluating TT as a prognostic marker for ISS following flow diversion device treatment of intracranial aneurysms. In our clinical practice, we observed reduced TT levels in certain patients with ISS; however, whether this reduction constitutes an independent risk factor for ISS or merely reflects concurrent phenomena remains unclear. To address this question, we conducted a multicenter retrospective cohort study evaluating the association between TT and ISS among patients with intracranial aneurysms treated with flow diversion devices between March 2016 and October 2024. Additionally, we explored the potential threshold effects of TT in predicting ISS risk, aiming to provide scientific evidence for developing individualized anticoagulation protocols that could improve patient outcomes. Our study design incorporated an extended outcome assessment period of 6 to 24 months to enhance the reliability and clinical applicability of our findings. METHODS Study Population This multicenter retrospective cohort study evaluated patients with intracranial aneurysms treated with FD devices between March 2016 and October 2024. Patients were enrolled from multiple centers after approval from institutional ethics committees. Given the retrospective nature, informed consent was waived. The investigation focused on examining the association between preoperative TT and ISS, with particular emphasis on potential threshold effects to inform individualized anticoagulation protocols. Follow-up assessments were conducted over 6–24 months to maximize clinical relevance. Variables The primary exposure variable was TT, measured from venous blood samples collected within 24 hours of admission using a Sysmex CS-5100 automated coagulation analyzer (Sysmex Corporation, Japan) with Siemens Healthcare reagent kits. Blood was drawn in a fasting state using vacuum tubes containing 3.2% sodium citrate. TT was recorded as a continuous variable (seconds), with a normal reference range of 14–21 seconds. We also categorized TT by tertiles to explore non-linear relationships. The primary outcome was ISS, defined as ≥ 25% luminal narrowing at digital subtraction angiography (DSA) follow-up. DSA images were independently evaluated by two neurointerventional radiologists blinded to clinical data and exposure variables. Stenosis severity was stratified as mild (25–50%), moderate (50–75%), or severe (> 75%). Covariates included: demographic characteristics (sex, age); vascular risk factors (hypertension, diabetes, hyperlipidemia, smoking); aneurysm characteristics (circulation location, morphology, diameter, neck width, proximal artery diameter); treatment-related factors (FD type); and laboratory parameters (platelet count, prothrombin time/activity, fibrinogen, D-dimer, liver function, red blood cell count). These covariates were selected based on existing literature and biological plausibility to control for potential confounding factors. Hypertension, diabetes, and hyperlipidemia were determined based on previous diagnoses or current medication use. Missing data, comprising less than 5% of the dataset, were handled using multiple imputation techniques, with sensitivity analyses employing complete case analysis to verify the robustness of our findings. All variable definitions and measurement methods were documented according to standardized operating procedures. Endovascular Procedures All patients received dual antiplatelet therapy (DAPT) 5 days before FD treatment, comprising aspirin (100 mg once daily) plus either clopidogrel (75 mg once daily) or ticagrelor (45 mg twice daily). Platelet aggregation capacity was assessed one day before the procedure. Interventions were performed under intravenous anesthesia with systemic heparinization. 3D DSA was acquired using a Philips Integris V system (Philips Healthcare, Eindhoven, Netherlands). FD dimensions were tailored to individual parent vessel and aneurysm characteristics. Heparin reversal was not performed post-procedure. After discharge, patients continued DAPT for 6 months, followed by aspirin monotherapy for 6–12 months. Follow-up DSA was performed at minimum 6 months post-intervention to evaluate ISS. Definition of stenosis rate The stenosis rate (SR) was calculated using the formula[ 14 ]: $$\:SR=(1-\frac{\:No.n\:follow\:-\:up\:In\:-\:stent\:artery\:Diameter\:\left(\:Dn\:\right)}{\:operation\:In\:-\:stent\:artery\:Diameter\:\left(\:Do\:\right)})\times\:100\%$$ Definition of ISS and outcome assessment Intimal hyperplasia was defined as a uniform growth process beyond the limits of the metallic mesh at 75%). The primary outcome, ISS, was assessed through DSA examinations performed at least 6 months after the procedure. ISS evaluation was conducted independently by two neurointerventional radiologists with over 10 years of experience using a double-blind method, with ISS positivity defined as stenosis ≥ 25%. Statistical Analysis Continuous variables were presented as mean ± standard deviation (normal distribution) or median (minimum, maximum) (skewed distribution). Categorical variables were expressed as frequencies/percentages. Between-group comparisons employed chi-square tests (categorical variables), Student's t-tests (normal distribution), or Mann-Whitney U tests (skewed distribution). The TT-ISS relationship was examined using a two-step approach: First, three progressive adjustment regression models (unadjusted, sociodemographic-adjusted, fully-adjusted) evaluated effect robustness; Second, Generalized Additive Models and smooth curve fitting explored non-linear relationships, with inflection points calculated and two-piecewise linear models constructed when non-linearity was detected. All analyses were performed using R software (P < 0.05 considered statistically significant). RESULTS Baseline Characteristics Stratified by TT Tertiles Baseline characteristics of participants shown in Table 1 . ISS occurred in 22.84% (90/394) of patients. Patients in the highest TT tertile exhibited significantly lower fibrinogen levels (2.69 ± 0.64 g/L vs. 3.05 ± 0.78 g/L in the lowest tertile; p < 0.001) and shorter prothrombin time (11.30 ± 1.03s vs. 11.67 ± 0.82s; p = 0.002). Prothrombin time activity was significantly elevated in both middle and high tertiles compared to the low tertile (106.40 ± 7.65% and 106.96 ± 7.88% vs. 102.64 ± 7.92%, respectively; p < 0.001). Proximal artery diameter demonstrated a non-linear distribution, with the middle tertile exhibiting the smallest diameter (3.90 ± 0.79mm compared to 4.24 ± 0.90mm and 4.19 ± 0.74mm in low and high tertiles, respectively; p = 0.002). Notably, both hypertension prevalence (43.3–28.9%; p = 0.047) and smoking rates (19.7–7.0%; p = 0.006) decreased significantly with increasing TT tertiles. Table 1 The baseline characteristics of patients TT Tertile Low(n = 127) Middle(n = 120) High(n = 142) Mean ± SD/ N (%) P-value TT 15.91 ± 0.64 17.32 ± 0.26 18.46 ± 0.73 < 0.001* Age 55.68 ± 11.31 52.86 ± 12.13 54.48 ± 10.70 0.149 Platelet Count 245.24 ± 61.43 255.95 ± 65.47 245.05 ± 59.00 0.286 Activated Partial Thromboplastin Time 28.24 ± 4.72 28.65 ± 4.14 28.95 ± 4.25 0.413 Prothrombin Time 11.67 ± 0.82 11.32 ± 0.95 11.30 ± 1.03 0.002* Fibrinogen 3.05 ± 0.78 2.84 ± 0.61 2.69 ± 0.64 < 0.001* Body Mass Index 23.80 ± 3.99 23.67 ± 4.80 23.65 ± 3.09 0.951 D-Dimer 0.62 ± 2.11 0.43 ± 0.54 0.60 ± 2.02 0.650 Aneurysm Diameter 5.98 ± 5.02 6.19 ± 4.03 6.90 ± 6.37 0.322 Aneurysm Neck 5.08 ± 2.96 5.28 ± 2.96 5.09 ± 3.55 0.861 Hematocrit 0.39 ± 0.04 0.39 ± 0.04 0.40 ± 0.04 0.453 Distal Artery Diameter 3.61 ± 0.79 3.54 ± 0.78 3.69 ± 0.80 0.312 Proximal Artery Diameter 4.24 ± 0.90 3.90 ± 0.79 4.19 ± 0.74 0.002* Prothrombin Time Activity 102.64 ± 7.92 106.96 ± 7.88 106.40 ± 7.65 < 0.001* Red Blood Cell Count 4.36 ± 0.50 4.45 ± 0.54 4.40 ± 0.46 0.364 Hemoglobin 127.39 ± 15.13 126.71 ± 13.66 129.34 ± 14.30 0.306 Alanine Aminotransferase 19.21 ± 13.14 16.55 ± 6.94 19.99 ± 10.42 0.029* Sex 0.148 No 84 (66.1%) 92 (76.7%) 96 (67.6%) Yes 43 (33.9%) 28 (23.3%) 46 (32.4%) Hypertension 0.047* No 72 (56.7%) 78 (65.0%) 101 (71.1%) Yes 55 (43.3%) 42 (35.0%) 41 (28.9%) Diabetes 0.677 No 113 (89.0%) 108 (90.0%) 123 (86.6%) Yes 14 (11.0%) 12 (10.0%) 19 (13.4%) Hyperlipidemia 0.126 Yes 97 (76.4%) 81 (67.5%) 93 (65.5%) No 30 (23.6%) 39 (32.5%) 49 (34.5%) Smoke 0.006* No 102 (80.3%) 107 (89.2%) 132 (93.0%) Yes 25 (19.7%) 13 (10.8%) 10 (7.0%) Anterior Circulation 0.404 No 10 (7.9%) 5 (4.2%) 7 (4.9%) Yes 117 (92.1%) 115 (95.8%) 135 (95.1%) Morphology 0.295 Saccular 117 (92.1%) 111 (92.5%) 133 (93.7%) Fusiform 3 (2.4%) 7 (5.8%) 5 (3.5%) Dissecting 7 (5.5%) 2 (1.7%) 4 (2.8%) Overlapping Stents 0.355 No 124 (97.6%) 113 (94.2%) 137 (96.5%) Yes 3 (2.4%) 7 (5.8%) 5 (3.5%) Flow Diverter 0.289 Tubridge Flow Diverter 59 (46.5%) 66 (55.0%) 78 (54.9%) Pipeline Embolization Device 68 (53.5%) 54 (45.0%) 64 (45.1%) ISS 0.126 0 106 (83.5%) 88 (73.3%) 107 (75.4%) 1 21 (16.5%) 32 (26.7%) 35 (24.6%) Statistical results are reported as mean ± SD or number (%). *Statistical significance Continuous variable was obtained by Kruskal-Wallis rank sum test. If the count variable had a theoretical number < 10, the probability was calculated accurately using Fisher's exact test Univariate Analysis Results The results of univariate analysis are shown in Table 2 . In our cohort of intracranial aneurysm patients, stratification by TT tertiles revealed several significant hemostatic and clinical differences. Patients in the high TT tertile demonstrated significantly lower fibrinogen levels (2.69 ± 0.64 g/L vs. 3.05 ± 0.78 g/L in the low tertile; p < 0.001) and shorter prothrombin time (11.30 ± 1.03 s vs. 11.67 ± 0.82 s; p = 0.002). Correspondingly, prothrombin time activity was elevated in both middle and high tertiles compared to the low tertile (106.40 ± 7.65% and 106.96 ± 7.88% vs. 102.64 ± 7.92%; p < 0.001). The proximal artery diameter exhibited a non-linear distribution across tertiles, with the middle tertile showing the smallest diameter (3.90 ± 0.79 mm compared to 4.24 ± 0.90 mm and 4.19 ± 0.74 mm in low and high tertiles, respectively; p = 0.002). Table 2 The results of univariate analysis Exposure Statistics ISS Mean ± SD/ N (%) OR ( 95% CI) P- value TT 17.28 ± 1.22 1.19 (0.98, 1.46) 0.0769 TT Tertile Low 127 (32.65%) 1 Middle 120 (30.85%) 1.84 (0.99, 3.41) 0.0544 High 142 (36.50%) 1.65 (0.90, 3.02) 0.1037 Sex No 276 (70.05%) 1 Yes 118 (29.95%) 0.70 (0.41, 1.20) 0.1957 Age 54.38 ± 11.37 0.98 (0.96, 1.00) 0.081 Age Tertile Low 127 (32.23%) 1 Middle 128 (32.49%) 0.55 (0.31, 0.98) 0.0409 High 139 (35.28%) 0.52 (0.29, 0.92) 0.024 Hypertension No 254 (64.47%) 1 Yes 140 (35.53%) 0.51 (0.30, 0.87) 0.0133 Diabetes No 348 (88.32%) 1 Yes 46 (11.68%) 1.07 (0.52, 2.20) 0.854 Hyperlipidemia Yes 274 (69.54%) 1 No 120 (30.46%) 0.97 (0.58, 1.62) 0.9146 Smoke No 346 (87.82%) 1 Yes 48 (12.18%) 1.00 (0.49, 2.06) 0.9896 Anterior Circulation No 22 (5.58%) 1 Yes 372 (94.42%) 3.10 (0.71, 13.51 0.1323 Morphology Saccular 366 (92.89%) 1 Fusiform 15 (3.81%) 0.80 (0.22, 2.91) 0.7366 Dissecting 13 (3.30%) 0.00 (0.00, Inf) 0.9815 Flow Diverter Tubridge Flow Diverter 206 (52.28%) 1 Pipeline Embolization Device 188 (47.72%) 0.56 (0.34, 0.90) 0.0177 Platelet Count 248.39 ± 61.65 1.00 (1.00, 1.01) 0.3394 Platelet Count Tertile Low 128 (32.82%) 1 Middle 132 (33.85%) 1.43 (0.80, 2.57) 0.232 High 130 (33.33%) 1.18 (0.65, 2.16) 0.5838 Prothrombin Time 11.43 ± 0.95 1.08 (0.84, 1.39) 0.5325 Prothrombin Time Tertile Low 128 (32.90%) 1 Middle 121 (31.11%) 0.59 (0.32, 1.11) 0.1022 High 140 (35.99%) 1.04 (0.60, 1.80) 0.8932 Fibrinogen 2.85 ± 0.70 0.76 (0.53, 1.10) 0.1504 Fibrinogen Tertile Low 128 (32.90%) 1 Middle 131 (33.68%) 0.59 (0.33, 1.04) 0.0679 High 130 (33.42%) 0.54 (0.30, 0.96) 0.0362 D-Dimer 0.55 ± 1.73 1.06 (0.95, 1.20) 0.2973 D-Dimer Tertile Low 123 (31.22%) 1 Middle 137 (34.77%) 1.60 (0.87, 2.95) 0.1287 High 134 (34.01%) 1.72 (0.94, 3.15) 0.0811 Aneurysm Diameter 6.36 ± 5.29 0.92 (0.86, 0.98) 0.011 Aneurysm Diameter Tertile Low 127 (32.23%) 1 Middle 135 (34.26%) 0.99 (0.58, 1.72) 0.9847 High 132 (33.50%) 0.49 (0.26, 0.91) 0.0228 Aneurysm Neck 5.14 ± 3.18 0.87 (0.79, 0.96) 0.0076 Aneurysm Neck Tertile Low 127 (32.23%) 1 Middle 135 (34.26%) 0.76 (0.44, 1.31) 0.3195 High 132 (33.50%) 0.39 (0.21, 0.73) 0.0031 Proximal Artery Diameter 4.12 ± 0.83 0.68 (0.51, 0.90) 0.0081 Proximal Artery Diameter Tertile Low 131 (33.25%) 1 Middle 131 (33.25%) 0.70 (0.40, 1.22) 0.2036 High 132 (33.50%) 0.52 (0.29, 0.93) 0.0274 Prothrombin Time Activity 105.34 ± 7.96 0.98 (0.95, 1.01) 0.1436 Prothrombin Time Activity Tertile Low 129 (32.74%) 1 Middle 132 (33.50%) 1.10 (0.63, 1.92) 0.7471 High 133 (33.76%) 0.73 (0.40, 1.32) 0.3025 Alanine Aminotransferase 18.64 ± 10.61 0.98 (0.96, 1.01) 0.2156 Alanine Aminotransferase Tertile Low 125 (32.55%) 1 Middle 130 (33.85%) 0.57 (0.32, 1.02) 0.0569 High 129 (33.59%) 0.50 (0.28, 0.90) 0.0202 Red Blood Cell Count 4.40 ± 0.51 0.62 (0.38, 1.02) 0.0574 Red Blood Cell Count Tertile Low 130 (33.33%) 1 Middle 129 (33.08%) 0.79 (0.45, 1.39) 0.4131 High 131 (33.59%) 0.53 (0.29, 0.96) 0.0357 Multivariate Analysis Results The results of multivariable analysis are shown in Table 3 . Multivariate regression analysis revealed a significant independent association between TT and incomplete stent stenosis in patients treated with FD for intracranial aneurysms. After adjustment for confounding factors, TT demonstrated a significant independent association with ISS. Each unit increase in TT was associated with approximately 36–40% higher odds of ISS development (Adjustment model I: OR = 1.40, 95% CI: 1.08–1.80, p = 0.010; Adjustment model II: OR = 1.36, 95% CI: 1.05–1.76, p = 0.021). When analyzed by tertiles, patients in the middle TT tertile exhibited the highest risk, with more than twice the odds of developing ISS compared to the lowest tertile (Adjustment model II: OR = 2.22, 95% CI: 1.04–4.76, p = 0.040). Table 3 The results of multivariable analysis Non-adjusted Adjust I Adjust II OR, 95% CI, P OR, 95% CI, P OR, 95% CI, P TT 1.19 (0.98, 1.46) 0.077 1.40 (1.08, 1.80) 0.010 1.36 (1.05, 1.76) 0.021 TT Tertile Low 1.0 1.0 1.0 Middle 1.84 (0.99, 3.41) 0.054 2.13 (1.01, 4.49) 0.046 2.22 (1.04, 4.76) 0.040 High 1.65 (0.90, 3.02) 0.104 2.05 (0.98, 4.26) 0.056 1.90 (0.89, 4.05) 0.097 Outcome: ISS Exposure Variables: TT; TT Tertile Adjust I adjust for: Sex; Age; Hypertension; Diabetes; Hyperlipidemia; Smoke; Anterior Circulation; Morphology (Saccular, Fusiform, Dissecting); Flow Diverter (Tubridge Flow Diverter, Pipeline Embolization Device); Platelet Count; Prothrombin Time; Fibrinogen; D-Dimer; Aneurysm Diameter; Aneurysm Neck; Proximal Artery Diameter; Prothrombin Time Activity; Alanine Aminotransferase; Red Blood Cell Count Adjust II adjust for: Sex; Age (smooth); Hypertension; Diabetes; Hyperlipidemia; Smoke; Anterior Circulation; Morphology (Saccular, Fusiform, Dissecting); Flow Diverter (Tubridge Flow Diverter, Pipeline Embolization Device); Platelet Count (smooth); Prothrombin Time (smooth); Fibrinogen (smooth); D-Dimer (smooth); Aneurysm Diameter (smooth); Aneurysm Neck (smooth); Proximal Artery Diameter (smooth); Prothrombin Time Activity (smooth); Alanine Aminotransferase (smooth); Red Blood Cell Count (smooth) Smooth Curve Fitting Analysis Smooth curve fitting analysis are shown in Fig. 1 . The smooth curve fitting analysis revealed a distinctive non-linear relationship between TT and the risk of ISS following FD placement for intracranial aneurysms. The relationship demonstrated a clear threshold effect with an inflection point at 19.2 seconds of TT. Below this threshold, TT exhibited a significant positive association with ISS risk (OR = 1.59, 95% CI: 1.19–2.13, p = 0.002), with each unit increase in TT corresponding to 59% higher odds of developing ISS. The predicted probability of ISS increased steadily from approximately 5% at 14 seconds to a peak of approximately 30% at 19.2 seconds. Beyond this inflection point, the relationship reversed direction (OR = 0.26, 95% CI: 0.02–2.88, p = 0.270), with ISS risk declining as TT increased further, though this inverse association did not reach statistical significance. The widening confidence intervals at extreme TT values reflect increased uncertainty in risk estimation for these ranges. The results of the two-piecewise linear regression model Threshold effect analysis of ISS using two-piecewise linear regression model are shown in Table 4 . To investigate potential non-linear associations between TT and ISS, we conducted a threshold effect analysis using a two-piecewise linear regression model. Segmented regression analysis confirmed a threshold effect at TT = 19.2 seconds. For values below this threshold, each unit increase in TT was associated with a 59% higher risk of ISS (OR = 1.59, 95% CI: 1.19–2.13, p = 0.002). Above this threshold, the relationship reversed direction (OR = 0.26, 95% CI: 0.02–2.88, p = 0.270), albeit without statistical significance. The likelihood ratio test (p = 0.048) validated that the segmented model provided superior fit compared to the conventional linear model. Patients with TT approaching but not exceeding 19.2 seconds may represent a particularly high-risk subgroup requiring enhanced monitoring or adjunctive therapeutic interventions. Table 4 Threshold Effect Analysis of ISS Using Two-Piecewise Linear Regression Model Model and Segments OR 95% CI P-value Model I Linear regression 1.40 1.08, 1.80 0.010 Model II Inflection point < 19.2 1.59 1.19, 2.13 0.002 ≥19.2 0.26 0.02, 2.88 0.270 likelihood ratio test 0.048 This table presents a two-model analysis showing both linear and non-linear (threshold) effects on ISS outcome. Model II indicates a significant change in effect pattern at the threshold point of 19.2(S). Adjust: Sex; Age; Hypertension; Diabetes; Hyperlipidemia; Smoke; Anterior Circulation; Morphology; Flow Diverter; Platelet Count; Prothrombin Time; Fibrinogen; D-Dimer; Aneurysm Diameter; Aneurysm Neck; Proximal Artery Diameter; Prothrombin Time Activity; Alanine Aminotransferase; Red Blood Cell Count DISCUSSION In this multicenter retrospective cohort study of 394 patients with unruptured intracranial aneurysms treated with FD, we identified a significant non-linear relationship between TT and ISS risk, characterized by a distinct threshold effect at 19.2 seconds. Below this threshold, each unit increase in TT was associated with 59% higher odds of developing ISS (OR = 1.59, 95% CI: 1.19–2.13, p = 0.002), while above this threshold, the relationship appeared to reverse direction, though this trend did not reach statistical significance (OR = 0.26, 95% CI: 0.02–2.88, p = 0.270). These findings establish TT as a novel biomarker for risk stratification in patients undergoing FD treatment for intracranial aneurysms. Studies indicate that ISS undergoes dynamic changes during postoperative follow-up. Typically, ISS is most easily detected within the first six months after implantation of a shunt (FD), and then the possibility of partial improvement is observed at 12 months or later. Gui et al.[ 14 ] reported in their single-center study that prolonged dual antiplatelet therapy correlates with increased rates of ISS regression, suggesting that ISS may represent a common self-limiting complication. Additionally, Cohen's retrospective analysis[ 16 ] demonstrated stenosis reduction with intensified clopidogrel therapy (150 mg/day), revealing cases that improved from moderate to mild stenosis during follow-up imaging. However, complete resolution of ISS is uncommon[ 14 ], indicating that it is a structural manifestation of the endothelial response to FD implantation rather than merely a transient or incidental finding. This study focuses on evaluating the predictive value of preoperative TT levels for the occurrence of ISS, rather than assessing its severity or temporal changes. Regardless of whether ISS is symptomatic, its presence could elevate the risk of long-term ischemic events. Our findings demonstrate a nonlinear relationship between TT levels and the risk of ISS, identifying a predictive threshold of 19.2 seconds, which underscores its potential clinical utility in risk stratification and management of ISS. Our investigation into the non-linear relationship between TT and ISS reveals both congruencies and divergences with existing literature. Several studies have demonstrated that prolonged TT correlates with reduced stenosis risk. Yu et al researched bioabsorbable Heparin-Silk Fibroin (Hep-SF) stent coverings and documented significant TT prolongation[ 17 ], concluding that this anticoagulant effect may diminish thrombus formation at stenotic sites. Similarly, Huang et al. investigated Chitosan-Heparin (ChS-HEP) multilayer film-modified stents[ 18 ], demonstrating enhanced hemocompatibility with prolonged TT, suggesting these modifications prevent vascular stenosis through altered coagulation dynamics. In another study, Jia et al. compared bivalirudin versus heparin in percutaneous coronary intervention (PCI) and concluded that bivalirudin might mitigate post-PCI stenosis and thrombosis by stabilizing coagulation parameters, including TT[ 12 ]. Conversely, Yu et al. examined microplastics in extracranial artery stenosis (ECAS) patients and observed elevated TT alongside increased microplastic concentrations[ 11 ], hypothesizing that microplastics might exacerbate arterial stenosis through coagulation dysfunction, though direct TT-stenosis correlations were not analyzed. While these studies collectively support the association between coagulation parameters and stent-related complications, they predominantly presupposed linear relationships. Our research uniquely identified a threshold effect at 19.2 seconds, with TT and ISS risk showing significantly positive correlation below this threshold but reversing trend above it—likely reflecting distinct pathophysiological mechanisms operating under various coagulation states. This novel finding provides a critical theoretical foundation for optimizing individualized anticoagulation strategies in clinical practice, suggesting that TT management should target specific ranges rather than simply maximizing anticoagulation effects. The non-linear relationship between TT and ISS likely reflects the complex mechanisms of coagulation system involvement in stent-related vascular pathology. Thrombin, as a key enzyme in the coagulation cascade[ 19 ], influences not only thrombus formation but also participates in vascular wall repair and remodeling through multiple pathways[ 20 ]. Goel et al discovered that thrombin promotes smooth muscle cell (SMC) proliferation and migration to injury sites through activation of PI3K/Akt and Ras pathways, contributing to neointimal formation[ 21 ]. However, Shen et al. demonstrated that Direct Thrombin Inhibitors (DTIs) such as dabigatran target thrombin's active site, thereby reducing thrombotic risk[ 22 ]. Furthermore, Catar et al. showed that thrombin, through ERK/AP-1 signal cascades, binds to the Vascular Endothelial Growth Factor (VEGF) promoter (region − 267 to -53), promoting VEGF mRNA synthesis and protein secretion, thus driving endothelial proliferation and angiogenesis[ 20 ]. We observed that patients in the low TT group typically presented with higher proportions of smoking history, hypertension, and diabetes—factors known to exacerbate endothelial dysfunction and inflammatory responses—which, acting synergistically with enhanced thrombin activity, may accelerate the progression of in-stent stenosis; interestingly, when TT values exceeded the 19.2-second threshold, ISS risk decreased rather than increased, possibly related to impaired endothelial repair function due to reduced thrombin activity, as moderate thrombin activity is necessary for maintaining and repairing vascular endothelial integrity[ 23 ]. Based on these mechanisms, for patients with low TT, intensified antiplatelet therapy with consideration of short-term anticoagulation may be more rational, whereas for high TT patients, potent anticoagulants should be used cautiously to avoid delayed vascular endothelial repair. Li et al.'s research on heparin-coated stents offers a strategy for local regulation of thrombin activity, with controlled release of heparin from the coating potentially reducing thrombotic risk while maintaining adequate endothelial repair capacity[ 24 ]. Future research should explore the applicability of TT thresholds across different populations, conduct prospective studies to validate the impact of TT-based individualized anticoagulation strategies on ISS incidence, and investigate novel biomarker combinations to improve predictive accuracy. Our findings demonstrate significant clinical translational value. First, the identified non-linear relationship between TT and ISS risk, with a threshold of 19.2 seconds, provides a reference standard for risk stratification following FD treatment of intracranial aneurysms. For high-risk patients with TT below 19.2 seconds, anticoagulation therapy may be considered when necessary, or antiplatelet therapy duration could be extended; conversely, for patients with TT above this threshold, alternative therapeutic strategies may be warranted to mitigate complications related to stenosis or hemorrhage. Second, our research offers novel insights for stent design, suggesting the potential development of drug-eluting stents specifically engineered to modulate thrombin activity. Finally, given the complexity of the coagulation system, future investigations should explore the value of combining TT with other coagulation parameters in predictive models for ISS, validate the applicability of the TT threshold across diverse populations, and evaluate the clinical outcomes of TT-adjusted anticoagulation strategies. Based on our findings, we have proposed actionable clinical recommendations that provide an evidence-based foundation for developing individualized anticoagulation protocols in this patient population. LIMITATIONS Several limitations of this study warrant careful consideration. First, our retrospective cohort design restricts the sample size and may introduce potential bias due to uneven distributions among patient groups. A prospective trial involving a larger number of random samples and long-term follow-up is necessary to validate our conclusions. Second, since all participants were drawn from four medical centers in southern China, caution should be exercised when generalizing these findings to other ethnic groups or regions. Third, as an observational study, we could only establish associations between TT and ISS rather than causal relationships. Fourth, while we controlled for multiple known confounders through multivariate analysis, unmeasured confounding factors may still affect the results. Additionally, our inclusion criteria excluded certain special populations, such as patients with coagulation disorders and severe hepatic or renal dysfunction, meaning our findings may not be applicable to these specific groups. Finally, given the relatively short follow-up period, longer-term follow-up studies are needed to assess the sustained impact of TT on ISS. CONCLUSIONS This multicenter retrospective cohort study pioneered the revelation of TT's critical threshold effect in assessing ISS risk following FD treatment for intracranial aneurysms, identifying 19.2 seconds as a pivotal inflection point where TT level serves as a reliable parameter for ISS risk evaluation. For TT values below this threshold, each unit increase was associated with 59% higher likelihood of developing ISS at follow-up. These results may help identify patients at higher risk for ISS who might benefit from more intensive. Declarations Funding Statement This work was supported by the National Natural Science Foundation of China (grant 81974177), the Zhongshan Science and Technology Bureau (grant 2020B1130) and Guangdong Second Provincial Genera Hospital (grant WKZX2023CZ0214, grant TJGC-2023012). Conflicts of interest/Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Ethics approval and consent to participate This study protocol received approval from the Ethics Committees of Zhujiang Hospital of Southern Medical University (approval number: 2024-KY-211), Zhongshan Hospital of Traditional Chinese Medicine (approval number: 2024ZSZY-LL-KY-315), The First Affiliated Hospital of Zhengzhou University (approval number: 2022-KY-0861), and the Eighth Affiliated Hospital of Sun Yat-sen University (approval number: 2024r298). Given the retrospective nature of the analysis and the anonymization of all patient data without additional interventions or follow-up procedures, the requirement for informed consent was waived in accordance with the principles of the Declaration of Helsinki. The research team strictly adhered to the Chinese ethical review regulations for human biomedical research and international ethical guidelines to ensure patient privacy and data security. All study data were stored on password-protected secure servers with access restricted to authorized research personnel only. This study received no commercial funding that might constitute a potential conflict of interest. Availability of data and material In this study, the data of the study population were sourced from the Hospital Information System. Therefore, to protect patient privacy, the datasets are not publicly available. However, the data can be accessed upon reasonable request through the corresponding author. Consent for publication Due to the study's retrospective design and the anonymization of patient data, informed consent was waived by the Ethics Committee. Authors' contributions Zhikun Jia, Jiayin Ma, Qile He, Jialin Gao, Yuqi Xie, Zhichao Wu, Mengshi Huang, Zhixi Li, Xin Jin: Investigation, Data curation, Formal analysis, Visualization, Writing – original draft. Zhikun Jia: Conceptualization, Methodology, Software. Zhikun Jia, Jiahe Yin, Shenquan Guo, Wenchao Liu, Shixing Su, Fa Jin: Writing – review & editing. Xuetao Wang, Xuying He and Xin Zhang: Funding acquisition. Chuanzhi Duan, Xuying He and Xin Zhang: Conceptualization, Validation, Project administration, Supervision, Writing – review & editing. All authors read and approved the final manuscript. Xin Zhang and Xuying He are co-corresponding authors. Acknowledgement We would like to thank Professor Chi Chen for his valuable contributions to the professional statistical analysis of the study data. We gratefully acknowledge the funding support from Xuetao Wang. We would like to thank Xuetao Wang, Tao Quan, and Bin Luo for their valuable contributions to data collection and analysis in this study. Human Ethics and Consent to Participate declarations Not applicable. References Brown RD Jr., Broderick JP (2014) Unruptured intracranial aneurysms: epidemiology, natural history, management options, and familial screening. Lancet Neurol 13(4):393–404. https://doi.org/10.1016/s1474-4422(14)70015-8 Tawk RG, Hasan TF, D’Souza CE, Peel JB, Freeman WD (2021) Diagnosis and treatment of unruptured intracranial aneurysms and aneurysmal subarachnoid hemorrhage. Mayo Clinic Proceedings. ;96(7):1970–2000. https://doi.org/10.1016/j.mayocp.2021.01.005 Ou C, Chong W, Duan CZ, Zhang X, Morgan M, Qian Y (2021) A preliminary investigation of radiomics differences between ruptured and unruptured intracranial aneurysms. Eur Radiol 31(5):2716–2725. https://doi.org/10.1007/s00330-020-07325-3 Zhang M, Hou X, Qian Y, Chong W, Zhang X, Duan CZ et al (2023) Evaluation of aneurysm rupture risk based upon flowrate-independent hemodynamic parameters: a multi-center pilot study. J Neurointerv Surg 15(7):695–700. https://doi.org/10.1136/neurintsurg-2022-018691 Dandapat S, Mendez-Ruiz A, Martínez-Galdámez M, Macho J, Derakhshani S, Foa Torres G et al (2021) Review of current intracranial aneurysm flow diversion technology and clinical use. J Neurointerv Surg 13(1):54–62. https://doi.org/10.1136/neurintsurg-2020-015877 Lauzier DC, Cler SJ, Osbun JW, Chatterjee AR, Moran CJ, Kansagra AP (2022) Management of in-stent stenosis with dual antiplatelet therapy following pipeline embolization of intracranial aneurysms. World Neurosurg 167:e303–e9. https://doi.org/10.1016/j.wneu.2022.08.002 You W, Lv J, Li Z, Chen X, Deng D, Tang Y et al (2023) The incidence and predictors of in-stent stenosis after pipeline flow-diverter stenting for intracranial aneurysm treatment. Front Neurol 14:1140497. https://doi.org/10.3389/fneur.2023.1140497 Tripodi A, Mannucci PM (2001) Laboratory Investigation of Thrombophilia. Clin Chem 47(9):1597–. https://doi.org/10.1093/clinchem/47.9.1597 . 606 Xu T, Ji H, Xu L, Cheng S, Liu X, Li Y et al (2023) Self-anticoagulant sponge for whole blood auto-transfusion and its mechanism of coagulation factor inactivation. Nat Commun 14(1):4875. https://doi.org/10.1038/s41467-023-40646-7 Matsuno H, Kozawa O, Niwa M, Abe A, Takiguchi Y, Uematsu T (2001) Characterization of simple and reproducible vascular stenosis model in hypercholesterolemic hamsters. Lipids 36(5):453–460. https://doi.org/10.1007/s11745-001-0742-4 Yu H, Li H, Cui C, Han Y, Xiao Y, Zhang B et al (2024) Association between blood microplastic levels and severity of extracranial artery stenosis. J Hazard Mater 480:136211. https://doi.org/10.1016/j.jhazmat.2024.136211 Dequan J, Xiaomei W, Bo Q, Jie H (2023) The effect of bivalirudin on coagulation function in male patients with coronary heart disease undergoing percutaneous coronary intervention. Pak J Pharm Sci 36(4):1089–1092 Hietala EM, Maasilta P, Välimaa T, Harjula AL, Törmälä P, Salminen US et al (2003) Platelet responses and coagulation activation on polylactide and heparin-polycaprolactone-L-lactide-coated polylactide stent struts. J Biomed Mater Res A 67(3):785–791. https://doi.org/10.1002/jbm.a.10154 Gui S, Chen X, Wei D, Deng D, You W, Meng X et al (2023) Long-term outcomes and dynamic changes of in-stent stenosis after Pipeline embolization device treatment of intracranial aneurysms. J Neurointerv Surg 15(12):1187–1193. https://doi.org/10.1136/jnis-2022-019680 Wang T, Richard SA, Jiao H, Li J, Lin S, Zhang C et al (2021) Institutional experience of in-stent stenosis after pipeline flow diverter implantation: A retrospective analysis of 6 isolated cases out of 118 patients. Med (Baltim) 100(11):e25149. https://doi.org/10.1097/md.0000000000025149 Cohen JE, Gomori JM, Moscovici S, Leker RR, Itshayek E (2014) Delayed complications after flow-diverter stenting: Reactive in-stent stenosis and creeping stents. J Clin Neurosci 21(7):1116–1122. https://doi.org/10.1016/j.jocn.2013.11.010 Yu Y, Dai M, Li M, Song G, Yin Y, Wang J (2025) Bioabsorbable Stent-Covering with Sustained Anticoagulant Activity Fabricated via Alternate Layer-by-Layer Self-Assembly of Heparin and Silk Fibroin. ACS Appl Mater Interfaces. https://doi.org/10.1021/acsami.4c16643 Huang LY, Yang MC, Tsou HM, Liu TY (2019) Hemocompatibility and anti-fouling behavior of multilayer biopolymers immobilized on gold-thiolized drug-eluting cardiovascular stents. Colloids Surf B Biointerfaces 173:470–477. https://doi.org/10.1016/j.colsurfb.2018.10.014 Nicoud F (2023) An adjoint-based method for the computation of gradients in coagulation schemes. Int J Numer Method Biomed Eng 39(5):e3698. https://doi.org/10.1002/cnm.3698 Catar R, Moll G, Hosp I, Simon M, Luecht C, Zhao H et al (2021) Transcriptional Regulation of Thrombin-Induced Endothelial VEGF Induction and Proangiogenic Response. Cells 10(4). https://doi.org/10.3390/cells10040910 Goel R, Phillips-Mason PJ, Gardner A, Raben DM, Baldassare JJ (2004) Alpha-thrombin-mediated phosphatidylinositol 3-kinase activation through release of Gbetagamma dimers from Galphaq and Galphai2. J Biol Chem 279(8):6701–6710. https://doi.org/10.1074/jbc.M308753200 Shen JI, Winkelmayer WC (2012) Use and safety of unfractionated heparin for anticoagulation during maintenance hemodialysis. Am J Kidney Dis 60(3):473–486. https://doi.org/10.1053/j.ajkd.2012.03.017 Bergmeier W, Hynes RO (2012) Extracellular matrix proteins in hemostasis and thrombosis. Cold Spring Harb Perspect Biol 4(2). https://doi.org/10.1101/cshperspect.a005132 Li M, Wu H, Wang Y, Yin T, Gregersen H, Zhang X et al (2017) Immobilization of heparin/poly-l-lysine microspheres on medical grade high nitrogen nickel-free austenitic stainless steel surface to improve the biocompatibility and suppress thrombosis. Mater Sci Eng C Mater Biol Appl 73:198–205. https://doi.org/10.1016/j.msec.2016.12.070 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 24 Oct, 2025 Read the published version in Neurosurgical Review → Version 1 posted Editorial decision: Revision requested 18 Jul, 2025 Reviews received at journal 09 Jul, 2025 Reviewers agreed at journal 25 Jun, 2025 Reviews received at journal 04 Jun, 2025 Reviewers agreed at journal 03 Jun, 2025 Reviewers invited by journal 19 May, 2025 Editor assigned by journal 09 May, 2025 Submission checks completed at journal 09 Apr, 2025 First submitted to journal 05 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6384391","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":458784117,"identity":"da93fe33-466f-4883-8001-89e5e05c131a","order_by":0,"name":"Zhikun Jia","email":"","orcid":"","institution":"Zhujiang Hospital of Southern Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhikun","middleName":"","lastName":"Jia","suffix":""},{"id":458784118,"identity":"c3b3f7c9-d50a-4e2e-b187-08cbae8448a8","order_by":1,"name":"Jiayin Ma","email":"","orcid":"","institution":"Zhujiang Hospital of Southern Medical 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Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDElEQVRIiWNgGAWjYDACCSjJxt58+EFChYQcPzPz4QdEaeHjOZZm8OGMhbFkO1uaARFaGBjkJHIMJGe2VSRuOM+jIIFPh/zs5mcPv7ZZ5LFJpCUY85yRMDY+zMNgwFBjE41LC+OcY+bGMmckitl4Hh94zAP0i9lh3gMPGI6l5Tbg0MIskWAmLVEhkdjGDrXF7DBfggFjw2GcWtgk0r9JSxgAtTDkGEjztkkkbm7mMZDAp4VHIsdM8gPIFg6w9yUSNzAT0CIhkVMmzXAGqAUSyBLGEoeBgZyAxy/yM9K3Sf5sq0uc3w6Oyjo5/v7Dhx98qLHBqQUcBDwYQgl4lIMA4w8CCkbBKBgFo2CEAwBmQVe9G5vGYAAAAABJRU5ErkJggg==","orcid":"","institution":"Zhujiang Hospital of Southern Medical University","correspondingAuthor":true,"prefix":"","firstName":"Xin","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-04-06 02:38:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6384391/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6384391/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10143-025-03899-y","type":"published","date":"2025-10-24T16:16:09+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":83282414,"identity":"a06edea8-be47-4df5-b2cf-004834f8e190","added_by":"auto","created_at":"2025-05-22 10:36:24","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":98845,"visible":true,"origin":"","legend":"\u003cp\u003eNon-linear threshold effect of TT on ISS risk.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6384391/v1/13c0e086d1116089e43302ae.jpeg"},{"id":94490491,"identity":"33dfa348-8fd3-4f03-81f7-0c7b8dab8b14","added_by":"auto","created_at":"2025-10-27 17:11:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1296756,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6384391/v1/5fec066c-5865-433d-9c71-fea686aec710.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Role of Thrombin Time as an Independent Variable in Predicting In-Stent Stenosis Risk After Flow Diverter Treatment for Intracranial Aneurysms: A Retrospective Cohort Study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eIntracranial aneurysms represent a significant neurological issue, with global prevalence rates ranging from 3\u0026ndash;5%, and notable geographic variation, as indicated by the higher 7% rate found in Chinese populations[\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Flow diverter (FD) interventions, while demonstrating validated safety and therapeutic success in the treatment of intracranial aneurysms[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], remain associated with the substantial post-procedural complication of in-stent stenosis (ISS)[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In a study involving 240 patients with intracranial aneurysms who underwent 252 FD implantation procedures, ISS was identified in 135 (53.6%) lesions, with severity categorized as mild in 66 (48.9%), moderate in 52 (38.5%), and severe in 17 (12.6%) cases[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This complication not only jeopardizes long-term treatment efficacy but also elevates the risk of thromboembolic events and requires extended anti-platelet therapy.\u003c/p\u003e \u003cp\u003eThrombin time (TT) is a coagulation assay measuring the conversion of fibrinogen to fibrin in the common pathway of blood coagulation, specifically reflecting the final stage of clot formation[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Prolonged TT values indicate decreased thrombin activity or fibrinogen dysfunction, while shortened values suggest hypercoagulability states[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Recent studies have demonstrated significant associations between TT and the incidence of adverse outcomes of various pathologies. In hypercholesterolemic hamster models of vascular stenosis[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], researchers identified mechanisms whereby elevated low-density lipoprotein (LDL) levels promote thrombosis and vascular narrowing through alterations in coagulation parameters, specifically TT. A separate investigation examining microplastic effects on stenosis revealed significantly prolonged TT in the ECAS cohort compared to control subjects[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. These established correlations underscore the clinical significance of monitoring and managing TT parameters in medical practice.\u003c/p\u003e \u003cp\u003eAvailable evidence suggests that alterations in TT may serve as predictive indicators for ISS risk. In a comparative investigation of bivalirudin versus heparin in percutaneous coronary intervention[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], findings indicated that bivalirudin potentially reduces post-procedural vascular stenosis and thrombotic events by stabilizing coagulation parameters, including TT. When examining various stent materials' influence on platelet reactivity and coagulation activation[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], researchers determined through TT assessment that heparin-coated stents mitigate post-implantation thrombosis and vascular stenosis risks via modulation of coagulation profiles. Nevertheless, the literature currently lacks reports evaluating TT as a prognostic marker for ISS following flow diversion device treatment of intracranial aneurysms.\u003c/p\u003e \u003cp\u003eIn our clinical practice, we observed reduced TT levels in certain patients with ISS; however, whether this reduction constitutes an independent risk factor for ISS or merely reflects concurrent phenomena remains unclear. To address this question, we conducted a multicenter retrospective cohort study evaluating the association between TT and ISS among patients with intracranial aneurysms treated with flow diversion devices between March 2016 and October 2024. Additionally, we explored the potential threshold effects of TT in predicting ISS risk, aiming to provide scientific evidence for developing individualized anticoagulation protocols that could improve patient outcomes. Our study design incorporated an extended outcome assessment period of 6 to 24 months to enhance the reliability and clinical applicability of our findings.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Population\u003c/h2\u003e \u003cp\u003eThis multicenter retrospective cohort study evaluated patients with intracranial aneurysms treated with FD devices between March 2016 and October 2024. Patients were enrolled from multiple centers after approval from institutional ethics committees. Given the retrospective nature, informed consent was waived. The investigation focused on examining the association between preoperative TT and ISS, with particular emphasis on potential threshold effects to inform individualized anticoagulation protocols. Follow-up assessments were conducted over 6\u0026ndash;24 months to maximize clinical relevance.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eVariables\u003c/h3\u003e\n\u003cp\u003eThe primary exposure variable was TT, measured from venous blood samples collected within 24 hours of admission using a Sysmex CS-5100 automated coagulation analyzer (Sysmex Corporation, Japan) with Siemens Healthcare reagent kits. Blood was drawn in a fasting state using vacuum tubes containing 3.2% sodium citrate. TT was recorded as a continuous variable (seconds), with a normal reference range of 14\u0026ndash;21 seconds. We also categorized TT by tertiles to explore non-linear relationships.\u003c/p\u003e \u003cp\u003eThe primary outcome was ISS, defined as \u0026ge;\u0026thinsp;25% luminal narrowing at digital subtraction angiography (DSA) follow-up. DSA images were independently evaluated by two neurointerventional radiologists blinded to clinical data and exposure variables. Stenosis severity was stratified as mild (25\u0026ndash;50%), moderate (50\u0026ndash;75%), or severe (\u0026gt;\u0026thinsp;75%).\u003c/p\u003e \u003cp\u003eCovariates included: demographic characteristics (sex, age); vascular risk factors (hypertension, diabetes, hyperlipidemia, smoking); aneurysm characteristics (circulation location, morphology, diameter, neck width, proximal artery diameter); treatment-related factors (FD type); and laboratory parameters (platelet count, prothrombin time/activity, fibrinogen, D-dimer, liver function, red blood cell count). These covariates were selected based on existing literature and biological plausibility to control for potential confounding factors. Hypertension, diabetes, and hyperlipidemia were determined based on previous diagnoses or current medication use. Missing data, comprising less than 5% of the dataset, were handled using multiple imputation techniques, with sensitivity analyses employing complete case analysis to verify the robustness of our findings. All variable definitions and measurement methods were documented according to standardized operating procedures.\u003c/p\u003e\n\u003ch3\u003eEndovascular Procedures\u003c/h3\u003e\n\u003cp\u003eAll patients received dual antiplatelet therapy (DAPT) 5 days before FD treatment, comprising aspirin (100 mg once daily) plus either clopidogrel (75 mg once daily) or ticagrelor (45 mg twice daily). Platelet aggregation capacity was assessed one day before the procedure. Interventions were performed under intravenous anesthesia with systemic heparinization. 3D DSA was acquired using a Philips Integris V system (Philips Healthcare, Eindhoven, Netherlands). FD dimensions were tailored to individual parent vessel and aneurysm characteristics. Heparin reversal was not performed post-procedure. After discharge, patients continued DAPT for 6 months, followed by aspirin monotherapy for 6\u0026ndash;12 months. Follow-up DSA was performed at minimum 6 months post-intervention to evaluate ISS.\u003c/p\u003e\n\u003ch3\u003eDefinition of stenosis rate\u003c/h3\u003e\n\u003cp\u003eThe stenosis rate (SR) was calculated using the formula[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:SR=(1-\\frac{\\:No.n\\:follow\\:-\\:up\\:In\\:-\\:stent\\:artery\\:Diameter\\:\\left(\\:Dn\\:\\right)}{\\:operation\\:In\\:-\\:stent\\:artery\\:Diameter\\:\\left(\\:Do\\:\\right)})\\times\\:100\\%$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eDefinition of ISS and outcome assessment\u003c/h3\u003e\n\u003cp\u003eIntimal hyperplasia was defined as a uniform growth process beyond the limits of the metallic mesh at \u0026lt;\u0026thinsp;25%. ISS[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], characterized by parent vessel narrowing exceeding 25%, was further classified as mild (25%-50%), moderate (50%-75%), or severe (\u0026gt;\u0026thinsp;75%).\u003c/p\u003e \u003cp\u003eThe primary outcome, ISS, was assessed through DSA examinations performed at least 6 months after the procedure. ISS evaluation was conducted independently by two neurointerventional radiologists with over 10 years of experience using a double-blind method, with ISS positivity defined as stenosis\u0026thinsp;\u0026ge;\u0026thinsp;25%.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (normal distribution) or median (minimum, maximum) (skewed distribution). Categorical variables were expressed as frequencies/percentages. Between-group comparisons employed chi-square tests (categorical variables), Student's t-tests (normal distribution), or Mann-Whitney U tests (skewed distribution). The TT-ISS relationship was examined using a two-step approach: First, three progressive adjustment regression models (unadjusted, sociodemographic-adjusted, fully-adjusted) evaluated effect robustness; Second, Generalized Additive Models and smooth curve fitting explored non-linear relationships, with inflection points calculated and two-piecewise linear models constructed when non-linearity was detected. All analyses were performed using R software (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered statistically significant).\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eBaseline Characteristics Stratified by TT Tertiles\u003c/h2\u003e \u003cp\u003eBaseline characteristics of participants shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. ISS occurred in 22.84% (90/394) of patients. Patients in the highest TT tertile exhibited significantly lower fibrinogen levels (2.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64 g/L vs. 3.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78 g/L in the lowest tertile; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and shorter prothrombin time (11.30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03s vs. 11.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82s; p\u0026thinsp;=\u0026thinsp;0.002). Prothrombin time activity was significantly elevated in both middle and high tertiles compared to the low tertile (106.40\u0026thinsp;\u0026plusmn;\u0026thinsp;7.65% and 106.96\u0026thinsp;\u0026plusmn;\u0026thinsp;7.88% vs. 102.64\u0026thinsp;\u0026plusmn;\u0026thinsp;7.92%, respectively; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Proximal artery diameter demonstrated a non-linear distribution, with the middle tertile exhibiting the smallest diameter (3.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79mm compared to 4.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90mm and 4.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74mm in low and high tertiles, respectively; p\u0026thinsp;=\u0026thinsp;0.002). Notably, both hypertension prevalence (43.3\u0026ndash;28.9%; p\u0026thinsp;=\u0026thinsp;0.047) and smoking rates (19.7\u0026ndash;7.0%; p\u0026thinsp;=\u0026thinsp;0.006) decreased significantly with increasing TT tertiles.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe baseline characteristics of patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTT Tertile\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow(n\u0026thinsp;=\u0026thinsp;127)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMiddle(n\u0026thinsp;=\u0026thinsp;120)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh(n\u0026thinsp;=\u0026thinsp;142)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD/ N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55.68\u0026thinsp;\u0026plusmn;\u0026thinsp;11.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.86\u0026thinsp;\u0026plusmn;\u0026thinsp;12.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.48\u0026thinsp;\u0026plusmn;\u0026thinsp;10.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet Count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e245.24\u0026thinsp;\u0026plusmn;\u0026thinsp;61.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e255.95\u0026thinsp;\u0026plusmn;\u0026thinsp;65.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e245.05\u0026thinsp;\u0026plusmn;\u0026thinsp;59.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.286\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActivated Partial Thromboplastin Time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.24\u0026thinsp;\u0026plusmn;\u0026thinsp;4.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.65\u0026thinsp;\u0026plusmn;\u0026thinsp;4.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.95\u0026thinsp;\u0026plusmn;\u0026thinsp;4.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.413\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProthrombin Time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFibrinogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody Mass Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.80\u0026thinsp;\u0026plusmn;\u0026thinsp;3.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.67\u0026thinsp;\u0026plusmn;\u0026thinsp;4.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.65\u0026thinsp;\u0026plusmn;\u0026thinsp;3.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.951\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-Dimer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.60\u0026thinsp;\u0026plusmn;\u0026thinsp;2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.650\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAneurysm Diameter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.98\u0026thinsp;\u0026plusmn;\u0026thinsp;5.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.19\u0026thinsp;\u0026plusmn;\u0026thinsp;4.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.90\u0026thinsp;\u0026plusmn;\u0026thinsp;6.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.322\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAneurysm Neck\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.08\u0026thinsp;\u0026plusmn;\u0026thinsp;2.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.28\u0026thinsp;\u0026plusmn;\u0026thinsp;2.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.09\u0026thinsp;\u0026plusmn;\u0026thinsp;3.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.861\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematocrit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.453\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistal Artery Diameter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.312\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProximal Artery Diameter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProthrombin Time Activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102.64\u0026thinsp;\u0026plusmn;\u0026thinsp;7.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106.96\u0026thinsp;\u0026plusmn;\u0026thinsp;7.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e106.40\u0026thinsp;\u0026plusmn;\u0026thinsp;7.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRed Blood Cell Count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e127.39\u0026thinsp;\u0026plusmn;\u0026thinsp;15.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e126.71\u0026thinsp;\u0026plusmn;\u0026thinsp;13.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e129.34\u0026thinsp;\u0026plusmn;\u0026thinsp;14.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.306\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlanine Aminotransferase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.21\u0026thinsp;\u0026plusmn;\u0026thinsp;13.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.55\u0026thinsp;\u0026plusmn;\u0026thinsp;6.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.99\u0026thinsp;\u0026plusmn;\u0026thinsp;10.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.029*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.148\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 (66.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92 (76.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96 (67.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (33.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (23.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46 (32.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.047*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 (56.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78 (65.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e101 (71.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (43.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (35.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41 (28.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.677\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113 (89.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108 (90.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e123 (86.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (11.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (10.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (13.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperlipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.126\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97 (76.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81 (67.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93 (65.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (23.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (32.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49 (34.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.006*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102 (80.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107 (89.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e132 (93.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (19.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (10.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (7.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnterior Circulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.404\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117 (92.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e115 (95.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e135 (95.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMorphology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSaccular\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117 (92.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e111 (92.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e133 (93.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFusiform\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (5.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDissecting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (5.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverlapping Stents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.355\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124 (97.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e113 (94.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e137 (96.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (5.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlow Diverter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.289\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTubridge Flow Diverter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (46.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 (55.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78 (54.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePipeline Embolization Device\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68 (53.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (45.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64 (45.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eISS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.126\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e106 (83.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88 (73.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e107 (75.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (16.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (26.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35 (24.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eStatistical results are reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or number (%).\u003c/p\u003e \u003cp\u003e*Statistical significance\u003c/p\u003e \u003cp\u003eContinuous variable was obtained by Kruskal-Wallis rank sum test. If the count variable had a theoretical number\u0026thinsp;\u0026lt;\u0026thinsp;10, the probability was calculated accurately using Fisher's exact test\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eUnivariate Analysis Results\u003c/h2\u003e \u003cp\u003eThe results of univariate analysis are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In our cohort of intracranial aneurysm patients, stratification by TT tertiles revealed several significant hemostatic and clinical differences. Patients in the high TT tertile demonstrated significantly lower fibrinogen levels (2.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64 g/L vs. 3.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78 g/L in the low tertile; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and shorter prothrombin time (11.30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03 s vs. 11.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82 s; p\u0026thinsp;=\u0026thinsp;0.002). Correspondingly, prothrombin time activity was elevated in both middle and high tertiles compared to the low tertile (106.40\u0026thinsp;\u0026plusmn;\u0026thinsp;7.65% and 106.96\u0026thinsp;\u0026plusmn;\u0026thinsp;7.88% vs. 102.64\u0026thinsp;\u0026plusmn;\u0026thinsp;7.92%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The proximal artery diameter exhibited a non-linear distribution across tertiles, with the middle tertile showing the smallest diameter (3.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79 mm compared to 4.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90 mm and 4.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74 mm in low and high tertiles, respectively; p\u0026thinsp;=\u0026thinsp;0.002).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e The results of univariate analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExposure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eISS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD/ N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR ( 95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP- value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.19 (0.98, 1.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0769\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTT Tertile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e127 (32.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120 (30.85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.84 (0.99, 3.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0544\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142 (36.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.65 (0.90, 3.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e276 (70.05%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118 (29.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.70 (0.41, 1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1957\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.38\u0026thinsp;\u0026plusmn;\u0026thinsp;11.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98 (0.96, 1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge Tertile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e127 (32.23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e128 (32.49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.55 (0.31, 0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0409\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e139 (35.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.52 (0.29, 0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e254 (64.47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140 (35.53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.51 (0.30, 0.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0133\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e348 (88.32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (11.68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.07 (0.52, 2.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.854\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperlipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e274 (69.54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120 (30.46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97 (0.58, 1.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e346 (87.82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (12.18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00 (0.49, 2.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9896\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnterior Circulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (5.58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e372 (94.42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.10 (0.71, 13.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1323\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMorphology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSaccular\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e366 (92.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFusiform\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (3.81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80 (0.22, 2.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7366\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDissecting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (3.30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00 (0.00, Inf)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9815\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlow Diverter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTubridge Flow Diverter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e206 (52.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePipeline Embolization Device\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e188 (47.72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.56 (0.34, 0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet Count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e248.39\u0026thinsp;\u0026plusmn;\u0026thinsp;61.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00 (1.00, 1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3394\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet Count Tertile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e128 (32.82%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132 (33.85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.43 (0.80, 2.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130 (33.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.18 (0.65, 2.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5838\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProthrombin Time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.08 (0.84, 1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5325\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProthrombin Time Tertile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e128 (32.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e121 (31.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.59 (0.32, 1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140 (35.99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.04 (0.60, 1.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8932\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFibrinogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.76 (0.53, 1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1504\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFibrinogen Tertile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e128 (32.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131 (33.68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.59 (0.33, 1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0679\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130 (33.42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.54 (0.30, 0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0362\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-Dimer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06 (0.95, 1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2973\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-Dimer Tertile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e123 (31.22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137 (34.77%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.60 (0.87, 2.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1287\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e134 (34.01%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.72 (0.94, 3.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0811\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAneurysm Diameter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.36\u0026thinsp;\u0026plusmn;\u0026thinsp;5.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.92 (0.86, 0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAneurysm Diameter Tertile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e127 (32.23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135 (34.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99 (0.58, 1.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9847\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132 (33.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.49 (0.26, 0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0228\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAneurysm Neck\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.14\u0026thinsp;\u0026plusmn;\u0026thinsp;3.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87 (0.79, 0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0076\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAneurysm Neck Tertile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e127 (32.23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135 (34.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.76 (0.44, 1.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3195\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132 (33.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.39 (0.21, 0.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProximal Artery Diameter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.68 (0.51, 0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0081\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProximal Artery Diameter Tertile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131 (33.25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131 (33.25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.70 (0.40, 1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132 (33.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.52 (0.29, 0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0274\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProthrombin Time Activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105.34\u0026thinsp;\u0026plusmn;\u0026thinsp;7.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98 (0.95, 1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1436\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProthrombin Time Activity Tertile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129 (32.74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132 (33.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.10 (0.63, 1.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7471\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133 (33.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.73 (0.40, 1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlanine Aminotransferase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.64\u0026thinsp;\u0026plusmn;\u0026thinsp;10.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98 (0.96, 1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2156\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlanine Aminotransferase Tertile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125 (32.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130 (33.85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.57 (0.32, 1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0569\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129 (33.59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.50 (0.28, 0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0202\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRed Blood Cell Count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62 (0.38, 1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0574\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRed Blood Cell Count Tertile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130 (33.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129 (33.08%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.79 (0.45, 1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4131\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131 (33.59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.53 (0.29, 0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0357\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMultivariate Analysis Results\u003c/h2\u003e \u003cp\u003eThe results of multivariable analysis are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Multivariate regression analysis revealed a significant independent association between TT and incomplete stent stenosis in patients treated with FD for intracranial aneurysms. After adjustment for confounding factors, TT demonstrated a significant independent association with ISS. Each unit increase in TT was associated with approximately 36\u0026ndash;40% higher odds of ISS development (Adjustment model I: OR\u0026thinsp;=\u0026thinsp;1.40, 95% CI: 1.08\u0026ndash;1.80, p\u0026thinsp;=\u0026thinsp;0.010; Adjustment model II: OR\u0026thinsp;=\u0026thinsp;1.36, 95% CI: 1.05\u0026ndash;1.76, p\u0026thinsp;=\u0026thinsp;0.021). When analyzed by tertiles, patients in the middle TT tertile exhibited the highest risk, with more than twice the odds of developing ISS compared to the lowest tertile (Adjustment model II: OR\u0026thinsp;=\u0026thinsp;2.22, 95% CI: 1.04\u0026ndash;4.76, p\u0026thinsp;=\u0026thinsp;0.040).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe results of multivariable analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-adjusted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdjust I\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjust II\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR, 95% CI, P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR, 95% CI, P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR, 95% CI, P\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.19 (0.98, 1.46) 0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.40 (1.08, 1.80) 0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.36 (1.05, 1.76) 0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTT Tertile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.84 (0.99, 3.41) 0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.13 (1.01, 4.49) 0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.22 (1.04, 4.76) 0.040\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.65 (0.90, 3.02) 0.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.05 (0.98, 4.26) 0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.90 (0.89, 4.05) 0.097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eOutcome: ISS\u003c/p\u003e \u003cp\u003eExposure Variables: TT; TT Tertile\u003c/p\u003e \u003cp\u003eAdjust I adjust for: Sex; Age; Hypertension; Diabetes; Hyperlipidemia; Smoke; Anterior Circulation; Morphology (Saccular, Fusiform, Dissecting); Flow Diverter (Tubridge Flow Diverter, Pipeline Embolization Device); Platelet Count; Prothrombin Time; Fibrinogen; D-Dimer; Aneurysm Diameter; Aneurysm Neck; Proximal Artery Diameter; Prothrombin Time Activity; Alanine Aminotransferase; Red Blood Cell Count\u003c/p\u003e \u003cp\u003eAdjust II adjust for: Sex; Age (smooth); Hypertension; Diabetes; Hyperlipidemia; Smoke; Anterior Circulation; Morphology (Saccular, Fusiform, Dissecting); Flow Diverter (Tubridge Flow Diverter, Pipeline Embolization Device); Platelet Count (smooth); Prothrombin Time (smooth); Fibrinogen (smooth); D-Dimer (smooth); Aneurysm Diameter (smooth); Aneurysm Neck (smooth); Proximal Artery Diameter (smooth); Prothrombin Time Activity (smooth); Alanine Aminotransferase (smooth); Red Blood Cell Count (smooth)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSmooth Curve Fitting Analysis\u003c/h2\u003e \u003cp\u003eSmooth curve fitting analysis are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The smooth curve fitting analysis revealed a distinctive non-linear relationship between TT and the risk of ISS following FD placement for intracranial aneurysms. The relationship demonstrated a clear threshold effect with an inflection point at 19.2 seconds of TT. Below this threshold, TT exhibited a significant positive association with ISS risk (OR\u0026thinsp;=\u0026thinsp;1.59, 95% CI: 1.19\u0026ndash;2.13, p\u0026thinsp;=\u0026thinsp;0.002), with each unit increase in TT corresponding to 59% higher odds of developing ISS. The predicted probability of ISS increased steadily from approximately 5% at 14 seconds to a peak of approximately 30% at 19.2 seconds. Beyond this inflection point, the relationship reversed direction (OR\u0026thinsp;=\u0026thinsp;0.26, 95% CI: 0.02\u0026ndash;2.88, p\u0026thinsp;=\u0026thinsp;0.270), with ISS risk declining as TT increased further, though this inverse association did not reach statistical significance. The widening confidence intervals at extreme TT values reflect increased uncertainty in risk estimation for these ranges.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eThe results of the two-piecewise linear regression model\u003c/h2\u003e \u003cp\u003eThreshold effect analysis of ISS using two-piecewise linear regression model are shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. To investigate potential non-linear associations between TT and ISS, we conducted a threshold effect analysis using a two-piecewise linear regression model. Segmented regression analysis confirmed a threshold effect at TT\u0026thinsp;=\u0026thinsp;19.2 seconds. For values below this threshold, each unit increase in TT was associated with a 59% higher risk of ISS (OR\u0026thinsp;=\u0026thinsp;1.59, 95% CI: 1.19\u0026ndash;2.13, p\u0026thinsp;=\u0026thinsp;0.002). Above this threshold, the relationship reversed direction (OR\u0026thinsp;=\u0026thinsp;0.26, 95% CI: 0.02\u0026ndash;2.88, p\u0026thinsp;=\u0026thinsp;0.270), albeit without statistical significance. The likelihood ratio test (p\u0026thinsp;=\u0026thinsp;0.048) validated that the segmented model provided superior fit compared to the conventional linear model. Patients with TT approaching but not exceeding 19.2 seconds may represent a particularly high-risk subgroup requiring enhanced monitoring or adjunctive therapeutic interventions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThreshold Effect Analysis of ISS Using Two-Piecewise Linear Regression Model\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel and Segments\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLinear regression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.08, 1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInflection point\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 19.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.19, 2.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;19.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02, 2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elikelihood ratio test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eThis table presents a two-model analysis showing both linear and non-linear (threshold) effects on ISS outcome. Model II indicates a significant change in effect pattern at the threshold point of 19.2(S).\u003c/p\u003e \u003cp\u003eAdjust: Sex; Age; Hypertension; Diabetes; Hyperlipidemia; Smoke; Anterior Circulation; Morphology; Flow Diverter; Platelet Count; Prothrombin Time; Fibrinogen; D-Dimer; Aneurysm Diameter; Aneurysm Neck; Proximal Artery Diameter; Prothrombin Time Activity; Alanine Aminotransferase; Red Blood Cell Count\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e "},{"header":"DISCUSSION","content":"\u003cp\u003eIn this multicenter retrospective cohort study of 394 patients with unruptured intracranial aneurysms treated with FD, we identified a significant non-linear relationship between TT and ISS risk, characterized by a distinct threshold effect at 19.2 seconds. Below this threshold, each unit increase in TT was associated with 59% higher odds of developing ISS (OR = 1.59, 95% CI: 1.19–2.13, p = 0.002), while above this threshold, the relationship appeared to reverse direction, though this trend did not reach statistical significance (OR = 0.26, 95% CI: 0.02–2.88, p = 0.270). These findings establish TT as a novel biomarker for risk stratification in patients undergoing FD treatment for intracranial aneurysms.\u003c/p\u003e \u003cp\u003eStudies indicate that ISS undergoes dynamic changes during postoperative follow-up. Typically, ISS is most easily detected within the first six months after implantation of a shunt (FD), and then the possibility of partial improvement is observed at 12 months or later. Gui et al.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] reported in their single-center study that prolonged dual antiplatelet therapy correlates with increased rates of ISS regression, suggesting that ISS may represent a common self-limiting complication. Additionally, Cohen's retrospective analysis[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] demonstrated stenosis reduction with intensified clopidogrel therapy (150 mg/day), revealing cases that improved from moderate to mild stenosis during follow-up imaging. However, complete resolution of ISS is uncommon[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], indicating that it is a structural manifestation of the endothelial response to FD implantation rather than merely a transient or incidental finding. This study focuses on evaluating the predictive value of preoperative TT levels for the occurrence of ISS, rather than assessing its severity or temporal changes. Regardless of whether ISS is symptomatic, its presence could elevate the risk of long-term ischemic events. Our findings demonstrate a nonlinear relationship between TT levels and the risk of ISS, identifying a predictive threshold of 19.2 seconds, which underscores its potential clinical utility in risk stratification and management of ISS.\u003c/p\u003e \u003cp\u003eOur investigation into the non-linear relationship between TT and ISS reveals both congruencies and divergences with existing literature. Several studies have demonstrated that prolonged TT correlates with reduced stenosis risk. Yu et al researched bioabsorbable Heparin-Silk Fibroin (Hep-SF) stent coverings and documented significant TT prolongation[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], concluding that this anticoagulant effect may diminish thrombus formation at stenotic sites. Similarly, Huang et al. investigated Chitosan-Heparin (ChS-HEP) multilayer film-modified stents[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], demonstrating enhanced hemocompatibility with prolonged TT, suggesting these modifications prevent vascular stenosis through altered coagulation dynamics. In another study, Jia et al. compared bivalirudin versus heparin in percutaneous coronary intervention (PCI) and concluded that bivalirudin might mitigate post-PCI stenosis and thrombosis by stabilizing coagulation parameters, including TT[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Conversely, Yu et al. examined microplastics in extracranial artery stenosis (ECAS) patients and observed elevated TT alongside increased microplastic concentrations[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], hypothesizing that microplastics might exacerbate arterial stenosis through coagulation dysfunction, though direct TT-stenosis correlations were not analyzed. While these studies collectively support the association between coagulation parameters and stent-related complications, they predominantly presupposed linear relationships. Our research uniquely identified a threshold effect at 19.2 seconds, with TT and ISS risk showing significantly positive correlation below this threshold but reversing trend above it—likely reflecting distinct pathophysiological mechanisms operating under various coagulation states. This novel finding provides a critical theoretical foundation for optimizing individualized anticoagulation strategies in clinical practice, suggesting that TT management should target specific ranges rather than simply maximizing anticoagulation effects.\u003c/p\u003e \u003cp\u003eThe non-linear relationship between TT and ISS likely reflects the complex mechanisms of coagulation system involvement in stent-related vascular pathology. Thrombin, as a key enzyme in the coagulation cascade[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], influences not only thrombus formation but also participates in vascular wall repair and remodeling through multiple pathways[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Goel et al discovered that thrombin promotes smooth muscle cell (SMC) proliferation and migration to injury sites through activation of PI3K/Akt and Ras pathways, contributing to neointimal formation[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, Shen et al. demonstrated that Direct Thrombin Inhibitors (DTIs) such as dabigatran target thrombin's active site, thereby reducing thrombotic risk[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Furthermore, Catar et al. showed that thrombin, through ERK/AP-1 signal cascades, binds to the Vascular Endothelial Growth Factor (VEGF) promoter (region − 267 to -53), promoting VEGF mRNA synthesis and protein secretion, thus driving endothelial proliferation and angiogenesis[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. We observed that patients in the low TT group typically presented with higher proportions of smoking history, hypertension, and diabetes—factors known to exacerbate endothelial dysfunction and inflammatory responses—which, acting synergistically with enhanced thrombin activity, may accelerate the progression of in-stent stenosis; interestingly, when TT values exceeded the 19.2-second threshold, ISS risk decreased rather than increased, possibly related to impaired endothelial repair function due to reduced thrombin activity, as moderate thrombin activity is necessary for maintaining and repairing vascular endothelial integrity[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Based on these mechanisms, for patients with low TT, intensified antiplatelet therapy with consideration of short-term anticoagulation may be more rational, whereas for high TT patients, potent anticoagulants should be used cautiously to avoid delayed vascular endothelial repair. Li et al.'s research on heparin-coated stents offers a strategy for local regulation of thrombin activity, with controlled release of heparin from the coating potentially reducing thrombotic risk while maintaining adequate endothelial repair capacity[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Future research should explore the applicability of TT thresholds across different populations, conduct prospective studies to validate the impact of TT-based individualized anticoagulation strategies on ISS incidence, and investigate novel biomarker combinations to improve predictive accuracy.\u003c/p\u003e \u003cp\u003eOur findings demonstrate significant clinical translational value. First, the identified non-linear relationship between TT and ISS risk, with a threshold of 19.2 seconds, provides a reference standard for risk stratification following FD treatment of intracranial aneurysms. For high-risk patients with TT below 19.2 seconds, anticoagulation therapy may be considered when necessary, or antiplatelet therapy duration could be extended; conversely, for patients with TT above this threshold, alternative therapeutic strategies may be warranted to mitigate complications related to stenosis or hemorrhage. Second, our research offers novel insights for stent design, suggesting the potential development of drug-eluting stents specifically engineered to modulate thrombin activity. Finally, given the complexity of the coagulation system, future investigations should explore the value of combining TT with other coagulation parameters in predictive models for ISS, validate the applicability of the TT threshold across diverse populations, and evaluate the clinical outcomes of TT-adjusted anticoagulation strategies. Based on our findings, we have proposed actionable clinical recommendations that provide an evidence-based foundation for developing individualized anticoagulation protocols in this patient population.\u003c/p\u003e "},{"header":"LIMITATIONS","content":"\u003cp\u003eSeveral limitations of this study warrant careful consideration. First, our retrospective cohort design restricts the sample size and may introduce potential bias due to uneven distributions among patient groups. A prospective trial involving a larger number of random samples and long-term follow-up is necessary to validate our conclusions. Second, since all participants were drawn from four medical centers in southern China, caution should be exercised when generalizing these findings to other ethnic groups or regions. Third, as an observational study, we could only establish associations between TT and ISS rather than causal relationships. Fourth, while we controlled for multiple known confounders through multivariate analysis, unmeasured confounding factors may still affect the results. Additionally, our inclusion criteria excluded certain special populations, such as patients with coagulation disorders and severe hepatic or renal dysfunction, meaning our findings may not be applicable to these specific groups. Finally, given the relatively short follow-up period, longer-term follow-up studies are needed to assess the sustained impact of TT on ISS.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eThis multicenter retrospective cohort study pioneered the revelation of TT's critical threshold effect in assessing ISS risk following FD treatment for intracranial aneurysms, identifying 19.2 seconds as a pivotal inflection point where TT level serves as a reliable parameter for ISS risk evaluation. For TT values below this threshold, each unit increase was associated with 59% higher likelihood of developing ISS at follow-up. These results may help identify patients at higher risk for ISS who might benefit from more intensive.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (grant 81974177), the Zhongshan Science and Technology Bureau (grant 2020B1130) and Guangdong Second Provincial Genera Hospital (grant WKZX2023CZ0214, grant TJGC-2023012).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest/Competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study protocol received approval from the Ethics Committees of Zhujiang Hospital of Southern Medical University (approval number: 2024-KY-211), Zhongshan Hospital of Traditional Chinese Medicine (approval number: 2024ZSZY-LL-KY-315), The First Affiliated Hospital of Zhengzhou University (approval number: 2022-KY-0861), and the Eighth Affiliated Hospital of Sun Yat-sen University (approval number: 2024r298). Given the retrospective nature of the analysis and the anonymization of all patient data without additional interventions or follow-up procedures, the requirement for informed consent was waived in accordance with the principles of the Declaration of Helsinki. The research team strictly adhered to the Chinese ethical review regulations for human biomedical research and international ethical guidelines to ensure patient privacy and data security. All study data were stored on password-protected secure servers with access restricted to authorized research personnel only. This study received no commercial funding that might constitute a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, the data of the study population were sourced from the Hospital Information System. Therefore, to protect patient privacy, the datasets are not publicly available. However, the data can be accessed upon reasonable request through the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDue to the study's retrospective design and the anonymization of patient data, informed consent was waived by the Ethics Committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZhikun Jia, Jiayin Ma, Qile He, Jialin Gao, Yuqi Xie, Zhichao Wu, Mengshi Huang, Zhixi Li, Xin Jin: Investigation, Data curation, Formal analysis, Visualization, Writing – original draft. Zhikun Jia: Conceptualization, Methodology, Software. Zhikun Jia, Jiahe Yin, Shenquan Guo, Wenchao Liu, Shixing Su, Fa Jin: Writing – review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eXuetao Wang, Xuying He and Xin Zhang: Funding acquisition.\u003c/p\u003e\n\u003cp\u003eChuanzhi Duan, Xuying He and Xin Zhang: Conceptualization, Validation, Project administration, Supervision, Writing – review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eXin Zhang and Xuying He are co-corresponding authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Professor Chi Chen for his valuable contributions to the professional statistical analysis of the study data. We gratefully acknowledge the funding support from Xuetao Wang. We would like to thank Xuetao Wang, Tao Quan, and Bin Luo for their valuable contributions to data collection and analysis in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate declarations\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBrown RD Jr., Broderick JP (2014) Unruptured intracranial aneurysms: epidemiology, natural history, management options, and familial screening. 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Mater Sci Eng C Mater Biol Appl 73:198\u0026ndash;205. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.msec.2016.12.070\u003c/span\u003e\u003cspan address=\"10.1016/j.msec.2016.12.070\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"neurosurgical-review","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nrev","sideBox":"Learn more about [Neurosurgical Review](https://www.springer.com/journal/10143)","snPcode":"10143","submissionUrl":"https://submission.nature.com/new-submission/10143/3","title":"Neurosurgical Review","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"intracranial aneurysm, flow diverter, thrombin time, stenosis","lastPublishedDoi":"10.21203/rs.3.rs-6384391/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6384391/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUnruptured intracranial aneurysms are common neurovascular diseases, and flow diverters (FD) are emerging as a key treatment modality. However, in-stent stenosis (ISS) remains a frequent complication following FD treatment, increasing thromboembolic risks. Thrombin time (TT), a critical coagulation indicator, has potential associations with ISS risk. To investigate the relationship between TT and ISS risk, focusing on potential threshold effects. This multicenter retrospective cohort study included 394 patients with unruptured intracranial aneurysms treated with FD between March 2016 and October 2024. The primary exposure was preoperative TT, and the primary outcome was ISS occurrence during follow-up. Generalized additive models explored non-linear relationships, with segmented linear regression determining threshold points. ISS occurred in 22.84% (90/394) of patients. TT exhibited a non-linear relationship with ISS risk, with a threshold of 19.2 seconds. For TT values below this threshold, each unit increase was linked to a 59% higher likelihood of developing ISS (OR\u0026thinsp;=\u0026thinsp;1.59, 95% CI: 1.19\u0026ndash;2.13, p\u0026thinsp;=\u0026thinsp;0.002). These findings may assist in identifying patients at greater risk for ISS who could benefit from more intensive intervention.\u003c/p\u003e","manuscriptTitle":"The Role of Thrombin Time as an Independent Variable in Predicting In-Stent Stenosis Risk After Flow Diverter Treatment for Intracranial Aneurysms: A Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-22 10:28:20","doi":"10.21203/rs.3.rs-6384391/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-18T12:29:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-09T10:08:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"219700868938046895077177650866034135008","date":"2025-06-25T18:24:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-04T06:26:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"280482849205315151689773028373009595777","date":"2025-06-03T15:38:12+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-19T13:57:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-09T19:36:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-09T08:26:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"Neurosurgical Review","date":"2025-04-06T02:28:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"neurosurgical-review","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nrev","sideBox":"Learn more about [Neurosurgical Review](https://www.springer.com/journal/10143)","snPcode":"10143","submissionUrl":"https://submission.nature.com/new-submission/10143/3","title":"Neurosurgical Review","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"12f452b0-c0aa-4683-8a7c-6e1eb2c17138","owner":[],"postedDate":"May 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-27T16:23:10+00:00","versionOfRecord":{"articleIdentity":"rs-6384391","link":"https://doi.org/10.1007/s10143-025-03899-y","journal":{"identity":"neurosurgical-review","isVorOnly":false,"title":"Neurosurgical Review"},"publishedOn":"2025-10-24 16:16:09","publishedOnDateReadable":"October 24th, 2025"},"versionCreatedAt":"2025-05-22 10:28:20","video":"","vorDoi":"10.1007/s10143-025-03899-y","vorDoiUrl":"https://doi.org/10.1007/s10143-025-03899-y","workflowStages":[]},"version":"v1","identity":"rs-6384391","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6384391","identity":"rs-6384391","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}