Carotid Intraplaque Neovascularization Increases the Risk of Recurrent Anterior Circulation Ischemic Stroke: A Prospective Cohort Study

Carotid Intraplaque Neovascularization Increases the Risk of Recurrent Anterior Circulation Ischemic Stroke: A Prospective 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 Carotid Intraplaque Neovascularization Increases the Risk of Recurrent Anterior Circulation Ischemic Stroke: A Prospective Cohort Study Hao Zhang, Jun He, Jimei Xu, Rongfeng Wang, Shugang Cao, Mingwu Xia This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8197849/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background and purpose The prognostic value of intraplaque neovascularization (IPN) in carotid artery plaques for predicting recurrent anterior circulation ischemic stroke (ACIS) remains uncertain. This study aimed to evaluate whether IPN can predict recurrent stroke in patients with ACIS and to determine whether the integration of IPN with conventional risk factors enhances risk stratification. Methods We prospectively enrolled consecutive patients with acute cerebral infarction syndrome (ACIS) who underwent assessment of intraplaque neovascularization (IPN) using AngioPLUS, an ultrasound-based imaging modality, between August 2020 and February 2025. A Cox proportional hazards regression model was employed to identify independent predictors of recurrent ischemic stroke. The predictive performance of a novel model incorporating IPN was compared with that of a conventional model excluding IPN by calculating the time-dependent area under the receiver operating characteristic curve (AUC). Results A total of 143 patients were included in the analysis, comprising 93 men and 50 women, with a mean age of 67.6 ± 11.7 years. The follow-up period ranged from 6 to 56 months, with a median duration of 21 months. Recurrent ischemic stroke occurred in 26 patients. Intergroup comparisons revealed significantly higher levels of fasting blood glucose (P = 0.012), homocysteine (P = 0.018), and a greater proportion of patients with grade 2 IPN (P = 0.002) in the recurrence group compared to the non-recurrence group. Multivariate Cox regression analysis identified grade 2 IPN as an independent predictor of recurrent ischemic stroke (HR = 6.936; 95% CI, 2.464–19.524; P < 0.001). Time-dependent receiver operating characteristic analysis showed that adding carotid IPN to the conventional model significantly improved its predictive accuracy for recurrent ACIS at 24, 36, and 48 months (all P < 0.05). Conclusion Carotid IPN is an independent predictor of recurrent ACIS. Incorporating IPN assessment with conventional risk factors improves the identification of high-risk patients. Carotid plaque Intraplaque neovascularization Stroke recurrence Figures Figure 1 Figure 2 Figure 3 Introduction The carotid artery serves as a critical “window” into systemic arterial health, and the pathological characteristics of carotid plaque—particularly plaque vulnerability—have become a major focus in understanding the pathogenesis of ischemic stroke[1]. However, whether all carotid plaques warrant statin therapy remains controversial[2–4]. Compared with stable plaques, vulnerable plaques confer a substantially higher risk of causing ischemic stroke. Among the key features associated with plaque vulnerability, intraplaque neovascularization (IPN) has emerged as a pivotal area of research. Carotid IPN contributes to an increased risk of intraplaque hemorrhage, which may promote plaque rupture or embolization. Moreover, IPN is implicated in the progression of carotid atherosclerosis, potentially exacerbating vascular stenosis and ultimately leading to vessel occlusion[5, 6]. Recent years have witnessed accumulating evidence indicating that the distribution characteristics and severity of carotid intraplaque neovascularization (IPN), as assessed by contrast-enhanced ultrasonography (CEUS), are closely associated with the occurrence of ischemic stroke[7]. It has been hypothesized that carotid IPN may increase the risk of recurrent anterior circulation ischemic stroke (ACIS). However, the widespread clinical adoption of CEUS is limited by its relatively high cost, invasive nature, requirement for specialized operator expertise, and potential risk of contrast agent allergy[8]. AngioPLUS technology, a novel microvascular Doppler ultrasonography, offers higher resolution and is capable of detecting minute vessels and low-velocity blood flow signals[9, 10]. Subsequent semi-quantitative grading of IPN using this technology facilitates the assessment of plaque vulnerability[11]. Studies have established carotid IPN as an independent risk factor for ischemic stroke[12, 13]. Nevertheless, it remains unclear whether the evaluation of carotid IPN provides incremental clinical value beyond conventional cerebrovascular risk factors in stratifying the risk of ischemic stroke recurrence. This study aimed to investigate the association between carotid IPN, as detected by AngioPLUS technology, and the risk of recurrent anterior circulation ischemic stroke, and to determine whether integrating IPN assessment with conventional cerebrovascular risk factors improves the predictive capability for stroke recurrence. Patients and Methods Study population Between August 2020 and February 2025, 170 patients with ACIS and carotid atherosclerotic plaques were enrolled at Hefei Second People's Hospital. The study protocol was approved by the local ethics committee. Written informed consent was obtained from all participating patients or their legal guardians. Inclusion criteria were as follows: (1) diagnosis of ischemic stroke with the presence of at least one carotid atherosclerotic plaque (thickness > 1.5 mm) ipsilateral to the side of ischemic stroke. Exclusion criteria were as follows: (1) significant plaque calcification on carotid ultrasound that substantially interfered with the assessment of intraplaque neovascularization (IPN); (2) complete carotid artery occlusion, or history of carotid endarterectomy or carotid artery stenting; (3) stroke subtypes including cardioembolism, small vessel occlusion, stroke of other determined etiology, or stroke of undetermined etiology; (4) isolated posterior circulation infarction; (5) concomitant intracerebral hemorrhage or large-area infarction; (6) severe cardiopulmonary dysfunction, hepatic or renal failure, or malignancy; (7) concurrent infection or autoimmune disease; and (8) incomplete clinical or radiological data. Collection of Clinical Data Comprehensive clinical data were collected for all enrolled patients, including demographic characteristics (e.g., sex, age), personal histories (e.g., smoking, alcohol consumption), and cerebrovascular risk factors (e.g., hypertension, diabetes mellitus, hyperlipidemia). Past medical histories, including coronary heart disease, prior ischemic stroke, and medication use (e.g., anticoagulants, lipid-lowering agents, hypoglycemic drugs, and antihypertensive agents), were also recorded. Blood pressure (systolic and diastolic) was documented upon admission. Medication adherence was evaluated based on whether patients took their prescribed oral medications (including antiplatelet agents, hypoglycemic drugs, antihypertensives, and lipid-lowering agents) as directed at discharge. For any medication discontinuation, the reasons were ascertained. Patients who discontinued medication for more than one month were classified as having poor medication adherence[14]. Laboratory Parameters Blood samples were collected from all participants in the early morning following an overnight fast. These samples underwent routine blood testing, biochemical analysis, and coagulation parameter assessment. Complete blood counts were performed using the Sysmex XN-10 automated hematology analyzer. Levels of fasting blood glucose (FBG), glycated hemoglobin (HbA1c), triglycerides (TG), total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), homocysteine (HCY), and creatinine (Cr) were measured using an automated biochemical analyzer (HITACHI Automatic Analyzer 7600–020, Japan). Diagnosis of Carotid Plaque and IPN Evaluation​ Conventional ultrasonography was performed along the carotid arteries in this study. Upon identification of a carotid plaque, AngioPLUS imaging was conducted using a French Sonic SuperSonic Imagine AixPlorer ultrasound system (Sonic Red series, equipped with AP ultrasound imaging technology and an SL10-2 transducer) to detect and evaluate intraplaque neovascularization (IPN) within the target plaque. In cases with multiple plaques, the thickest plaque on one side was selected as the target for analysis. IPN grading was determined as follows[10, 15]: under AngioPLUS mode, IPN was identified by the presence of short-linear or strip-like high-signal echoes observed within a 2-minute dynamic clip. The IPN score was assigned based on the following criteria: score 0, no detectable flow signals within the plaque; score 1, a few punctate or short-linear flow signals (< 4 signals) located unilaterally within the plaque; score 2, dendritic or diffuse linear flow signals within the plaque. For clinical interpretation, IPN scores were categorized into low IPN (scores 0–1) and high IPN (score 2) (Fig. 1 ). All examinations were independently evaluated by two trained sonographers using a double-blind method. In cases of disagreement, a third senior sonologist was consulted to reach consensus. Sonographers were blinded to all patient laboratory data. IPN Grading: Panel A shows a grade 0 IPN score; Panel B represents a grade 1 score; Panel C corresponds to a grade 2 score. The left side of each panel displays the two-dimensional B-mode ultrasound image, while the right side shows the corresponding AngioPLUS imaging depicting microvascular flow signals. Follow-up and Endpoints​ Patients enrolled with acute anterior circulation ischemic stroke (ACIS) were scheduled for follow-up assessments every six months via telephone interviews or outpatient clinic visits. Those who developed any suspected stroke symptoms were promptly hospitalized and underwent diffusion-weighted imaging magnetic resonance imaging (DWI-MRI) to confirm the occurrence of recurrent acute ischemic stroke. The primary outcome was the incidence of DWI-confirmed ipsilateral ACIS recurrence. The follow-up endpoint was set at August 30, 2025. Statistical Analysis​ Statistical analyses were performed using R software, version 4.5.0 (R Foundation for Statistical Computing, Vienna, Austria). A two-sided p-value < 0.05 was considered statistically significant. Continuous variables with normal distribution are presented as mean ± standard deviation, while non-normally distributed variables are expressed as median (interquartile range). Group comparisons for normally distributed continuous variables were performed using the Student’s t-test, and the Wilcoxon rank-sum test was used for non-normally distributed variables. Categorical variables are summarized as frequencies (percentages) and compared using the chi-square test. Variables showing a statistically significant association (p < 0.05) in univariate Cox proportional hazards regression models were included in a multivariate Cox model to evaluate the independent association between IPN and the risk of recurrent anterior circulation ischemic stroke. To assess the predictive value of IPN for ipsilateral recurrent stroke, time-dependent receiver operating characteristic (ROC) curve analysis was conducted. The areas under the curve (AUC) for a model incorporating IPN and a conventional model without IPN were calculated and compared to evaluate incremental predictive performance. Results Study Population and Baseline Clinical Characteristics A total of 170 patients with symptomatic carotid artery stenosis were initially enrolled. However, 27 patients were excluded for the following reasons: seven due to poor-quality ultrasonographic images; eight with isolated posterior circulation infarction; two with cardioembolic embolism; two with malignancy; two with Moyamoya disease; and six with incomplete clinical or radiological data (Fig. 2 ). Consequently, 143 patients (93 men and 50 women; mean age, 67.6 ± 11.7 years) who met the inclusion criteria were included in the final analysis. The follow-up duration ranged from 6 to 56 months, with a mean of 21 months. During follow-up, recurrent ischemic stroke occurred in 26 patients (5 with IPN grade 1 and 21 with IPN grade 2). Patient Baseline Characteristics Patients were classified into "recurrent" (n = 26) and "non-recurrent" (n = 117) groups according to the occurrence of recurrent ischemic stroke. Baseline characteristics are summarized in Table 1 . No statistically significant differences were observed in demographic parameters between the two groups. However, fasting blood glucose (P = 0.012), homocysteine levels (P = 0.018), and the proportion of patients with IPN grade 2 (P = 0.002) were significantly higher in the recurrence group compared to the non-recurrence group. Table 1 Baseline characteristics of patients (N = 143). Non-recurrent(n =117 ) Recurrent(n = 26) p -value Age, year, mean ± SD 67.35 ± 12.166 68.54 ± 9.791 0.537 Sex, man, n (%) 74(63.2) 18(69.2) 0.565 Hypertension, n (%) 56(47.9) 14(53.8) 0.581 Diabetes, n (%) 27(23.1) 10(38.5) 0.105 Hyperlipidemia, n (%) 31(26.5) 5(19.2) 0.440 coronary heart disease, n (%) 16(13.7) 4(15.4) 0.820 History of stroke,n (%) 28(23.9) 9(34.6) 0.261 Smoking, n (%) 39(33.3) 10(38.5) 0.618 Drinking, n (%) 33(28.2) 8(30.8) 0.794 Poor medication adherence, n (%) 22(18.8) 8(30.8) 0.175 BMI, mean ± SD 24.33 ± 2.721 25.13 ± 2.283 0.099 TG, median (IQR) 1.44(1.02, 2.31) 1.42(0.85, 4.01) 0.628 TC, median (IQR) 4.41(3.71, 5.02) 4.45(4.01, 5.18) 0.593 HDL-C, mean ± SD 1.21 ± 0.278 1.16 ± 0.266 0.902 LDL-C, mean ± SD 2.75 ± 0.820 3.49 ± 0.639 0.192 FBG, median (IQR) 5.28(4.84, 7.04) 6.44(5.43, 9.46) 0.012 HCY, median (IQR) 12.00(10.20, 16.85) 16.00(12.02, 20.38) 0.018 Cr, median (IQR) 68(56.00, 81.50) 67.50(55.25, 83.75) 0.969 Thrombolysis, n (%) 12(10.3) 4(15.4) 0.453 IPN, n (%) <0.001 Grades 0 and 1, n (%) 78(94.0) 5(6.0) Grades 2, n (%) 39(33.3) 21(80.8) Note: BMI, body mass index; TG, triglycerides; TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; FBG, fasting blood glucose; HCY, homocysteine; Cr, creatinine; IQR, interquartile range; IPN, intraplaque neovascularization. Association Between IPN Grading and the Risk of Recurrent Acute Ischemic Stroke Univariate Cox regression analysis identified the following factors as significantly associated with recurrent ischemic stroke: diabetes mellitus (HR 3.274, 95% CI 1.466–7.312, P = 0.004), poor medication adherence (HR 2.399, 95% CI 1.034–5.567, P = 0.042), elevated low-density lipoprotein cholesterol (LDL-C) levels (HR 2.195, 95% CI 1.375–3.504, P < 0.001), and presence of grade 2 intraplaque neovascularization (IPN) (HR 4.936, 95% CI 1.859–13.105, P = 0.001). Variables with P ≤ 0.05 in univariate analysis—diabetes mellitus, poor medication adherence, elevated LDL-C, and grade 2 IPN—were included as covariates in a multivariate Cox regression model. Multivariate analysis confirmed that grade 2 IPN was an independent predictor of recurrent ischemic stroke (HR 6.936, 95% CI 2.464–19.524, P < 0.001) (Table 2 ). Table 2 Predictive factors for future ischemic stroke Univariable analysis Multivariable analysis HR 95%CI P-value HR 95%CI P-value Age 1.009 0.975 ~ 1.043 0.613 - - - Male 1.293 0.562 ~ 2.975 0.546 - - - Hypertension 1.408 0.651 ~ 3.046 0.385 - - - Diabetes 3.274 1.466 ~ 7.312 0.004 2.253 0.967 ~ 5.247 0.060 Hyperlipidemia 1.149 0.430 ~ 3.071 0.782 - - - coronary heart disease 1.589 0.547 ~ 4.620 0.395 - - - History of stroke 1.381 0.615 ~ 3.100 0.434 - - - Smoking 1.386 0.628 ~ 3.060 0.419 - - - Drinking 1.256 0.545 ~ 2.898 0.592 - - - Poor medication adherence 2.399 1.034 ~ 5.567 0.042 3.385 1.319 ~ 8.685 0.011 BMI 1.149 0.968 ~ 1.364 0.112 - - - SBP 0.991 0.975 ~ 1.008 0.287 - - - DBP 1.001 0.977 ~ 1.026 0.932 - - - TG 0.926 0.622 ~ 1.376 0.702 - - - TC 1.155 0.763 ~ 1.750 0.495 - - - HDL-C 0.752 0.167 ~ 3.389 0.711 - - - LDL-C 2.195 1.375 ~ 3.504 <0.001 1.825 1.128 ~ 2.953 0.014 FBG 1.127 0.995 ~ 1.277 0.059 - - - HCY 1.030 0.991 ~ 1.070 0.130 - - - Cr 1.003 0.985 ~ 1.023 0.719 - - - Carotid IPN (grade 2) 4.936 1.859 ~ 13.105 0.001 6.936 2.464 ~ 19.524 <0.001 Note:​BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; TG, triglycerides; TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; FBG, fasting blood glucose; HCY, homocysteine; Cr, creatinine; IPN, intraplaque neovascularization. Predictive Value of IPN Grading for Stroke Recurrence Risk Over time, Model 2 demonstrated greater areas under the receiver operating characteristic (ROC) curves than Model 1 (Fig. 3 ). At 12 months, the area under the curve (AUC) for Model 2 was 0.855 (95% CI, 0.735–0.974), compared with 0.847 (95% CI, 0.750–0.943) for Model 1 (P = 0.901). At 24 months, the AUC for Model 2 was significantly higher than that for Model 1 (0.853 [95% CI, 0.765–0.941] vs. 0.749 [95% CI, 0.631–0.867], P = 0.040). This significant advantage of Model 2 persisted at 36 months (AUC 0.877 [95% CI, 0.793–0.961] vs. 0.756 [95% CI, 0.636–0.876], P = 0.016) and at 48 months (AUC 0.866 [95% CI, 0.759–0.973] vs. 0.733 [95% CI, 0.578–0.887], P = 0.035). Time-dependent ROC curve analysis indicated that incorporating IPN assessment into Model 1—which initially included only traditional risk factors (age, hypertension, diabetes, and LDL-C)—resulted in Model 2, which exhibited significantly improved predictive performance for recurrent anterior circulation ischemic stroke at 24, 36, and 48 months (Fig. 3 ). Therefore, IPN serves as a robust predictor of ischemic stroke recurrence. Targeted therapeutic interventions addressing IPN may potentially reduce recurrence risk in patients with ACIS. Model 1 was defined as the traditional prediction model including age, hypertension, diabetes mellitus, medication adherence, and LDL-C. Model 2 incorporated IPN into the traditional model. tdAUROC denotes the time-dependent area under the receiver operating characteristic curve. Discussion This study demonstrated that carotid intraplaque neovascularization (IPN), as assessed by AngioPLUS technology, remains an independent risk factor for recurrent anterior circulation ischemic stroke, even after adjusting for conventional cerebrovascular risk factors. Incorporating IPN evaluation with traditional risk factors enhances the ability to predict stroke recurrence, thereby assisting clinicians in identifying patients at high risk for recurrent ischemic events. Carotid atherosclerotic plaque is a major etiological contributor to ischemic stroke, with approximately 20% of cases attributed to embolism following plaque rupture. Assessment of plaque stability is therefore critical for the prevention of ischemic stroke. Intraplaque neovascularization (IPN) has emerged as a key indicator of plaque vulnerability and is strongly associated with an increased risk of both incident and recurrent ischemic stroke[7, 12, 16]. Consequently, IPN grading holds significant predictive value for stroke risk stratification. This study demonstrated that carotid intraplaque neovascularization (IPN) is significantly associated with the risk of recurrent ipsilateral acute cerebral infarction (ACIS). This association remained statistically robust after adjustment for potential confounding factors. Moreover, the integration of carotid IPN grading into a prediction model based on conventional cerebrovascular risk factors substantially improved the model’s ability to predict recurrent ACIS. These findings suggest that carotid IPN may serve as a novel biomarker for predicting stroke recurrence and represent a potential therapeutic target for preventing recurrent ischemic events. IPN grading exhibits considerable predictive utility in stroke risk assessment. Cheng et al. reported that intraplaque neovascularization (IPN) was independently associated with adverse outcomes at 90 days in patients with ischemic stroke[17]. A prospective study of 155 ischemic stroke patients followed over 24 months found that grade 2 IPN was independently correlated with stroke recurrence. Similarly, Huang et al. showed that carotid IPN detected by contrast-enhanced ultrasonography (CEUS) was independently associated with ischemic stroke recurrence[18]. Zhang et al. further demonstrated that in patients with mild carotid stenosis, the presence of carotid IPN independently predicted future ischemic events in both symptomatic and asymptomatic individuals[12]. Consistent with these findings, the present study confirmed that carotid IPN remained independently associated with ACIS recurrence after adjusting for confounders including diabetes history, medication adherence, and low-density lipoprotein levels. Cui et al. suggested that combining IPN assessment with a baseline model—including hypoechoic plaque, smoking, and elevated homocysteine levels—improved the identification of patients at high risk for ischemic stroke recurrence compared to the baseline model alone[18]. The current study further revealed that incorporating carotid IPN grading into traditional cerebrovascular risk factor models significantly enhanced predictive performance for recurrent ACIS. These results highlight the potential of IPN grading to refine existing stroke risk stratification systems, supporting the clinical applicability of a combined prediction model for assessing stroke recurrence risk. Atherosclerosis is a systemic disease process, and contemporary research frequently employs carotid IPN as a surrogate marker for cerebrovascular event prediction[19, 20]. Future studies should evaluate IPN grading across multiple vascular territories to enable a more comprehensive assessment of stroke risk and recurrence. The formation of intraplaque neovascularization (IPN) is regulated by multiple interacting factors, including dysregulation of glucose and lipid metabolism, inflammatory responses, and other extrinsic elements. These factors act through complex pathophysiological mechanisms to promote IPN development, thereby influencing plaque stability. Dysregulation of glucose and lipid metabolism represents a significant contributor to IPN formation. A study of 157 patients with acute cerebral ischemic stroke (ACIS) and carotid artery stenosis showed that the risk of developing IPN grade 3–4 was 5.55-fold higher in patients with blood glucose levels > 13.35 mmol/L compared to those with levels < 6.20 mmol/L[21]. Abnormal lipid metabolism is also closely associated with IPN. A cross-sectional study of 250 high-stroke-risk patients undergoing superb microvascular imaging for carotid IPN detection demonstrated that the IPN-positive group had significantly higher levels of total cholesterol, low-density lipoprotein cholesterol (LDL-C), and non-high-density lipoprotein cholesterol (non-HDL-C) than the IPN-negative group[22]. Furthermore, a study of 244 patients with carotid plaques assessed by contrast-enhanced ultrasonography revealed that obesity indicators—including body mass index, upper arm circumference, and waist-to-height ratio—were positively correlated with IPN grade, potentially mediated by metabolic disturbances and adipose tissue-induced inflammatory responses [21, 23]. Additionally, clinical evidence suggests that elevated serum uric acid and homocysteine levels may promote IPN formation, whereas bilirubin may exert an inhibitory effect[24]. Inflammatory response is a key driver of IPN progression. In a study of 144 patients with asymptomatic carotid artery stenosis evaluated by contrast-enhanced ultrasonography, individuals in the highest quartile of neutrophil-to-lymphocyte ratio (NLR) had a 4.55-fold increased risk of IPN grade 2 compared to those in the lowest quartile[25]. Another study involving 244 patients with carotid plaques found significantly higher D-dimer levels in the vulnerable plaque group (IPN grade 3–4) than in the stable plaque group, indicating a strong association between activation of the fibrinolytic system and plaque instability[21, 23]. Future research should focus on identifying additional risk factors and elucidating the underlying molecular mechanisms of IPN formation to identify potential therapeutic targets for inhibiting pathological neovascularization [22, 26–28]. This study has several limitations. First, the relatively long follow-up period and limited sample size warrant validation through future multicenter studies with larger cohorts. Second, documentation and follow-up regarding post-discharge medication adherence were insufficiently detailed; only medication discontinuation status was recorded. Incorporating specific types of medication discontinuation into the predictive model could enhance the comprehensiveness of the analysis. Third, as a single-center study, over 90% of participants were recruited from the Hefei region, which may introduce selection bias. Conclusion In summary, IPN serves as an independent risk factor for stroke recurrence in patients with ACIS. Moreover, integrating IPN assessment into risk prediction models significantly improves the accuracy of conventional cerebrovascular risk factors in identifying patients at high risk of recurrent ischemic stroke. Declarations Ethics approval and consent to participate This study was approved by the Institutional Review Board of the Second People's Hospital of Hefei (Hefei Hospital Affiliated to Anhui Medical University). The study was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was obtained from all participating patients or their legal guardians. Availability of data and materials All data generated during this study are included in the published article. The datasets analyzed during the current study are available from the corresponding author upon reasonable request. Conflict of Interest The authors declare no conflicts of interest. Funding: Hefei Municipal Health Commission Applied Medical Research Project (No. Hwk2022zd004) Scientific Research Foundation of Anhui Medical University (No. 2023xkj231) Natural Science Key Project of Bengbu Medical University (No. 2024byzd423) Authors' contributions S.C. and H.Z. contributed to study design, data collection, statistical analysis, and manuscript writing. J.H. and R.W. were responsible for clinical and laboratory data collection. H.Z., J.X., and S.C. collected and analyzed ultrasound data. H.Z. prepared the figures. S.C. and M.X. participated in data interpretation and critical revision of the manuscript. All authors read and approved the final version of the manuscript. References Ding S, Zhang M, Zhao Y, Chen W, Yao G, Zhang C, et al. The role of carotid plaque vulnerability and inflammation in the pathogenesis of acute ischemic stroke. Am J Med Sci. 2008;336 1:27-31; doi: 10.1097/MAJ.0b013e31815b60a1. Koole D, Heyligers J, Moll FL, Pasterkamp G. Intraplaque neovascularization and hemorrhage: markers for cardiovascular risk stratification and therapeutic monitoring. J Cardiovasc Med (Hagerstown). 2012;13 10:635-9; doi: 10.2459/JCM.0b013e3283590cd2. Du R, Cai J, Cui B, Wu H, Zhao XQ, Ye P. Rapid improvement in carotid adventitial angiogenesis and plaque neovascularization after rosuvastatin therapy in statin treatment-naïve subjects. J Clin Lipidol. 2019;13 5:847-53; doi: 10.1016/j.jacl.2019.07.008. Han Y, Ren L, Fei X, Wang J, Chen T, Guo J, et al. Effect of moderate-intensity statin on carotid intraplaque neovascularization of coronary artery disease: a retrospective cohort study. Quant Imaging Med Surg. 2024;14 2:1660-72; doi: 10.21037/qims-23-1104. Huang Y, Sun X, Ding X, Tan S, Yu Z, Shi X, et al. Pathological Intraplaque Hemorrhage as the Gold Standard to Assess the Efficacy of Ultrasound in Predicting Vulnerable Carotid Plaque Rupture. J Ultrasound Med. 2024;43 10:1869-81; doi: 10.1002/jum.16518. Boswell-Patterson CA, Hétu MF, Kearney A, Pang SC, Tse MY, Herr JE, et al. Vascularized Carotid Atherosclerotic Plaque Models for the Validation of Novel Methods of Quantifying Intraplaque Neovascularization. J Am Soc Echocardiogr. 2021;34 11:1184-94; doi: 10.1016/j.echo.2021.06.003. Cao J, Zeng Y, Zhou Y, Yao Z, Tan Z, Huo G, et al. The value of contrast-enhanced ultrasound in assessing carotid plaque vulnerability and predicting stroke risk. Sci Rep. 2025;15 1:5850; doi: 10.1038/s41598-025-90319-2. Tian M, Mohamad N, Gao XZ, Mohd Taib NH. Quantitative characterisation of carotid atherosclerotic plaque neovascularisation using contrast-enhanced ultrasound imaging: A feasibility study. Med J Malaysia. 2025;80 1:88-95. Zhang S, Jiang S, Wang C, Han C. Comparison of ultrasonic shear wave elastography, AngioPLUS planewave ultrasensitive imaging, and optimized high-resolution magnetic resonance imaging in evaluating carotid plaque stability. PeerJ. 2023;11:e16150; doi: 10.7717/peerj.16150. Zamani M, Skagen K, Scott H, Lindberg B, Russell D, Skjelland M. Carotid Plaque Neovascularization Detected With Superb Microvascular Imaging Ultrasound Without Using Contrast Media. Stroke. 2019;50 11:3121-7; doi: 10.1161/strokeaha.119.025496. Chambara N, Liu SYW, Lo X, Ying M. Diagnostic Value of AngioPLUS Microvascular Imaging in Thyroid Nodule Diagnosis Using Quantitative and Qualitative Vascularity Grading. Biomedicines. 2022;10 7; doi: 10.3390/biomedicines10071554. Zhang L, Wu R, Chen J, Gu S, Jia C. The role of intraplaque neovascularization in recent and future ischemic stroke in patients with mild carotid stenosis. Ultrasonography. 2025;44 1:62-71; doi: 10.14366/usg.24123. Camps-Renom P, Prats-Sánchez L, Casoni F, González-de-Echávarri JM, Marrero-González P, Castrillón I, et al. Plaque neovascularization detected with contrast-enhanced ultrasound predicts ischaemic stroke recurrence in patients with carotid atherosclerosis. Eur J Neurol. 2020;27 5:809-16; doi: 10.1111/ene.14157. Cramer JA, Roy A, Burrell A, Fairchild CJ, Fuldeore MJ, Ollendorf DA, et al. Medication compliance and persistence: terminology and definitions. Value Health. 2008;11 1:44-7; doi: 10.1111/j.1524-4733.2007.00213.x. Chen J, Liu D, Wang J, Song W, Ma F. Clinical application of super sensitive microflow ultrasound on the detection of intraplaque neovascularization in patients with atheromatous carotid artery plaque. Clin Hemorheol Microcirc. 2022;82 3:283-93; doi: 10.3233/ch-221510. Jin X, Yang X, Li F. Prediction of ischemic stroke in elderly hypertensive patients using carotid plaque superb microvascular imaging characteristics: a lasso-logistic regression model. J Med Ultrason (2001). 2025;52 2:227-35; doi: 10.1007/s10396-024-01513-0. Cheng L, Zheng S, Zhang J, Wang F, Liu X, Zhang L, et al. Multimodal ultrasound-based carotid plaque risk biomarkers predict poor functional outcome in patients with ischemic stroke or TIA. BMC Neurol. 2023;23 1:13; doi: 10.1186/s12883-023-03052-6. Cui L, Liu R, Zhou F, Tian B, Chen Y, Xing Y. Incremental clinical value of intraplaque neovascularization in predicting recurrent ischemic stroke. Ann Clin Transl Neurol. 2025;12 2:291-9; doi: 10.1002/acn3.52255. Mantella LE, Colledanchise KN, Hétu MF, Feinstein SB, Abunassar J, Johri AM. Carotid intraplaque neovascularization predicts coronary artery disease and cardiovascular events. Eur Heart J Cardiovasc Imaging. 2019;20 11:1239-47; doi: 10.1093/ehjci/jez070. Zhang L, Jia C, Gu S, Chen J, Wu R. Intraplaque neovascularization combined with plaque elasticity for predicting ipsilateral stroke in patients with asymptomatic mild carotid stenosis. Quant Imaging Med Surg. 2024;14 7:4815-24; doi: 10.21037/qims-24-202. Liu Z, Zhang L, Sun B, Ding Y. Association of cardiovascular risk factors and intraplaque neovascularization in symptomatic carotid plaque. Front Neurol. 2024;15:1442656; doi: 10.3389/fneur.2024.1442656. Wang Y, Yao M, Zou M, Ge Z, Cai S, Hong Y, et al. Relationship Between Serum Lipid Profiles and Carotid Intraplaque Neovascularization in a High-Stroke-Risk Population: A Cross-Sectional Study in China. J Am Heart Assoc. 2021;10 22:e021545; doi: 10.1161/jaha.121.021545. Wang B, Dong L, Qi Z. Carotid Plaque Vulnerability Assessed by Contrast-Enhanced Ultrasound and Clinical Risk Factors. J Stroke Cerebrovasc Dis. 2022;31 8:106598; doi: 10.1016/j.jstrokecerebrovasdis.2022.106598. Zhang D, Zhang R, Wang N, Lin L, Yu B. Correlation of Serum Uric Acid Levels with Nonculprit Plaque Instability in Patients with Acute Coronary Syndromes: A 3-Vessel Optical Coherence Tomography Study. Biomed Res Int. 2018;2018:7919165; doi: 10.1155/2018/7919165. Lyu Q, Liu Z, Zhu Z, Yin M. Neutrophil-to-lymphocyte ratio is associated with carotid intraplaque neovascularization in asymptomatic carotid stenosis patients. J Clin Ultrasound. 2022;50 3:319-25; doi: 10.1002/jcu.23132. Song Y, Dang Y, Feng J, Ruan LT. Remnant Cholesterol and Carotid Intraplaque Neovascularization Assessed by Contrast-Enhanced Ultrasonography in Patients With Ischemic Stroke. Cardiol Res. 2024;15 3:144-52; doi: 10.14740/cr1634. Xia S, Qiu W, Cai A, Kong B, Xu L, Wu Z, et al. The association of lipoprotein(a) and intraplaque neovascularization in patients with carotid stenosis: a retrospective study. BMC Cardiovasc Disord. 2021;21 1:285; doi: 10.1186/s12872-021-02038-x. Tan Y, Nie F, Wu G, Guo F, Wang Y, Wang L. Impact of H-Type Hypertension on Intraplaque Neovascularization Assessed by Contrast-Enhanced Ultrasound. J Atheroscler Thromb. 2022;29 4:492-501; doi: 10.5551/jat.61275. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8197849","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":555519861,"identity":"11489dc8-ec6b-467e-aa39-8631970156a0","order_by":0,"name":"Hao Zhang","email":"","orcid":"","institution":"Hefei Hospital Affiliated to Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hao","middleName":"","lastName":"Zhang","suffix":""},{"id":555519862,"identity":"fbde02d6-5e44-480a-9a8e-2198886e50f9","order_by":1,"name":"Jun He","email":"","orcid":"","institution":"Hefei Hospital Affiliated to Anhui Medical 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15:35:57","extension":"xml","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":70818,"visible":true,"origin":"","legend":"","description":"","filename":"f85dd4e6a7d248839fe42c4e4a9b2aa01structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8197849/v1/aeaaa25c2562140bba5ddb9a.xml"},{"id":97745340,"identity":"63337c4a-7eb4-47b4-9bca-36d115a969be","added_by":"auto","created_at":"2025-12-09 00:24:21","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":79895,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8197849/v1/18596db80e255fa0f4cf54a7.html"},{"id":97745326,"identity":"ca32be31-7aa1-448f-ad55-d8d933bf0615","added_by":"auto","created_at":"2025-12-09 00:24:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":322450,"visible":true,"origin":"","legend":"\u003cp\u003eIPN Grading: Panel A shows a grade 0 IPN score; Panel B represents a grade 1 score; Panel C corresponds to a grade 2 score. The left side of each panel displays the two-dimensional B-mode ultrasound image, while the right side shows the corresponding AngioPLUS imaging depicting microvascular flow signals.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8197849/v1/d60ea35e9d72de071b9b3224.png"},{"id":97894910,"identity":"7d268ba9-1a52-46b4-8a03-78ac12b20128","added_by":"auto","created_at":"2025-12-10 15:33:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":226424,"visible":true,"origin":"","legend":"\u003cp\u003eStudy flowchart.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8197849/v1/2b66b8f746af29ca0c1509f0.png"},{"id":97745328,"identity":"9bc370c7-6ec7-4d17-879c-32a6183cf0fa","added_by":"auto","created_at":"2025-12-09 00:24:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":37517,"visible":true,"origin":"","legend":"\u003cp\u003eModel 1 was defined as the traditional prediction model including age, hypertension, diabetes mellitus, medication adherence, and LDL-C.\u003c/p\u003e\n\u003cp\u003eModel 2 incorporated IPN into the traditional model. tdAUROC denotes the time-dependent area under the receiver operating characteristic curve.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8197849/v1/044db08ee8666751bcb69ae3.png"},{"id":103508088,"identity":"444a4949-6bed-4958-8ad5-08848d595117","added_by":"auto","created_at":"2026-02-26 13:47:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1469283,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8197849/v1/5aa9c07e-ae1c-4e2f-aa0e-27a1058c4d3a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Carotid Intraplaque Neovascularization Increases the Risk of Recurrent Anterior Circulation Ischemic Stroke: A Prospective Cohort Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe carotid artery serves as a critical \u0026ldquo;window\u0026rdquo; into systemic arterial health, and the pathological characteristics of carotid plaque\u0026mdash;particularly plaque vulnerability\u0026mdash;have become a major focus in understanding the pathogenesis of ischemic stroke[1]. However, whether all carotid plaques warrant statin therapy remains controversial[2\u0026ndash;4]. Compared with stable plaques, vulnerable plaques confer a substantially higher risk of causing ischemic stroke. Among the key features associated with plaque vulnerability, intraplaque neovascularization (IPN) has emerged as a pivotal area of research. Carotid IPN contributes to an increased risk of intraplaque hemorrhage, which may promote plaque rupture or embolization. Moreover, IPN is implicated in the progression of carotid atherosclerosis, potentially exacerbating vascular stenosis and ultimately leading to vessel occlusion[5, 6].\u003c/p\u003e\u003cp\u003eRecent years have witnessed accumulating evidence indicating that the distribution characteristics and severity of carotid intraplaque neovascularization (IPN), as assessed by contrast-enhanced ultrasonography (CEUS), are closely associated with the occurrence of ischemic stroke[7]. It has been hypothesized that carotid IPN may increase the risk of recurrent anterior circulation ischemic stroke (ACIS). However, the widespread clinical adoption of CEUS is limited by its relatively high cost, invasive nature, requirement for specialized operator expertise, and potential risk of contrast agent allergy[8]. AngioPLUS technology, a novel microvascular Doppler ultrasonography, offers higher resolution and is capable of detecting minute vessels and low-velocity blood flow signals[9, 10]. Subsequent semi-quantitative grading of IPN using this technology facilitates the assessment of plaque vulnerability[11]. Studies have established carotid IPN as an independent risk factor for ischemic stroke[12, 13]. Nevertheless, it remains unclear whether the evaluation of carotid IPN provides incremental clinical value beyond conventional cerebrovascular risk factors in stratifying the risk of ischemic stroke recurrence.\u003c/p\u003e\u003cp\u003eThis study aimed to investigate the association between carotid IPN, as detected by AngioPLUS technology, and the risk of recurrent anterior circulation ischemic stroke, and to determine whether integrating IPN assessment with conventional cerebrovascular risk factors improves the predictive capability for stroke recurrence.\u003c/p\u003e"},{"header":"Patients and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy population\u003c/h2\u003e\u003cp\u003eBetween August 2020 and February 2025, 170 patients with ACIS and carotid atherosclerotic plaques were enrolled at Hefei Second People's Hospital. The study protocol was approved by the local ethics committee. Written informed consent was obtained from all participating patients or their legal guardians. Inclusion criteria were as follows: (1) diagnosis of ischemic stroke with the presence of at least one carotid atherosclerotic plaque (thickness\u0026thinsp;\u0026gt;\u0026thinsp;1.5 mm) ipsilateral to the side of ischemic stroke. Exclusion criteria were as follows: (1) significant plaque calcification on carotid ultrasound that substantially interfered with the assessment of intraplaque neovascularization (IPN); (2) complete carotid artery occlusion, or history of carotid endarterectomy or carotid artery stenting; (3) stroke subtypes including cardioembolism, small vessel occlusion, stroke of other determined etiology, or stroke of undetermined etiology; (4) isolated posterior circulation infarction; (5) concomitant intracerebral hemorrhage or large-area infarction; (6) severe cardiopulmonary dysfunction, hepatic or renal failure, or malignancy; (7) concurrent infection or autoimmune disease; and (8) incomplete clinical or radiological data.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eCollection of Clinical Data\u003c/h3\u003e\n\u003cp\u003eComprehensive clinical data were collected for all enrolled patients, including demographic characteristics (e.g., sex, age), personal histories (e.g., smoking, alcohol consumption), and cerebrovascular risk factors (e.g., hypertension, diabetes mellitus, hyperlipidemia). Past medical histories, including coronary heart disease, prior ischemic stroke, and medication use (e.g., anticoagulants, lipid-lowering agents, hypoglycemic drugs, and antihypertensive agents), were also recorded. Blood pressure (systolic and diastolic) was documented upon admission. Medication adherence was evaluated based on whether patients took their prescribed oral medications (including antiplatelet agents, hypoglycemic drugs, antihypertensives, and lipid-lowering agents) as directed at discharge. For any medication discontinuation, the reasons were ascertained. Patients who discontinued medication for more than one month were classified as having poor medication adherence[14].\u003c/p\u003e\n\u003ch3\u003eLaboratory Parameters\u003c/h3\u003e\n\u003cp\u003eBlood samples were collected from all participants in the early morning following an overnight fast. These samples underwent routine blood testing, biochemical analysis, and coagulation parameter assessment. Complete blood counts were performed using the Sysmex XN-10 automated hematology analyzer. Levels of fasting blood glucose (FBG), glycated hemoglobin (HbA1c), triglycerides (TG), total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), homocysteine (HCY), and creatinine (Cr) were measured using an automated biochemical analyzer (HITACHI Automatic Analyzer 7600\u0026ndash;020, Japan).\u003c/p\u003e\n\u003ch3\u003eDiagnosis of Carotid Plaque and IPN Evaluation​\u003c/h3\u003e\n\u003cp\u003eConventional ultrasonography was performed along the carotid arteries in this study. Upon identification of a carotid plaque, AngioPLUS imaging was conducted using a French Sonic SuperSonic Imagine AixPlorer ultrasound system (Sonic Red series, equipped with AP ultrasound imaging technology and an SL10-2 transducer) to detect and evaluate intraplaque neovascularization (IPN) within the target plaque. In cases with multiple plaques, the thickest plaque on one side was selected as the target for analysis.\u003c/p\u003e\u003cp\u003eIPN grading was determined as follows[10, 15]: under AngioPLUS mode, IPN was identified by the presence of short-linear or strip-like high-signal echoes observed within a 2-minute dynamic clip. The IPN score was assigned based on the following criteria: score 0, no detectable flow signals within the plaque; score 1, a few punctate or short-linear flow signals (\u0026lt;\u0026thinsp;4 signals) located unilaterally within the plaque; score 2, dendritic or diffuse linear flow signals within the plaque. For clinical interpretation, IPN scores were categorized into low IPN (scores 0\u0026ndash;1) and high IPN (score 2) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All examinations were independently evaluated by two trained sonographers using a double-blind method. In cases of disagreement, a third senior sonologist was consulted to reach consensus. Sonographers were blinded to all patient laboratory data.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIPN Grading: Panel A shows a grade 0 IPN score; Panel B represents a grade 1 score; Panel C corresponds to a grade 2 score. The left side of each panel displays the two-dimensional B-mode ultrasound image, while the right side shows the corresponding AngioPLUS imaging depicting microvascular flow signals.\u003c/p\u003e\n\u003ch3\u003eFollow-up and Endpoints​\u003c/h3\u003e\n\u003cp\u003ePatients enrolled with acute anterior circulation ischemic stroke (ACIS) were scheduled for follow-up assessments every six months via telephone interviews or outpatient clinic visits. Those who developed any suspected stroke symptoms were promptly hospitalized and underwent diffusion-weighted imaging magnetic resonance imaging (DWI-MRI) to confirm the occurrence of recurrent acute ischemic stroke. The primary outcome was the incidence of DWI-confirmed ipsilateral ACIS recurrence. The follow-up endpoint was set at August 30, 2025.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis​\u003c/h2\u003e\u003cp\u003eStatistical analyses were performed using R software, version 4.5.0 (R Foundation for Statistical Computing, Vienna, Austria). A two-sided p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Continuous variables with normal distribution are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, while non-normally distributed variables are expressed as median (interquartile range). Group comparisons for normally distributed continuous variables were performed using the Student\u0026rsquo;s t-test, and the Wilcoxon rank-sum test was used for non-normally distributed variables. Categorical variables are summarized as frequencies (percentages) and compared using the chi-square test. Variables showing a statistically significant association (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in univariate Cox proportional hazards regression models were included in a multivariate Cox model to evaluate the independent association between IPN and the risk of recurrent anterior circulation ischemic stroke. To assess the predictive value of IPN for ipsilateral recurrent stroke, time-dependent receiver operating characteristic (ROC) curve analysis was conducted. The areas under the curve (AUC) for a model incorporating IPN and a conventional model without IPN were calculated and compared to evaluate incremental predictive performance.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eStudy Population and Baseline Clinical Characteristics\u003c/h2\u003e\u003cp\u003eA total of 170 patients with symptomatic carotid artery stenosis were initially enrolled. However, 27 patients were excluded for the following reasons: seven due to poor-quality ultrasonographic images; eight with isolated posterior circulation infarction; two with cardioembolic embolism; two with malignancy; two with Moyamoya disease; and six with incomplete clinical or radiological data (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Consequently, 143 patients (93 men and 50 women; mean age, 67.6\u0026thinsp;\u0026plusmn;\u0026thinsp;11.7 years) who met the inclusion criteria were included in the final analysis. The follow-up duration ranged from 6 to 56 months, with a mean of 21 months. During follow-up, recurrent ischemic stroke occurred in 26 patients (5 with IPN grade 1 and 21 with IPN grade 2).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003ePatient Baseline Characteristics\u003c/h2\u003e\u003cp\u003ePatients were classified into \"recurrent\" (n\u0026thinsp;=\u0026thinsp;26) and \"non-recurrent\" (n\u0026thinsp;=\u0026thinsp;117) groups according to the occurrence of recurrent ischemic stroke. Baseline characteristics are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. No statistically significant differences were observed in demographic parameters between the two groups. However, fasting blood glucose (P\u0026thinsp;=\u0026thinsp;0.012), homocysteine levels (P\u0026thinsp;=\u0026thinsp;0.018), and the proportion of patients with IPN grade 2 (P\u0026thinsp;=\u0026thinsp;0.002) were significantly higher in the recurrence group compared to the non-recurrence group.\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\u003eBaseline characteristics of patients (N\u0026thinsp;=\u0026thinsp;143).\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=\"char\" char=\".\" 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-recurrent(n\u0026nbsp;=117 )\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRecurrent(n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, year, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e67.35\u0026thinsp;\u0026plusmn;\u0026thinsp;12.166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68.54\u0026thinsp;\u0026plusmn;\u0026thinsp;9.791\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.537\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex, man,\u0026nbsp;n\u0026nbsp;(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e74(63.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18(69.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.565\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e56(47.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14(53.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.581\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27(23.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10(38.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.105\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHyperlipidemia, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e31(26.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5(19.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.440\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecoronary heart disease, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16(13.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4(15.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.820\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHistory of stroke,n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28(23.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9(34.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.261\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39(33.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10(38.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.618\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrinking, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33(28.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8(30.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.794\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoor medication adherence, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22(18.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8(30.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.175\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.721\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25.13\u0026thinsp;\u0026plusmn;\u0026thinsp;2.283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.099\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTG, median (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.44(1.02, 2.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.42(0.85, 4.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.628\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTC, median (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.41(3.71, 5.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.45(4.01, 5.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.593\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHDL-C, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.278\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.266\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.902\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDL-C, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.820\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.639\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.192\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFBG, median (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.28(4.84, 7.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.44(5.43, 9.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHCY, median (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.00(10.20, 16.85)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.00(12.02, 20.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCr, median (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68(56.00, 81.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e67.50(55.25, 83.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.969\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThrombolysis, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12(10.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4(15.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.453\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIPN, n (%)\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=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGrades 0 and 1, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e78(94.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5(6.0)\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\u003eGrades 2, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39(33.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21(80.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: BMI, body mass index; TG, triglycerides; TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; FBG, fasting blood glucose; HCY, homocysteine; Cr, creatinine; IQR, interquartile range; IPN, intraplaque neovascularization.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eAssociation Between IPN Grading and the Risk of Recurrent Acute Ischemic Stroke\u003c/h2\u003e\u003cp\u003eUnivariate Cox regression analysis identified the following factors as significantly associated with recurrent ischemic stroke: diabetes mellitus (HR 3.274, 95% CI 1.466\u0026ndash;7.312, P\u0026thinsp;=\u0026thinsp;0.004), poor medication adherence (HR 2.399, 95% CI 1.034\u0026ndash;5.567, P\u0026thinsp;=\u0026thinsp;0.042), elevated low-density lipoprotein cholesterol (LDL-C) levels (HR 2.195, 95% CI 1.375\u0026ndash;3.504, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and presence of grade 2 intraplaque neovascularization (IPN) (HR 4.936, 95% CI 1.859\u0026ndash;13.105, P\u0026thinsp;=\u0026thinsp;0.001). Variables with P\u0026thinsp;\u0026le;\u0026thinsp;0.05 in univariate analysis\u0026mdash;diabetes mellitus, poor medication adherence, elevated LDL-C, and grade 2 IPN\u0026mdash;were included as covariates in a multivariate Cox regression model. Multivariate analysis confirmed that grade 2 IPN was an independent predictor of recurrent ischemic stroke (HR 6.936, 95% CI 2.464\u0026ndash;19.524, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\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\u003ePredictive factors for future ischemic stroke\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eUnivariable analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003eMultivariable analysis\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHR\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\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e95%CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\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\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.975\u0026thinsp;~\u0026thinsp;1.043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.613\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.293\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.562\u0026thinsp;~\u0026thinsp;2.975\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.546\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\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=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.408\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.651\u0026thinsp;~\u0026thinsp;3.046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.385\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\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=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.274\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.466\u0026thinsp;~\u0026thinsp;7.312\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.253\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.967\u0026thinsp;~\u0026thinsp;5.247\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.060\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=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.149\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.430\u0026thinsp;~\u0026thinsp;3.071\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.782\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ecoronary heart disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.589\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.547\u0026thinsp;~\u0026thinsp;4.620\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.395\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHistory of stroke\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.381\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.615\u0026thinsp;~\u0026thinsp;3.100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.434\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.386\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.628\u0026thinsp;~\u0026thinsp;3.060\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.419\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.256\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.545\u0026thinsp;~\u0026thinsp;2.898\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.592\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoor medication adherence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.399\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.034\u0026thinsp;~\u0026thinsp;5.567\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.385\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.319\u0026thinsp;~\u0026thinsp;8.685\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.149\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.968\u0026thinsp;~\u0026thinsp;1.364\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSBP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.991\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.975\u0026thinsp;~\u0026thinsp;1.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.287\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDBP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.977\u0026thinsp;~\u0026thinsp;1.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.932\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.926\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.622\u0026thinsp;~\u0026thinsp;1.376\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.702\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.763\u0026thinsp;~\u0026thinsp;1.750\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.495\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHDL-C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.752\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.167\u0026thinsp;~\u0026thinsp;3.389\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.711\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDL-C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.195\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" 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colname=\"c4\"\u003e\u003cp\u003e0.059\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHCY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.030\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.991\u0026thinsp;~\u0026thinsp;1.070\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCr\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.985\u0026thinsp;~\u0026thinsp;1.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.719\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCarotid IPN (grade 2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.936\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.859\u0026thinsp;~\u0026thinsp;13.105\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.936\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.464\u0026thinsp;~\u0026thinsp;19.524\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003eNote:​BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; TG, triglycerides; TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; FBG, fasting blood glucose; HCY, homocysteine; Cr, creatinine; IPN, intraplaque neovascularization.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003ePredictive Value of IPN Grading for Stroke Recurrence Risk\u003c/h2\u003e\u003cp\u003eOver time, Model 2 demonstrated greater areas under the receiver operating characteristic (ROC) curves than Model 1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). At 12 months, the area under the curve (AUC) for Model 2 was 0.855 (95% CI, 0.735\u0026ndash;0.974), compared with 0.847 (95% CI, 0.750\u0026ndash;0.943) for Model 1 (P\u0026thinsp;=\u0026thinsp;0.901). At 24 months, the AUC for Model 2 was significantly higher than that for Model 1 (0.853 [95% CI, 0.765\u0026ndash;0.941] vs. 0.749 [95% CI, 0.631\u0026ndash;0.867], P\u0026thinsp;=\u0026thinsp;0.040). This significant advantage of Model 2 persisted at 36 months (AUC 0.877 [95% CI, 0.793\u0026ndash;0.961] vs. 0.756 [95% CI, 0.636\u0026ndash;0.876], P\u0026thinsp;=\u0026thinsp;0.016) and at 48 months (AUC 0.866 [95% CI, 0.759\u0026ndash;0.973] vs. 0.733 [95% CI, 0.578\u0026ndash;0.887], P\u0026thinsp;=\u0026thinsp;0.035). Time-dependent ROC curve analysis indicated that incorporating IPN assessment into Model 1\u0026mdash;which initially included only traditional risk factors (age, hypertension, diabetes, and LDL-C)\u0026mdash;resulted in Model 2, which exhibited significantly improved predictive performance for recurrent anterior circulation ischemic stroke at 24, 36, and 48 months (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Therefore, IPN serves as a robust predictor of ischemic stroke recurrence. Targeted therapeutic interventions addressing IPN may potentially reduce recurrence risk in patients with ACIS.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eModel 1 was defined as the traditional prediction model including age, hypertension, diabetes mellitus, medication adherence, and LDL-C.\u003c/p\u003e\u003cp\u003eModel 2 incorporated IPN into the traditional model. tdAUROC denotes the time-dependent area under the receiver operating characteristic curve.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study demonstrated that carotid intraplaque neovascularization (IPN), as assessed by AngioPLUS technology, remains an independent risk factor for recurrent anterior circulation ischemic stroke, even after adjusting for conventional cerebrovascular risk factors. Incorporating IPN evaluation with traditional risk factors enhances the ability to predict stroke recurrence, thereby assisting clinicians in identifying patients at high risk for recurrent ischemic events.\u003c/p\u003e\u003cp\u003eCarotid atherosclerotic plaque is a major etiological contributor to ischemic stroke, with approximately 20% of cases attributed to embolism following plaque rupture. Assessment of plaque stability is therefore critical for the prevention of ischemic stroke. Intraplaque neovascularization (IPN) has emerged as a key indicator of plaque vulnerability and is strongly associated with an increased risk of both incident and recurrent ischemic stroke[7, 12, 16]. Consequently, IPN grading holds significant predictive value for stroke risk stratification.\u003c/p\u003e\u003cp\u003eThis study demonstrated that carotid intraplaque neovascularization (IPN) is significantly associated with the risk of recurrent ipsilateral acute cerebral infarction (ACIS). This association remained statistically robust after adjustment for potential confounding factors. Moreover, the integration of carotid IPN grading into a prediction model based on conventional cerebrovascular risk factors substantially improved the model\u0026rsquo;s ability to predict recurrent ACIS. These findings suggest that carotid IPN may serve as a novel biomarker for predicting stroke recurrence and represent a potential therapeutic target for preventing recurrent ischemic events.\u003c/p\u003e\u003cp\u003eIPN grading exhibits considerable predictive utility in stroke risk assessment. Cheng et al. reported that intraplaque neovascularization (IPN) was independently associated with adverse outcomes at 90 days in patients with ischemic stroke[17]. A prospective study of 155 ischemic stroke patients followed over 24 months found that grade 2 IPN was independently correlated with stroke recurrence. Similarly, Huang et al. showed that carotid IPN detected by contrast-enhanced ultrasonography (CEUS) was independently associated with ischemic stroke recurrence[18]. Zhang et al. further demonstrated that in patients with mild carotid stenosis, the presence of carotid IPN independently predicted future ischemic events in both symptomatic and asymptomatic individuals[12]. Consistent with these findings, the present study confirmed that carotid IPN remained independently associated with ACIS recurrence after adjusting for confounders including diabetes history, medication adherence, and low-density lipoprotein levels. Cui et al. suggested that combining IPN assessment with a baseline model\u0026mdash;including hypoechoic plaque, smoking, and elevated homocysteine levels\u0026mdash;improved the identification of patients at high risk for ischemic stroke recurrence compared to the baseline model alone[18]. The current study further revealed that incorporating carotid IPN grading into traditional cerebrovascular risk factor models significantly enhanced predictive performance for recurrent ACIS. These results highlight the potential of IPN grading to refine existing stroke risk stratification systems, supporting the clinical applicability of a combined prediction model for assessing stroke recurrence risk. Atherosclerosis is a systemic disease process, and contemporary research frequently employs carotid IPN as a surrogate marker for cerebrovascular event prediction[19, 20]. Future studies should evaluate IPN grading across multiple vascular territories to enable a more comprehensive assessment of stroke risk and recurrence.\u003c/p\u003e\u003cp\u003eThe formation of intraplaque neovascularization (IPN) is regulated by multiple interacting factors, including dysregulation of glucose and lipid metabolism, inflammatory responses, and other extrinsic elements. These factors act through complex pathophysiological mechanisms to promote IPN development, thereby influencing plaque stability. Dysregulation of glucose and lipid metabolism represents a significant contributor to IPN formation. A study of 157 patients with acute cerebral ischemic stroke (ACIS) and carotid artery stenosis showed that the risk of developing IPN grade 3\u0026ndash;4 was 5.55-fold higher in patients with blood glucose levels\u0026thinsp;\u0026gt;\u0026thinsp;13.35 mmol/L compared to those with levels\u0026thinsp;\u0026lt;\u0026thinsp;6.20 mmol/L[21]. Abnormal lipid metabolism is also closely associated with IPN. A cross-sectional study of 250 high-stroke-risk patients undergoing superb microvascular imaging for carotid IPN detection demonstrated that the IPN-positive group had significantly higher levels of total cholesterol, low-density lipoprotein cholesterol (LDL-C), and non-high-density lipoprotein cholesterol (non-HDL-C) than the IPN-negative group[22]. Furthermore, a study of 244 patients with carotid plaques assessed by contrast-enhanced ultrasonography revealed that obesity indicators\u0026mdash;including body mass index, upper arm circumference, and waist-to-height ratio\u0026mdash;were positively correlated with IPN grade, potentially mediated by metabolic disturbances and adipose tissue-induced inflammatory responses [21, 23]. Additionally, clinical evidence suggests that elevated serum uric acid and homocysteine levels may promote IPN formation, whereas bilirubin may exert an inhibitory effect[24]. Inflammatory response is a key driver of IPN progression. In a study of 144 patients with asymptomatic carotid artery stenosis evaluated by contrast-enhanced ultrasonography, individuals in the highest quartile of neutrophil-to-lymphocyte ratio (NLR) had a 4.55-fold increased risk of IPN grade 2 compared to those in the lowest quartile[25]. Another study involving 244 patients with carotid plaques found significantly higher D-dimer levels in the vulnerable plaque group (IPN grade 3\u0026ndash;4) than in the stable plaque group, indicating a strong association between activation of the fibrinolytic system and plaque instability[21, 23]. Future research should focus on identifying additional risk factors and elucidating the underlying molecular mechanisms of IPN formation to identify potential therapeutic targets for inhibiting pathological neovascularization [22, 26\u0026ndash;28].\u003c/p\u003e\u003cp\u003eThis study has several limitations. First, the relatively long follow-up period and limited sample size warrant validation through future multicenter studies with larger cohorts. Second, documentation and follow-up regarding post-discharge medication adherence were insufficiently detailed; only medication discontinuation status was recorded. Incorporating specific types of medication discontinuation into the predictive model could enhance the comprehensiveness of the analysis. Third, as a single-center study, over 90% of participants were recruited from the Hefei region, which may introduce selection bias.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, IPN serves as an independent risk factor for stroke recurrence in patients with ACIS. Moreover, integrating IPN assessment into risk prediction models significantly improves the accuracy of conventional cerebrovascular risk factors in identifying patients at high risk of recurrent ischemic stroke.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board of the Second People\u0026apos;s Hospital of Hefei (Hefei Hospital Affiliated to Anhui Medical University). The study was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was obtained from all participating patients or their legal guardians.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated during this study are included in the published article. The datasets analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding: \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHefei Municipal Health Commission Applied Medical Research Project (No. Hwk2022zd004)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eScientific Research Foundation of Anhui Medical University (No. 2023xkj231) \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNatural Science Key Project of Bengbu Medical University (No. 2024byzd423)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eS.C. and H.Z. contributed to study design, data collection, statistical analysis, and manuscript writing. J.H. and R.W. were responsible for clinical and laboratory data collection. H.Z., J.X., and S.C. collected and analyzed ultrasound data. H.Z. prepared the figures. S.C. and M.X. participated in data interpretation and critical revision of the manuscript. All authors read and approved the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDing S, Zhang M, Zhao Y, Chen W, Yao G, Zhang C, et al. The role of carotid plaque vulnerability and inflammation in the pathogenesis of acute ischemic stroke. Am J Med Sci. 2008;336 1:27-31; doi: 10.1097/MAJ.0b013e31815b60a1.\u003c/li\u003e\n\u003cli\u003eKoole D, Heyligers J, Moll FL, Pasterkamp G. Intraplaque neovascularization and hemorrhage: markers for cardiovascular risk stratification and therapeutic monitoring. J Cardiovasc Med (Hagerstown). 2012;13 10:635-9; doi: 10.2459/JCM.0b013e3283590cd2.\u003c/li\u003e\n\u003cli\u003eDu R, Cai J, Cui B, Wu H, Zhao XQ, Ye P. Rapid improvement in carotid adventitial angiogenesis and plaque neovascularization after rosuvastatin therapy in statin treatment-na\u0026iuml;ve subjects. J Clin Lipidol. 2019;13 5:847-53; doi: 10.1016/j.jacl.2019.07.008.\u003c/li\u003e\n\u003cli\u003eHan Y, Ren L, Fei X, Wang J, Chen T, Guo J, et al. Effect of moderate-intensity statin on carotid intraplaque neovascularization of coronary artery disease: a retrospective cohort study. Quant Imaging Med Surg. 2024;14 2:1660-72; doi: 10.21037/qims-23-1104.\u003c/li\u003e\n\u003cli\u003eHuang Y, Sun X, Ding X, Tan S, Yu Z, Shi X, et al. Pathological Intraplaque Hemorrhage as the Gold Standard to Assess the Efficacy of Ultrasound in Predicting Vulnerable Carotid Plaque Rupture. J Ultrasound Med. 2024;43 10:1869-81; doi: 10.1002/jum.16518.\u003c/li\u003e\n\u003cli\u003eBoswell-Patterson CA, H\u0026eacute;tu MF, Kearney A, Pang SC, Tse MY, Herr JE, et al. Vascularized Carotid Atherosclerotic Plaque Models for the Validation of Novel Methods of Quantifying Intraplaque Neovascularization. J Am Soc Echocardiogr. 2021;34 11:1184-94; doi: 10.1016/j.echo.2021.06.003.\u003c/li\u003e\n\u003cli\u003eCao J, Zeng Y, Zhou Y, Yao Z, Tan Z, Huo G, et al. The value of contrast-enhanced ultrasound in assessing carotid plaque vulnerability and predicting stroke risk. Sci Rep. 2025;15 1:5850; doi: 10.1038/s41598-025-90319-2.\u003c/li\u003e\n\u003cli\u003eTian M, Mohamad N, Gao XZ, Mohd Taib NH. Quantitative characterisation of carotid atherosclerotic plaque neovascularisation using contrast-enhanced ultrasound imaging: A feasibility study. Med J Malaysia. 2025;80 1:88-95.\u003c/li\u003e\n\u003cli\u003eZhang S, Jiang S, Wang C, Han C. Comparison of ultrasonic shear wave elastography, AngioPLUS planewave ultrasensitive imaging, and optimized high-resolution magnetic resonance imaging in evaluating carotid plaque stability. PeerJ. 2023;11:e16150; doi: 10.7717/peerj.16150.\u003c/li\u003e\n\u003cli\u003eZamani M, Skagen K, Scott H, Lindberg B, Russell D, Skjelland M. Carotid Plaque Neovascularization Detected With Superb Microvascular Imaging Ultrasound Without Using Contrast Media. Stroke. 2019;50 11:3121-7; doi: 10.1161/strokeaha.119.025496.\u003c/li\u003e\n\u003cli\u003eChambara N, Liu SYW, Lo X, Ying M. Diagnostic Value of AngioPLUS Microvascular Imaging in Thyroid Nodule Diagnosis Using Quantitative and Qualitative Vascularity Grading. Biomedicines. 2022;10 7; doi: 10.3390/biomedicines10071554.\u003c/li\u003e\n\u003cli\u003eZhang L, Wu R, Chen J, Gu S, Jia C. The role of intraplaque neovascularization in recent and future ischemic stroke in patients with mild carotid stenosis. Ultrasonography. 2025;44 1:62-71; doi: 10.14366/usg.24123.\u003c/li\u003e\n\u003cli\u003eCamps-Renom P, Prats-S\u0026aacute;nchez L, Casoni F, Gonz\u0026aacute;lez-de-Ech\u0026aacute;varri JM, Marrero-Gonz\u0026aacute;lez P, Castrill\u0026oacute;n I, et al. Plaque neovascularization detected with contrast-enhanced ultrasound predicts ischaemic stroke recurrence in patients with carotid atherosclerosis. Eur J Neurol. 2020;27 5:809-16; doi: 10.1111/ene.14157.\u003c/li\u003e\n\u003cli\u003eCramer JA, Roy A, Burrell A, Fairchild CJ, Fuldeore MJ, Ollendorf DA, et al. Medication compliance and persistence: terminology and definitions. Value Health. 2008;11 1:44-7; doi: 10.1111/j.1524-4733.2007.00213.x.\u003c/li\u003e\n\u003cli\u003eChen J, Liu D, Wang J, Song W, Ma F. Clinical application of super sensitive microflow ultrasound on the detection of intraplaque neovascularization in patients with atheromatous carotid artery plaque. Clin Hemorheol Microcirc. 2022;82 3:283-93; doi: 10.3233/ch-221510.\u003c/li\u003e\n\u003cli\u003eJin X, Yang X, Li F. Prediction of ischemic stroke in elderly hypertensive patients using carotid plaque superb microvascular imaging characteristics: a lasso-logistic regression model. J Med Ultrason (2001). 2025;52 2:227-35; doi: 10.1007/s10396-024-01513-0.\u003c/li\u003e\n\u003cli\u003eCheng L, Zheng S, Zhang J, Wang F, Liu X, Zhang L, et al. Multimodal ultrasound-based carotid plaque risk biomarkers predict poor functional outcome in patients with ischemic stroke or TIA. BMC Neurol. 2023;23 1:13; doi: 10.1186/s12883-023-03052-6.\u003c/li\u003e\n\u003cli\u003eCui L, Liu R, Zhou F, Tian B, Chen Y, Xing Y. Incremental clinical value of intraplaque neovascularization in predicting recurrent ischemic stroke. Ann Clin Transl Neurol. 2025;12 2:291-9; doi: 10.1002/acn3.52255.\u003c/li\u003e\n\u003cli\u003eMantella LE, Colledanchise KN, H\u0026eacute;tu MF, Feinstein SB, Abunassar J, Johri AM. Carotid intraplaque neovascularization predicts coronary artery disease and cardiovascular events. Eur Heart J Cardiovasc Imaging. 2019;20 11:1239-47; doi: 10.1093/ehjci/jez070.\u003c/li\u003e\n\u003cli\u003eZhang L, Jia C, Gu S, Chen J, Wu R. Intraplaque neovascularization combined with plaque elasticity for predicting ipsilateral stroke in patients with asymptomatic mild carotid stenosis. Quant Imaging Med Surg. 2024;14 7:4815-24; doi: 10.21037/qims-24-202.\u003c/li\u003e\n\u003cli\u003eLiu Z, Zhang L, Sun B, Ding Y. Association of cardiovascular risk factors and intraplaque neovascularization in symptomatic carotid plaque. Front Neurol. 2024;15:1442656; doi: 10.3389/fneur.2024.1442656.\u003c/li\u003e\n\u003cli\u003eWang Y, Yao M, Zou M, Ge Z, Cai S, Hong Y, et al. Relationship Between Serum Lipid Profiles and Carotid Intraplaque Neovascularization in a High-Stroke-Risk Population: A Cross-Sectional Study in China. J Am Heart Assoc. 2021;10 22:e021545; doi: 10.1161/jaha.121.021545.\u003c/li\u003e\n\u003cli\u003eWang B, Dong L, Qi Z. Carotid Plaque Vulnerability Assessed by Contrast-Enhanced Ultrasound and Clinical Risk Factors. J Stroke Cerebrovasc Dis. 2022;31 8:106598; doi: 10.1016/j.jstrokecerebrovasdis.2022.106598.\u003c/li\u003e\n\u003cli\u003eZhang D, Zhang R, Wang N, Lin L, Yu B. Correlation of Serum Uric Acid Levels with Nonculprit Plaque Instability in Patients with Acute Coronary Syndromes: A 3-Vessel Optical Coherence Tomography Study. Biomed Res Int. 2018;2018:7919165; doi: 10.1155/2018/7919165.\u003c/li\u003e\n\u003cli\u003eLyu Q, Liu Z, Zhu Z, Yin M. Neutrophil-to-lymphocyte ratio is associated with carotid intraplaque neovascularization in asymptomatic carotid stenosis patients. J Clin Ultrasound. 2022;50 3:319-25; doi: 10.1002/jcu.23132.\u003c/li\u003e\n\u003cli\u003eSong Y, Dang Y, Feng J, Ruan LT. Remnant Cholesterol and Carotid Intraplaque Neovascularization Assessed by Contrast-Enhanced Ultrasonography in Patients With Ischemic Stroke. Cardiol Res. 2024;15 3:144-52; doi: 10.14740/cr1634.\u003c/li\u003e\n\u003cli\u003eXia S, Qiu W, Cai A, Kong B, Xu L, Wu Z, et al. The association of lipoprotein(a) and intraplaque neovascularization in patients with carotid stenosis: a retrospective study. BMC Cardiovasc Disord. 2021;21 1:285; doi: 10.1186/s12872-021-02038-x.\u003c/li\u003e\n\u003cli\u003eTan Y, Nie F, Wu G, Guo F, Wang Y, Wang L. Impact of H-Type Hypertension on Intraplaque Neovascularization Assessed by Contrast-Enhanced Ultrasound. J Atheroscler Thromb. 2022;29 4:492-501; doi: 10.5551/jat.61275.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Carotid plaque, Intraplaque neovascularization, Stroke recurrence","lastPublishedDoi":"10.21203/rs.3.rs-8197849/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8197849/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground and purpose\u003c/h2\u003e\u003cp\u003eThe prognostic value of intraplaque neovascularization (IPN) in carotid artery plaques for predicting recurrent anterior circulation ischemic stroke (ACIS) remains uncertain. This study aimed to evaluate whether IPN can predict recurrent stroke in patients with ACIS and to determine whether the integration of IPN with conventional risk factors enhances risk stratification.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe prospectively enrolled consecutive patients with acute cerebral infarction syndrome (ACIS) who underwent assessment of intraplaque neovascularization (IPN) using AngioPLUS, an ultrasound-based imaging modality, between August 2020 and February 2025. A Cox proportional hazards regression model was employed to identify independent predictors of recurrent ischemic stroke. The predictive performance of a novel model incorporating IPN was compared with that of a conventional model excluding IPN by calculating the time-dependent area under the receiver operating characteristic curve (AUC).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eA total of 143 patients were included in the analysis, comprising 93 men and 50 women, with a mean age of 67.6\u0026thinsp;\u0026plusmn;\u0026thinsp;11.7 years. The follow-up period ranged from 6 to 56 months, with a median duration of 21 months. Recurrent ischemic stroke occurred in 26 patients. Intergroup comparisons revealed significantly higher levels of fasting blood glucose (P\u0026thinsp;=\u0026thinsp;0.012), homocysteine (P\u0026thinsp;=\u0026thinsp;0.018), and a greater proportion of patients with grade 2 IPN (P\u0026thinsp;=\u0026thinsp;0.002) in the recurrence group compared to the non-recurrence group. Multivariate Cox regression analysis identified grade 2 IPN as an independent predictor of recurrent ischemic stroke (HR\u0026thinsp;=\u0026thinsp;6.936; 95% CI, 2.464\u0026ndash;19.524; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Time-dependent receiver operating characteristic analysis showed that adding carotid IPN to the conventional model significantly improved its predictive accuracy for recurrent ACIS at 24, 36, and 48 months (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eCarotid IPN is an independent predictor of recurrent ACIS. Incorporating IPN assessment with conventional risk factors improves the identification of high-risk patients.\u003c/p\u003e","manuscriptTitle":"Carotid Intraplaque Neovascularization Increases the Risk of Recurrent Anterior Circulation Ischemic Stroke: A Prospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-09 00:24:16","doi":"10.21203/rs.3.rs-8197849/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a050930f-de8a-4bfd-9e40-312185651459","owner":[],"postedDate":"December 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-26T03:40:15+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-09 00:24:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8197849","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8197849","identity":"rs-8197849","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}