An online dynamic nomogram for predicting the recurrence of patients with endovascular treatment of intracranial aneurysms

An online dynamic nomogram for predicting the recurrence of patients with endovascular treatment of intracranial aneurysms | 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 An online dynamic nomogram for predicting the recurrence of patients with endovascular treatment of intracranial aneurysms Chunchun Ma, Chengzhi Ni, Zejin Li, Bangyue Wang, Yuyang Wang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8306812/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 Purpose Intracranial aneurysm (IA) is a serious cerebrovascular disease with a relatively high incidence, once ruptured, it an cause severely mortality and morbidity rate. Currently, endovascular coiling has become one of the main treatment methods for IAs.The purpose of this study is to develop and validate a novel clinically assessment system dynamic nomogram based on pre- and post-operative clinical and imaging characteristics to predict IAs recurrence after patients treated with endovascular coiling. Methods This single-institution retrospective study collected 113 patients with single IA who underwent coil embolization. Patients were followed up by using digital subtraction angiography (DSA) or Computed Tomography Angiography (CTA) or Magnetic Resonance Angiography (MRA) to observe IAs recurrence in 12 months after coil embolization. The univariate and multivariate logistic regression analysis were used to select recurrence factors to generate the nomogram. The discrimination and calibration of the nomogram were assessed using concordance index (C-index), area under time-dependent receiver operating characteristic curve (ROC), and calibration curves. Decision curve analysis (DCA) was used to assess clinical utility. Result Logistic regression analysis identified age, angle inflow tract > 90℃ and postoperative Raymond grade II or III as predictors of IAs recurrence after patients treated with endovascular coiling (all P < 0.05). The area under ROC curve (AUC) of the nomogram was 0.838 suggested satisfactory discriminative ability of the nomogram. The calibration plots with a 1,000 bootstrap resampling indicated that probabilities predicted by the nomogram favorable consistency with the actual observation. The DCA showed that our model can gain a greater net benefit. Conclusion This useful technique of nomogram was developed and validated which can help physicians in predicting the recurrence of patients with endovascular coiling of IAs. Intracranial aneurysm nomogram recurrence endovascular coiling Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Intracranial aneurysms (IAs) are a cerebrovascular disease that seriously threatens human health [ 1 ]. If untreated or left to grow, they can rupture, leading to life-threatening conditions such as subarachnoid hemorrhage (SAH) or intracerebral hematoma formation, which can cause significantly devastating consequences [ 2 ]. Nowadays coil embolization (including stent-assisted coiling) is a highly safe and effective method for treatment IAs [ 3 ]. Although coil embolization has significant advantages in the treatment of intracranial aneurysms, it also has quite a few drawbacks. The most prominent one is the risk of recurrence, which can cause the aneurysm to expand again or reopen, and increases the risk of aneurysm rupture [ 4 ]. Therefore, to reduce the recurrence rate after intracranial aneurysm coiling embolization, it is crucial to identify and predict the factors that contribute to recurrence following endovascular coiling of intracranial aneurysms. In the past years, many studies have already confirmed several reasons that lead to the recurrence of IAs after coil embolization, including in the middle cerebral artery (MCA), large size(> 10mm), posterior circulation location, ruptured aneurysm, wide neck [ 5 – 9 ]. Artificial intelligence (AI) is now applied to aspects such as the calculation of morphological parameters of intracranial aneurysms, rupture risk stratification, and the prediction of aneurysm recurrence risk based on Machine Learning (ML) methods. Some studies have established multiple ML models for predicting aneurysm rupture, such as Random Forest (RF), Support Vector Machine (SVM) or Gradient Boosting Decision Tre (GBDT), based on the clinical characteristics of patients and the morphological features of aneurysms. They compared the AUC values, sensitivity, specificity and accuracy of these models with those of the classic logistic regression model. All results confirmed that the machine learning models were superior to the logistic regression model. However, there are relatively few models for predicting aneurysm recurrence [ 10 – 13 ]. The current research on the risk prediction of recurrence of intracranial aneurysms after endovascular intervention focuses on risk factor screening, and some foreign research institutions have begun to predict the risk of recurrence by establishing a logistic regression model based on screening risk factors [ 14 – 15 ]. A total of 218 patients with intracranial aneurysms who underwent interventional embolization, and the results of multivariate analysis showed that the maximum diameter of the aneurysm and posterior circulation aneurysms were risk factors for aneurysm recurrence. Stent-assisted embolization was a protective factor for aneurysm recurrence [ 16 ]. However, these studies, like other similar studies, did not simplify the logistic regression model, and the calculation of risk through mathematical formulas in clinical applications is still relatively complicated. Therefore, establishing a simple, accurate, and clinically useful dynamic nomogram for predicting the recurrence risk after intracranial aneurysm embolization that can comprehensively consider relevant risk factors is of great value for clinical decision-making and improving surgical efficacy. Materials and methods Patients’ data and characteristics We collected 113 IA patients who had undergone endovascular coiling between November 2018 and January 2024 at the Second Affiliated Hospital of Anhui Medical University (Hefei, China). The study was approved by the Ethics Committee of the Second Affiliated Hospital at Anhui Medical University (document NO: YX2025-185). This study was performed in line with the ethical standards of the Helsinki Declaration (revised by Brazil in 2013). All patients gave informed consent to enroll in the study. The inclusion criteria for patients in this study were as follows: 1. Patients who were diagnosed with IAs by CTA, MRA or DSA before surgery. 2. IAs treated with coil embolization, including simple embolization and stent-assisted embolization. 3. Complete DSA or MRA images before and after the operation, enabling morphological measurement. Patients’ exclusion criteria: 1. blister - like aneurysms and other special aneurysms; 2. Patients who underwent craniotomy, parent-artery occlusion, treatment with flow - diverting devices, or conservative management; 3. Patients who had undergone surgical clipping or endovascular embolization for aneurysms before admission and were admitted for re-operation; 4. There are no imaging follow - up data for more than 3 months after the surgery. Some variables from the clinical characteristics: including gender, age, smoking, alcohol, hypertension, diabetes, coronary heart disease (CHD). We also recorded operation-related data, such as ruptured status, aneurysm location, operation time, stent types, aneurysm size classification, operation time, Raymond-Roy occlusion classification (RROC), and aneurysm morphologies. Aneurysm location was divided into six parts, namely, internal carotid artery (ICA), anterior communicating artery (ACoA) posterior communicating artery (PCoA), anterior cerebral artery (ACA), middle cerebral artery (MCA) and posterior circulation (basilar artery, superior cerebellar artery, vertebral artery, and posterior inferior cerebellar artery). Stent types, including coil alone, braided and laser-cut type. The anatomical data of aneurysms were measured according to the results of DSA imaging. Aneurysm size classification was divided into giant aneurysms (> 25mm), large aneurysms (10-25mm), medium aneurysms (5-10mm) and small aneurysms (< 5mm) according to the longest diameter of aneurysm body. Raymond-Roy occlusion classification (RROC) was used to evaluate the immediate results of treatment by the surgeon, Grade I represent complete occlusion; Grade II represents residual neck; Grade III represents residual part of the aneurysm sac. Aneurysm morphologies parameters were measured by DSA. The morphological variables were defined as follows, Maximum diameter (MD); Neck of the aneurysm (N); Incident Angle (IA); wide-necked aneurysm or narrow-neck aneurysms; saccular or irregular shape. Imaging postoperative follow-up In clinical practice, the first follow-up is usually 6 months after surgery as an indicator of whether the aneurysm is occluded. Imaging postoperative follow-up was performed by DSA or MRA. According to the comparison with the immediate postoperative imaging results, the imaging results were divided into four types: cure, improvement, stability and recurrence. Cure, defined as no contrast agent into the aneurysm, aneurysm embolization; Improvement, defined as a reduction in the volume of contrast agent entering the aneurysm, but not complete embolization; Stable, defined as no significant change in the volume of contrast agent entering the aneurysm compared to immediately after surgery; Recurrence, defined as an increase in the volume of contrast agent entering the aneurysm compared to immediately after surgery, or significant coil compression detected. Imaging findings Angiographic findings were interpreted by at least two neuroradiologists with more than 5 years of imaging interpretation experience [ 17 ]. Statistical analysis All statistical analysis was executed by using R language (version 4.2.0, Vienna, Austria). For the measurement data conforming to the normal distribution, it is expressed as mean ± standard deviation (mean ± SD), and the inter-group difference analysis adopts two independent sample t-test. For the measurement data not conforming to the normal distribution, it is expressed as median and quartile [median (Q25, Q75)], and the inter-group comparison adopts Mann-Whitney U test. For the count data, it is expressed as number (rate), and the inter-group difference test adopts χ² test. The odds ratio (OR) and 95% confidence interval (CI) were figured. Univariate analysis was performed to determine risk factors for recurrence of patients with endovascular treatment of intracranial aneurysms. Variables with a P value less than 0.05, then entering into next step, using multivariate logistic regression analysis to determine the independent risk factors for predicting recurrence of patients with endovascular treatment of intracranial aneurysms. Although univariate analysis showed no statistically significant association between stent groups and outcomes (P > 0.05), stents may indirectly influence outcomes through several factors: preventing the migration of microcoils and improving the dense packing rate; assisting coil embolization and promoting thrombus formation; and their mesh structure can cover the aneurysm neck, reducing direct blood flow impact on the residual aneurysm neck and lowering the probability of aneurysm recurrence. Therefore, this study included it in the multivariate model to adjust for potential confounding effects and enhance the robustness of the model. According to the results of multivariate logistic regression analysis, a static and dynamic online nomogram was established with R language (version 4.2.0, Vienna, Austria). Mode performance of the nomogram was evaluated based on discrimination and calibration. The receiver operating characteristic (ROC) were used to measure model discrimination. The effectiveness of calibration was determined using a calibration plot, which indicates the correlation between predicted and actual probability using a bootstrapped sample. The decision curve analysis (DCA) was performed to evaluate the clinical applicability at each threshold probability of the nomogram. The p-value < 0.05 was considered statistically significant in all analyses. Results Patient characteristics 113 IA patients who met the inclusion criteria and conducted imaging postoperative follow‑up, were enrolled in this study, and 7 had two aneurysms which were also undergone endovascular coiling. Overall characteristics of IA patients are presented in Table 1 . The mean age of all patients was 57.53 ± 11.74 years, female was more common than men, and the average imaging postoperative follow-up was 6.46 months for all patients. Among all these IAs, ruptured aneurysms were 72 (63.7%), Obtuse angle were 78 (69%), 100(88.5%) were classified as RROC Ⅰ, 13 (11.5%) were classified as RROC Ⅱ/Ⅲ, and 42 IAs treated with stents. The overall recurrence occurred in 23% (26/113). Table 1 Baseline Information Characteristics Total(n = 113) Male 38(33.6%) Age (year) 57.53 ± 11.74 Follow-up time(month) 6.46(4.5,8) Hypertension 82(72.6%) Diabetes 9(8.0%) Heart disease 3(2.7%) Smoke 7(6.2%) Drink 9(8.0%) Stroke 18(2.7%) Rupture 72(63.7%) Location ICA 22(19.5%) MCA 8(7.1%) ACA 7(6.2%) ACoA 24(21.2%) PCoA 43(38.1%) PCA 9(8.0%) Size(mm) 5.72(4.13,6.65) Size classification Small 61(54.0%) Medium 44(38.9%) Large 7(6.2%) Serpentine 1(0.9%) Neck(mm) 3.51(2.50,4.20) Wide necked 42(37.2%) Morphology Saccular 67(59.3%) Irregularity 46(40.7%) Incident angle Acute angle 35(31.0%) Obtuse angle 78(69.0%) Stent 42(37.2%) Surgery time(h) 2.26(1.75,2.6) RROC Ⅰ 100(88.5%) Ⅱ/Ⅲ 13(11.5%) Recurrence 26(23.0%) ACA, anterior cerebral artery; ACoA, anterior communicating artery; ICA, internal carotid artery; MCA, middle cerebral artery; PCoA, posterior communicating artery; PCA, posterior cerebral artery; RROC, Raymond-Roy occlusion classification. Nomogram variable screening, construction and validation According to the univariate regression analyses, we identified that age (P = 0.018), Rupture (P = 0.039), Incident angle (P = 0.001), Stent (P = 0.009) and RROC (P = 0.005) were five major risk factors for recurrence of patients with endovascular treatment of IAs (Table 2 ). The multivariate regression analyses showed that Age (OR:0.904, 95% CI:0.854–0.957, P = < 0.001), Incident angle (OR:0.053, 95% CI:0.006–0.495, P = 0.010) and RROC (OR:0.138, 95% CI:0.032–0.596, P = 0.008) were independent risk factors for recurrence in patients with IAs after endovascular coiling (Table 3 ). Based on the results of multivariate regression analysis, the nomograms for predicting IAs recurrence after endovascular coiling in patients with IAs are shown in (Fig. 1 ). The predictive nomogram for IAs recurrence was developed using the following five independent predictive variables: Age, Rupture, Incident angle, Stent and RROC. For each predictive factor in the nomogram was given a score. The total score was further converted to probability which represents IAs recurrence in patients with IAs after endovascular coiling. Meanwhile, a website was developed to make the clinical application more useful and available Online https://recurrentaneurysm.shinyapps.io/Recurrent/ (Fig. 2 ). The nomogram had good discriminative ability with the C index was 0.856 (95% CI = 0.679–0.781) and its AUC displayed (Fig. 3 ). The calibration plot showed that IAs recurrence probabilities predicted by the nomogram had a good correlation with the actual observation probabilities with a mean absolute error of 0.037 in (Fig. 4 ). The decision curve analysis of the nomogram is presented in (Fig. 5 ), which indicated the clinical value. if the threshold probability of was between 0 and 80%, using the nomogram to predict IAs recurrence added more net benefit. Table 2 Univariate regression analysis for risk factors of recurrence Characteristics Cured group(n = 87) Recurrence group(n = 26) P Male 29(33.3%) 9(34.6%) 0.903 Age (year) 59.26 ± 10.30 51.73 ± 14.38 0.018* Follow-up time(month) 6(4,7) 7(4.75,9) 0.122 Hypertension 64(73.6%) 18(69.2%) 0.664 Diabetes 6(6.9%) 3(11.5%) 0.443 Heart disease 3(3.4%) 0(0%) 0.337 Smoke 6(6.9%) 1(3.8%) 0.571 Drink 6(6.9%) 3(11.5%) 0.443 Stroke 13(14.9%) 5(19.2%) 0.600 Rupture 51(58.6%) 21(80.8%) 0.039* Location 0.927 ICA 18(20.7%) 4(15.4%) MCA 6(6.9%) 2(7.7%) ACA 6(6.9%) 1(3.8%) ACoA 19(21.8%) 5(19.2%) PCoA 32(36.8%) 11(42.3%) PCA 6(6.9%) 3(11.5%) Size(mm) 4.6(4.04,6.36) 4.6(4.28,7.28) 0.373 Size classification 0.530 Small 47(54.0%) 14(53.8%) Medium 37(42.5%) 7(26.9%) Large 2(2.3%) 5(19.2%) Serpentine 1(1.1%) - Neck(mm) 3.2(2.5,4.2) 3.25(2.15,4.23) 0.793 Wide necked 33(37.9%) 9(34.6%) 0.759 Morphology 0.519 Saccular 53(60.9%) 14(53.8%) Irregularity 34(39.1%) 12(46.2%) Incident angle 0.001* Acute angle 34(39.1%) 1(3.8%) Obtuse angle 53(60.9%) 25(96.2%) Stent 38(43.7%) 4(15.3%) 0.009* Surgery time(h) 2.1(1.8,2.7) 1.9(1.68,2.45) 0.385 RROC 0.005* Ⅰ 81(93.1%) 19(73.1%) Ⅱ/Ⅲ 6(6.9%) 7(26.9%) *Indicates significance at the p < 0.05 level. ACA, anterior cerebral artery; ACoA, anterior communicating artery; ICA, internal carotid artery; MCA, middle cerebral artery; PCoA, posterior communicating artery; PCA, posterior cerebral artery; RROC, Raymond-Roy occlusion classification. Table 3 Multivariate regression analysis for risk factors of recurrence Characteristics S.E. Wald OR 95%CI P Age 0.026 7.788 0.930 0.884–0.979 0.005* Rupture 0.641 0.438 0.654 0.187–2.297 0.508 Incident angle 1.113 4.448 0.096 0.011–0.847 0.035* Stent 0.720 0.286 1.469 0.358–6.022 0.593 RROC 0.729 7.129 0.143 0.034–0.596 0.008* *Indicates significance at the p < 0.05 level. Discussion In this study, we first developed an online nomogram which was a healthy and practical tool for predicting the recurrence for intracranial aneurysms after intracranial aneurysm endovascular coiling. It indicated convincing predictive accuracy and calibration, with potential methods in identifying high-risk patients and guiding individualized treatment strategies. As is well known, currently, endovascular coiling for IAs has become the first-line treatment option for IAs, and its therapeutic effects have been confirmed [ 18 ]. Coil embolization, including stent-assisted and/or without stent, because of its less injury, high safety, wide indications and rapid recovery, has a relatively high success rate and relatively few postoperative complications. Everything has two sides, a higher IAs recurrence rate is the most obvious drawback of endovascular embolization, which is about 15–33%, compared to surgical clipping [ 19 – 20 ]. Therefore, this present study was performed to identify the factors affecting IAs recurrence after endovascular embolization so as to provide some advice for practical clinical decision-making. Firstly, young age, as an independent risk factor for recurrence following endovascular intervention for intracranial aneurysms, can be incorporated into the construction of risk prediction models. Conventionally, it is believed that advancing age is accompanied by the deterioration of multiple bodily functions and a concomitant increase in disease risk. However, existing research has demonstrated that age ≥ 65 years may be associated with a reduced risk of aneurysm recurrence after endovascular coiling [ 21 ]. This finding contradicts conventional wisdom, and the mechanism underlying the potential protective effect of advanced age against aneurysm recurrence remains elusive. We hypothesize that with aging, vascular elasticity progressively diminishes and arteriosclerosis becomes more prominent, resulting in lower tension of the aneurysm wall, a more stable morphology, and decreased likelihood of blood flow breaching the occluded region post-treatment. In contrast, the vasculature of younger individuals exhibits greater elasticity and stronger pulsatility, which may lead to inadequate occlusion at the aneurysm site and increased susceptibility to recanalization. Aneurysms in young patients may be in an active growth phase, characterized by rapid expansion and an unstable response to interventional therapy. Conversely, aneurysms in elderly patients often enter a "quiescent" state with attenuated growth momentum and minimal post-treatment progression. Elderly patients typically present with a certain degree of systemic atherosclerosis, which slows blood flow; this attenuated hemodynamic profile facilitates more stable coil embolization of the aneurysm and mitigates the risks of reperfusion and recanalization [ 22 ]. Although reduced metabolic activity is commonly regarded as a hallmark of aging, this "slowed rhythm" confers benefits for tissue stability during the repair process after aneurysm occlusion, precluding the formation of new aneurysm cavities or abnormal vascular channels. A series of studies have identified that the reduction in arterial stiffness induced by extracellular matrix degradation via matrix metalloproteinases (MMPs) constitutes one of the central mechanisms driving aneurysm progression, suggesting that factors regulating MMP expression or activity may represent viable therapeutic targets [ 23 ]. Another study revealed that in various physiological contexts, advancing age correlates negatively with the expression levels of different MMP subtypes [ 24 ]. These findings support the notion that age per se should not be considered a contraindication when evaluating candidates for endovascular aneurysm treatment. Close follow-up is imperative for young patients. Given their relatively elevated risk of postoperative recurrence, regular imaging surveillance is recommended at 6 months, 1 year, and 2 years post-procedure to enable timely detection of recurrent aneurysms. Regarding the risk of recurrence after endovascular aneurysm intervention, the "protective effect" of age provides a novel perspective for clinical decision-making. Currently, research on hemodynamic risk factors influencing aneurysm recurrence remains relatively scarce. In a study by Zhang et al., pre-interventional and immediate post-interventional aneurysm models were constructed using computational modeling approaches. Computational fluid dynamics was employed to quantify four hemodynamic parameters of the enrolled aneurysms: blood flow velocity at the aneurysm neck plane, intra-aneurysmal blood flow velocity, wall shear stress (WSS) at the aneurysm neck, and WSS across the entire aneurysm wall. The hemodynamic reduction rate for each parameter was defined as [(pre-treatment mean value - immediate post-treatment mean value) / pre-treatment mean value]. The study findings indicated that the reduction rate of blood flow velocity at the aneurysm neck plane was significantly associated with aneurysm recurrence (OR = 0.98, 95% CI: 0.96–1.00, P = 0.013), with a lower reduction rate correlating with a higher recurrence risk [ 22 – 23 ]. The incident angle is defined as the planar projection angle between the centerline of the parent artery and the direction of the aneurysm’s maximum diameter. It exhibits a positive correlation with the peak velocity and kinetic energy of blood flow at the aneurysm neck [ 24 – 26 ]. Consequently, we deduced that the incident angle is negatively correlated with the aneurysm recurrence rate, and an incident angle > 90° constitutes a risk factor for recurrence, which further validates the nomogram. In the present study, patients who underwent stent-assisted embolization exhibited a lower postoperative recurrence rate. The advantages of stent-assisted coil embolization include confining coils within the aneurysm cavity to prevent protrusion into the parent artery, reducing the risk of distal vascular embolism, promoting vascular endothelial proliferation and intimal stabilization, achieving more thorough occlusion of the aneurysm neck, and providing effective scaffolding for coil deployment [ 27 – 28 ]. This technique addresses the limitation of unstable coil placement associated with standalone coil embolization, enabling secure, complete, and dense packing. This minimizes coil dislodgment and compression-induced deformation, thereby enhancing embolization efficacy and reducing the recurrence rate [ 29 ].The use of stents is one of the important factors in preventing the recurrence of aneurysms, which has also been confirmed by our research. There were significant differences observed in the univariate analysis. Stents placement is influenced by multiple factors such as the size of the aneurysm, the width of the aneurysm neck, and the angle of incidence. Additionally, there are certain interactions between stents and other variables. Typically, stents are used for wide-necked aneurysms, while simple coil embolization is employed for narrow-necked aneurysms. Wide-necked aneurysms are more prone to recurrence, whereas narrow-necked aneurysms are less likely to recur. These factors may explain why stents are not identified as an independent influencing factor in the multivariate analysis. In fact, this study is merely a single-center retrospective study with an insufficient sample size. The impact of stent use on the probability of postoperative recurrence is affected by multiple factors. Therefore, further large-sample, multi-center studies are required. The Raymond-Roy classification is an imaging-based system designed to assess the immediate and follow-up outcomes of endovascular embolization for intracranial aneurysms, categorized into Grade I (complete occlusion), Grade II (near-complete occlusion), and Grade III (partial occlusion) [ 30 ]. Raymond-Roy Occlusion Classification (RROC) II (residual neck) is not infrequent in clinical practice, with a reported incidence ranging from 20% to 60% [ 31 ]. In this study, aneurysms with an immediate post-interventional RROC of Grade II or III had a significantly higher recurrence rate. A study by Kim et al. also confirmed an association between Raymond-Roy Grade II or III and recurrence of posterior communicating artery aneurysms [ 32 ]. The underlying mechanism may involve the formation of complex hemodynamic patterns (e.g., turbulence and eddy currents) within the aneurysm cavity that is not fully packed with coils. These eddy zones represent high-risk regions for coil migration or dislodgment and are subjected to continuous impingement by residual blood flow, ultimately leading to aneurysm recurrence. It is crucial to emphasize that the selection of treatment strategies for intracranial aneurysms in our practice is primarily based on a "risk-benefit" assessment contingent on aneurysm rupture status. For ruptured aneurysms, the paramount goal is to urgently prevent rebleeding (with a mortality rate of 40%–60% for rebleeding), thus advocating for a "proactive packing" strategy to minimize residual space within the aneurysm cavity. For unruptured aneurysms, the primary objective is to prevent future rupture while balancing treatment-related complications (e.g. thrombosis, vascular injury). Accordingly, packing strategies are more individualized, and "moderate packing" may be deemed acceptable. This strategic discrepancy is directly reflected in the degree of intraoperative packing: for ruptured aneurysms, every effort is made to achieve Raymond-Roy Grade I complete occlusion, even if it necessitates increased procedural complexity to avoid Grade II/III residuals. In contrast, for unruptured aneurysms, on the premise of ensuring occlusion of the main aneurysm body, a higher tolerance for Grade II neck residuals is permitted to avoid additional risks arising from the overzealous pursuit of "perfect occlusion". Given that numerous studies have documented poor prognostic outcomes associated with ruptured aneurysms, our center adopts a prudent approach in managing such cases [ 33 – 34 ]. This may account for the observed difference in the rupture factor in univariate analysis, which was not replicated in multivariate analysis. The prediction model developed in this study is not without limitations, which may hinder its widespread application and the accuracy of its interpretations. First, the model is derived from the analysis of a single dataset, and its generalizability to patient populations of other ethnicities or geographical regions may be limited. Second, the relatively small sample size may have resulted in insufficient statistical power, precluding the capture of all complex relationships between potential predictive variables and the outcome. Third, the variable selection strategy employed during model construction may have introduced overfitting, particularly given the multiplicity and complexity of the variables. Although overfitted models demonstrate excellent performance on the training dataset, their generalization capability to independent validation datasets is often compromised. Additionally, with the advancement of new evidence and technologies, the model will require periodic updates to maintain its accuracy and clinical relevance. Conclusion This study identifies young age, incident angle > 90° and immediate post-interventional RROC Grade II–III as independent risk factors for recurrence following coil embolization of intracranial aneurysms. The constructed risk model, which integrates clinical and imaging parameters, exhibits robust predictive performance, as validated by calibration curve and decision curve analysis. It holds promise for assisting clinicians in predicting and mitigating the risk of postoperative recurrence in patients undergoing intracranial aneurysm coil embolization. Future research should focus on enhancing the model’s accuracy and reliability, as well as exploring its applicability across broader and more diverse patient cohorts. Declarations Funding We received funding supported by National Natural Science Foundation Youth Incubation Project of the Second Affiliated Hospital of Anhui Medical University (Grant No. 2019GQFY01). Author contribution C. Ma: Writing–original draft, Methodology, Investigation, Funding acquisition C. Ni: Writing–original draft, Methodology, Investigation, Validation 3. B. Zhao: Writing–review & editing, Supervision, Resources, Project administration 4. Z. Li: Conceptualization, Software, Visualization 5. B. Wang: Validation 6. Y. Wang: Data curation 7. G. Zong: Formal analysis 8. Y. Hu: Data curation All authors have read and approved the final manuscript. B. Zhao is the corresponding author and guarantor of the study. Data availability The authors confirm that the data supporting the findings of this study are available within the article. Conflict of interest There are no conflicts of interest to be declared. 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Neurosurgery. 2015;77(2):241–7. discussion 247. He YL, Ji M, Liao ZP, Shang R, Hu HT, Ma YH, Richard SA, Zhang CW, Niu L. Comparison of Stent-Assisted and Non-Stent-Assisted coil embolization in the treatment of Wide-Neck intracranial aneurysms: A Meta-Analysis. Neurol Sci. 2025;46(10):4875–88. Darflinger R, Thompson LA, Zhang Z, Chao K. Recurrence, retreatment, and rebleed rates of coiled aneurysms with respect to the Raymond-Roy scale: a meta-analysis. J Neurointerv Surg. 2016;8(5):507–11. Munich SA, Cress MC, Rangel-Castilla L, Sonig A, Ogilvy CS, Lanzino G, Petr O, Mocco J, Morone PJ, Snyder KV, Hopkins LN, Siddiqui AH, Levy EI. Neck Remnants and the Risk of Aneurysm Rupture After Endovascular Treatment With Coiling or Stent-Assisted Coiling. Much Ado About Nothing? Neurosurg. 2019;84(2):421–7. Kim MJ, Chung J, Park KY, Kim DJ, Kim BM, Suh SH, Lee JW, Huh SK, Kim YB, Joo JY, Son NH, Jang CK. Recurrence and risk factors of posterior communicating artery aneurysms after endovascular treatment. Acta Neurochir (Wien). 2021;163(8):2319–26. Hamming AL, van Dijck JTJM, Visser T, Baarse M, Verbaan D, Schenck H, Haeren RHL, Fakhry R, Dammers R, Aquarius R, Boogaarts JHD, Peul WC, Moojen WA. Study on prognosis of acutely ruptured intracranial aneurysms (SPARTA): a protocol for a multicentre prospective cohort study. BMC Neurol. 2024;24(1):68. Higashi T. [Ruptured Cerebral Aneurysm:Indications and Outcomes]. No Shinkei Geka. 2023;51(2):230–8. 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8306812","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":559026408,"identity":"58b6b9b5-2922-4293-b6d7-fc545ea32233","order_by":0,"name":"Chunchun Ma","email":"","orcid":"","institution":"The Second Affiliated Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chunchun","middleName":"","lastName":"Ma","suffix":""},{"id":559026410,"identity":"f39b9a7b-fe20-4470-8ecd-6512e75980db","order_by":1,"name":"Chengzhi Ni","email":"","orcid":"","institution":"The Second Affiliated Hospital of Anhui 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16:18:19","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":130310,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8306812/v1/1741915dd1804d6a7b82be0f.html"},{"id":98245544,"identity":"329522f9-265d-4c44-a2e2-6609c158c160","added_by":"auto","created_at":"2025-12-15 16:18:03","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":68820,"visible":true,"origin":"","legend":"\u003cp\u003eNomogram Prediction Model for Risk Factors of Recurrence After Aneurysm Interventional Surgery\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8306812/v1/0884b7a8b8ecf476883ef56e.jpg"},{"id":98245806,"identity":"694178b5-5295-4a31-9146-7441baefa4a9","added_by":"auto","created_at":"2025-12-15 16:18:24","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":57778,"visible":true,"origin":"","legend":"\u003cp\u003eExamples of the dynamic nomograms for Risk Factors of Recurrence After Aneurysm Interventional Surgery(https://recurrentaneurysm.shinyapps.io/DynNomapp/). The probability of recurrence is shown on the right side of the screen after each parameter is entered on the left input field.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8306812/v1/2ac42123f014b9e9fe265a40.jpg"},{"id":98245752,"identity":"0401a5d3-ecb9-445b-ab97-e136b8e215a2","added_by":"auto","created_at":"2025-12-15 16:18:20","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":40834,"visible":true,"origin":"","legend":"\u003cp\u003eThe ROC curves of the nomogram. The ability of the nomogram was measured and compared according to area under the curve values\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8306812/v1/ce7195ecca6fbb16307e214f.jpg"},{"id":98245368,"identity":"fb318795-82aa-425e-9fbb-482018adabe1","added_by":"auto","created_at":"2025-12-15 16:17:50","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":45868,"visible":true,"origin":"","legend":"\u003cp\u003eThe calibration curves for the nomogram are presented in Figure 1. The generation of a prediction model that is entirely accurate will result in the creation of a plot in which the probability of the observed and predicted values falling along the 45° line is reflected. The apparent calibration curve is representative of the calibration of the model in the development data set, while the bias-corrected curve is the calibration result subsequent to the correction of optimism through the implementation of 1000 bootstrap resamplings. It is evident that the closer the apparent calibration curve is to the bias-corrected curve, the more accurate the model's predictions regarding prognosis.\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8306812/v1/24cb1ff0e79a5f3e9cc248a0.jpg"},{"id":98245599,"identity":"67a6cf47-2152-4c17-b202-9b4258b7df80","added_by":"auto","created_at":"2025-12-15 16:18:09","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":65311,"visible":true,"origin":"","legend":"\u003cp\u003eDecision curve analysis of the nomograms for Recurrence After Aneurysm Interventional Surgery. DCA plots revealed that the nomogram had good net benefits. DCA, decision curve analysis.\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8306812/v1/9e87adc129670eb7dd412a9d.jpg"},{"id":99793923,"identity":"ed33d874-a1ce-4149-a1ea-13062be71834","added_by":"auto","created_at":"2026-01-08 13:33:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1046065,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8306812/v1/deab2788-df30-4e95-85df-857e1506048c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"An online dynamic nomogram for predicting the recurrence of patients with endovascular treatment of intracranial aneurysms","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIntracranial aneurysms (IAs) are a cerebrovascular disease that seriously threatens human health [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. If untreated or left to grow, they can rupture, leading to life-threatening conditions such as subarachnoid hemorrhage (SAH) or intracerebral hematoma formation, which can cause significantly devastating consequences [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Nowadays coil embolization (including stent-assisted coiling) is a highly safe and effective method for treatment IAs [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Although coil embolization has significant advantages in the treatment of intracranial aneurysms, it also has quite a few drawbacks. The most prominent one is the risk of recurrence, which can cause the aneurysm to expand again or reopen, and increases the risk of aneurysm rupture [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Therefore, to reduce the recurrence rate after intracranial aneurysm coiling embolization, it is crucial to identify and predict the factors that contribute to recurrence following endovascular coiling of intracranial aneurysms.\u003c/p\u003e\u003cp\u003eIn the past years, many studies have already confirmed several reasons that lead to the recurrence of IAs after coil embolization, including in the middle cerebral artery (MCA), large size(\u0026gt;\u0026thinsp;10mm), posterior circulation location, ruptured aneurysm, wide neck [\u003cspan additionalcitationids=\"CR6 CR7 CR8\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Artificial intelligence (AI) is now applied to aspects such as the calculation of morphological parameters of intracranial aneurysms, rupture risk stratification, and the prediction of aneurysm recurrence risk based on Machine Learning (ML) methods. Some studies have established multiple ML models for predicting aneurysm rupture, such as Random Forest (RF), Support Vector Machine (SVM) or Gradient Boosting Decision Tre (GBDT), based on the clinical characteristics of patients and the morphological features of aneurysms. They compared the AUC values, sensitivity, specificity and accuracy of these models with those of the classic logistic regression model. All results confirmed that the machine learning models were superior to the logistic regression model. However, there are relatively few models for predicting aneurysm recurrence [\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The current research on the risk prediction of recurrence of intracranial aneurysms after endovascular intervention focuses on risk factor screening, and some foreign research institutions have begun to predict the risk of recurrence by establishing a logistic regression model based on screening risk factors [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. A total of 218 patients with intracranial aneurysms who underwent interventional embolization, and the results of multivariate analysis showed that the maximum diameter of the aneurysm and posterior circulation aneurysms were risk factors for aneurysm recurrence. Stent-assisted embolization was a protective factor for aneurysm recurrence [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHowever, these studies, like other similar studies, did not simplify the logistic regression model, and the calculation of risk through mathematical formulas in clinical applications is still relatively complicated.\u003c/p\u003e\u003cp\u003eTherefore, establishing a simple, accurate, and clinically useful dynamic nomogram for predicting the recurrence risk after intracranial aneurysm embolization that can comprehensively consider relevant risk factors is of great value for clinical decision-making and improving surgical efficacy.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003ePatients\u0026rsquo; data and characteristics\u003c/h2\u003e\u003cp\u003eWe collected 113 IA patients who had undergone endovascular coiling between November 2018 and January 2024 at the Second Affiliated Hospital of Anhui Medical University (Hefei, China). The study was approved by the Ethics Committee of the Second Affiliated Hospital at Anhui Medical University (document NO: YX2025-185). This study was performed in line with the ethical standards of the Helsinki Declaration (revised by Brazil in 2013). All patients gave informed consent to enroll in the study.\u003c/p\u003e\u003cp\u003eThe inclusion criteria for patients in this study were as follows: 1. Patients who were diagnosed with IAs by CTA, MRA or DSA before surgery. 2. IAs treated with coil embolization, including simple embolization and stent-assisted embolization. 3. Complete DSA or MRA images before and after the operation, enabling morphological measurement. Patients\u0026rsquo; exclusion criteria: 1. blister - like aneurysms and other special aneurysms; 2. Patients who underwent craniotomy, parent-artery occlusion, treatment with flow - diverting devices, or conservative management; 3. Patients who had undergone surgical clipping or endovascular embolization for aneurysms before admission and were admitted for re-operation; 4. There are no imaging follow - up data for more than 3 months after the surgery.\u003c/p\u003e\u003cp\u003eSome variables from the clinical characteristics: including gender, age, smoking, alcohol, hypertension, diabetes, coronary heart disease (CHD). We also recorded operation-related data, such as ruptured status, aneurysm location, operation time, stent types, aneurysm size classification, operation time, Raymond-Roy occlusion classification (RROC), and aneurysm morphologies. Aneurysm location was divided into six parts, namely, internal carotid artery (ICA), anterior communicating artery (ACoA) posterior communicating artery (PCoA), anterior cerebral artery (ACA), middle cerebral artery (MCA) and posterior circulation (basilar artery, superior cerebellar artery, vertebral artery, and posterior inferior cerebellar artery). Stent types, including coil alone, braided and laser-cut type. The anatomical data of aneurysms were measured according to the results of DSA imaging. Aneurysm size classification was divided into giant aneurysms (\u0026gt;\u0026thinsp;25mm), large aneurysms (10-25mm), medium aneurysms (5-10mm) and small aneurysms (\u0026lt;\u0026thinsp;5mm) according to the longest diameter of aneurysm body. Raymond-Roy occlusion classification (RROC) was used to evaluate the immediate results of treatment by the surgeon, Grade I represent complete occlusion; Grade II represents residual neck; Grade III represents residual part of the aneurysm sac. Aneurysm morphologies parameters were measured by DSA. The morphological variables were defined as follows, Maximum diameter (MD); Neck of the aneurysm (N); Incident Angle (IA); wide-necked aneurysm or narrow-neck aneurysms; saccular or irregular shape.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eImaging postoperative follow-up\u003c/h3\u003e\n\u003cp\u003eIn clinical practice, the first follow-up is usually 6 months after surgery as an indicator of whether the aneurysm is occluded. Imaging postoperative follow-up was performed by DSA or MRA. According to the comparison with the immediate postoperative imaging results, the imaging results were divided into four types: cure, improvement, stability and recurrence. Cure, defined as no contrast agent into the aneurysm, aneurysm embolization; Improvement, defined as a reduction in the volume of contrast agent entering the aneurysm, but not complete embolization; Stable, defined as no significant change in the volume of contrast agent entering the aneurysm compared to immediately after surgery; Recurrence, defined as an increase in the volume of contrast agent entering the aneurysm compared to immediately after surgery, or significant coil compression detected. Imaging findings Angiographic findings were interpreted by at least two neuroradiologists with more than 5 years of imaging interpretation experience [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eAll statistical analysis was executed by using R language (version 4.2.0, Vienna, Austria). For the measurement data conforming to the normal distribution, it is expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD), and the inter-group difference analysis adopts two independent sample t-test. For the measurement data not conforming to the normal distribution, it is expressed as median and quartile [median (Q25, Q75)], and the inter-group comparison adopts Mann-Whitney U test. For the count data, it is expressed as number (rate), and the inter-group difference test adopts χ\u0026sup2; test. The odds ratio (OR) and 95% confidence interval (CI) were figured. Univariate analysis was performed to determine risk factors for recurrence of patients with endovascular treatment of intracranial aneurysms. Variables with a P value less than 0.05, then entering into next step, using multivariate logistic regression analysis to determine the independent risk factors for predicting recurrence of patients with endovascular treatment of intracranial aneurysms. Although univariate analysis showed no statistically significant association between stent groups and outcomes (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), stents may indirectly influence outcomes through several factors: preventing the migration of microcoils and improving the dense packing rate; assisting coil embolization and promoting thrombus formation; and their mesh structure can cover the aneurysm neck, reducing direct blood flow impact on the residual aneurysm neck and lowering the probability of aneurysm recurrence. Therefore, this study included it in the multivariate model to adjust for potential confounding effects and enhance the robustness of the model. According to the results of multivariate logistic regression analysis, a static and dynamic online nomogram was established with R language (version 4.2.0, Vienna, Austria). Mode performance of the nomogram was evaluated based on discrimination and calibration. The receiver operating characteristic (ROC) were used to measure model discrimination. The effectiveness of calibration was determined using a calibration plot, which indicates the correlation between predicted and actual probability using a bootstrapped sample. The decision curve analysis (DCA) was performed to evaluate the clinical applicability at each threshold probability of the nomogram. The p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant in all analyses.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003ePatient characteristics\u003c/h2\u003e\u003cp\u003e113 IA patients who met the inclusion criteria and conducted imaging postoperative follow‑up, were enrolled in this study, and 7 had two aneurysms which were also undergone endovascular coiling. Overall characteristics of IA patients are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The mean age of all patients was 57.53\u0026thinsp;\u0026plusmn;\u0026thinsp;11.74 years, female was more common than men, and the average imaging postoperative follow-up was 6.46 months for all patients. Among all these IAs, ruptured aneurysms were 72 (63.7%), Obtuse angle were 78 (69%), 100(88.5%) were classified as RROC Ⅰ, 13 (11.5%) were classified as RROC Ⅱ/Ⅲ, and 42 IAs treated with stents. The overall recurrence occurred in 23% (26/113).\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 Information\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal(n\u0026thinsp;=\u0026thinsp;113)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\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\u003e38(33.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (year)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e57.53\u0026thinsp;\u0026plusmn;\u0026thinsp;11.74\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFollow-up time(month)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.46(4.5,8)\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\u003e82(72.6%)\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\u003e9(8.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeart disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3(2.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoke\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7(6.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrink\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9(8.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStroke\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18(2.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRupture\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e72(63.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eICA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22(19.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8(7.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eACA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7(6.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eACoA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e24(21.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePCoA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e43(38.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9(8.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSize(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5.72(4.13,6.65)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSize classification\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmall\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e61(54.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e44(38.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLarge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7(6.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSerpentine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1(0.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeck(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.51(2.50,4.20)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWide necked\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e42(37.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMorphology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSaccular\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e67(59.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIrregularity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e46(40.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncident angle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcute angle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35(31.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eObtuse angle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e78(69.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e42(37.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSurgery time(h)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.26(1.75,2.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRROC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eⅠ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e100(88.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eⅡ/Ⅲ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13(11.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRecurrence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26(23.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eACA, anterior cerebral artery; ACoA, anterior communicating artery; ICA, internal carotid artery; MCA, middle cerebral artery; PCoA, posterior communicating artery; PCA, posterior cerebral artery; RROC, Raymond-Roy occlusion classification.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eNomogram variable screening, construction and validation\u003c/h2\u003e\u003cp\u003eAccording to the univariate regression analyses, we identified that age (P\u0026thinsp;=\u0026thinsp;0.018), Rupture (P\u0026thinsp;=\u0026thinsp;0.039), Incident angle (P\u0026thinsp;=\u0026thinsp;0.001), Stent (P\u0026thinsp;=\u0026thinsp;0.009) and RROC (P\u0026thinsp;=\u0026thinsp;0.005) were five major risk factors for recurrence of patients with endovascular treatment of IAs (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The multivariate regression analyses showed that Age (OR:0.904, 95% CI:0.854\u0026ndash;0.957, P\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001), Incident angle (OR:0.053, 95% CI:0.006\u0026ndash;0.495, P\u0026thinsp;=\u0026thinsp;0.010) and RROC (OR:0.138, 95% CI:0.032\u0026ndash;0.596, P\u0026thinsp;=\u0026thinsp;0.008) were independent risk factors for recurrence in patients with IAs after endovascular coiling (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Based on the results of multivariate regression analysis, the nomograms for predicting IAs recurrence after endovascular coiling in patients with IAs are shown in (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The predictive nomogram for IAs recurrence was developed using the following five independent predictive variables: Age, Rupture, Incident angle, Stent and RROC. For each predictive factor in the nomogram was given a score. The total score was further converted to probability which represents IAs recurrence in patients with IAs after endovascular coiling. Meanwhile, a website was developed to make the clinical application more useful and available Online \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://recurrentaneurysm.shinyapps.io/Recurrent/\u003c/span\u003e\u003cspan address=\"https://recurrentaneurysm.shinyapps.io/Recurrent/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The nomogram had good discriminative ability with the C index was 0.856 (95% CI\u0026thinsp;=\u0026thinsp;0.679\u0026ndash;0.781) and its AUC displayed (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The calibration plot showed that IAs recurrence probabilities predicted by the nomogram had a good correlation with the actual observation probabilities with a mean absolute error of 0.037 in (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The decision curve analysis of the nomogram is presented in (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), which indicated the clinical value. if the threshold probability of was between 0 and 80%, using the nomogram to predict IAs recurrence added more net benefit.\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\u003eUnivariate regression analysis for risk factors of recurrence\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\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCured group(n\u0026thinsp;=\u0026thinsp;87)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRecurrence group(n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29(33.3%)\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\u003e0.903\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (year)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59.26\u0026thinsp;\u0026plusmn;\u0026thinsp;10.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51.73\u0026thinsp;\u0026plusmn;\u0026thinsp;14.38\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\u003eFollow-up time(month)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6(4,7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7(4.75,9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.122\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e64(73.6%)\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\u003e0.664\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6(6.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3(11.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.443\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeart disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3(3.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0(0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.337\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoke\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6(6.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(3.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.571\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrink\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6(6.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3(11.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.443\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStroke\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13(14.9%)\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\u003e0.600\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRupture\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e51(58.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21(80.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.039*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocation\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\u003e0.927\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eICA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18(20.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4(15.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6(6.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2(7.7%)\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\u003eACA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6(6.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(3.8%)\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\u003eACoA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19(21.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5(19.2%)\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\u003ePCoA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32(36.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11(42.3%)\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\u003ePCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6(6.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3(11.5%)\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\u003eSize(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.6(4.04,6.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.6(4.28,7.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.373\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSize classification\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\u003e0.530\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmall\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47(54.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14(53.8%)\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\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37(42.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7(26.9%)\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\u003eLarge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2(2.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5(19.2%)\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\u003eSerpentine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1(1.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\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\u003eNeck(mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.2(2.5,4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.25(2.15,4.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.793\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWide necked\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33(37.9%)\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\u003e0.759\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMorphology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.519\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSaccular\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e53(60.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14(53.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIrregularity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34(39.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12(46.2%)\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\u003eIncident angle\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\u003e0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcute angle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34(39.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(3.8%)\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\u003eObtuse angle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e53(60.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25(96.2%)\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\u003eStent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38(43.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4(15.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.009*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSurgery time(h)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.1(1.8,2.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.9(1.68,2.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.385\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRROC\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\u003e0.005*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eⅠ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e81(93.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19(73.1%)\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\u003eⅡ/Ⅲ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6(6.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7(26.9%)\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\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e*Indicates significance at the p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 level.\u003c/p\u003e\u003cp\u003eACA, anterior cerebral artery; ACoA, anterior communicating artery; ICA, internal carotid artery; MCA, middle cerebral artery; PCoA, posterior communicating artery; PCA, posterior cerebral artery; RROC, Raymond-Roy occlusion classification.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultivariate regression analysis for risk factors of recurrence\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eS.E.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWald\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95%CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\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\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.788\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.930\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.884\u0026ndash;0.979\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.005*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRupture\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.641\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.438\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.654\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.187\u0026ndash;2.297\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.508\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncident angle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.113\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.448\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.096\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.011\u0026ndash;0.847\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.035*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.720\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.286\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.469\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.358\u0026ndash;6.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.593\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRROC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.729\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.034\u0026ndash;0.596\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.008*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e*Indicates significance at the p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 level.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we first developed an online nomogram which was a healthy and practical tool for predicting the recurrence for intracranial aneurysms after intracranial aneurysm endovascular coiling. It indicated convincing predictive accuracy and calibration, with potential methods in identifying high-risk patients and guiding individualized treatment strategies. As is well known, currently, endovascular coiling for IAs has become the first-line treatment option for IAs, and its therapeutic effects have been confirmed [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Coil embolization, including stent-assisted and/or without stent, because of its less injury, high safety, wide indications and rapid recovery, has a relatively high success rate and relatively few postoperative complications. Everything has two sides, a higher IAs recurrence rate is the most obvious drawback of endovascular embolization, which is about 15\u0026ndash;33%, compared to surgical clipping [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Therefore, this present study was performed to identify the factors affecting IAs recurrence after endovascular embolization so as to provide some advice for practical clinical decision-making.\u003c/p\u003e\u003cp\u003eFirstly, young age, as an independent risk factor for recurrence following endovascular intervention for intracranial aneurysms, can be incorporated into the construction of risk prediction models. Conventionally, it is believed that advancing age is accompanied by the deterioration of multiple bodily functions and a concomitant increase in disease risk. However, existing research has demonstrated that age\u0026thinsp;\u0026ge;\u0026thinsp;65 years may be associated with a reduced risk of aneurysm recurrence after endovascular coiling [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This finding contradicts conventional wisdom, and the mechanism underlying the potential protective effect of advanced age against aneurysm recurrence remains elusive. We hypothesize that with aging, vascular elasticity progressively diminishes and arteriosclerosis becomes more prominent, resulting in lower tension of the aneurysm wall, a more stable morphology, and decreased likelihood of blood flow breaching the occluded region post-treatment. In contrast, the vasculature of younger individuals exhibits greater elasticity and stronger pulsatility, which may lead to inadequate occlusion at the aneurysm site and increased susceptibility to recanalization. Aneurysms in young patients may be in an active growth phase, characterized by rapid expansion and an unstable response to interventional therapy. Conversely, aneurysms in elderly patients often enter a \"quiescent\" state with attenuated growth momentum and minimal post-treatment progression. Elderly patients typically present with a certain degree of systemic atherosclerosis, which slows blood flow; this attenuated hemodynamic profile facilitates more stable coil embolization of the aneurysm and mitigates the risks of reperfusion and recanalization [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Although reduced metabolic activity is commonly regarded as a hallmark of aging, this \"slowed rhythm\" confers benefits for tissue stability during the repair process after aneurysm occlusion, precluding the formation of new aneurysm cavities or abnormal vascular channels. A series of studies have identified that the reduction in arterial stiffness induced by extracellular matrix degradation via matrix metalloproteinases (MMPs) constitutes one of the central mechanisms driving aneurysm progression, suggesting that factors regulating MMP expression or activity may represent viable therapeutic targets [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Another study revealed that in various physiological contexts, advancing age correlates negatively with the expression levels of different MMP subtypes [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. These findings support the notion that age per se should not be considered a contraindication when evaluating candidates for endovascular aneurysm treatment. Close follow-up is imperative for young patients. Given their relatively elevated risk of postoperative recurrence, regular imaging surveillance is recommended at 6 months, 1 year, and 2 years post-procedure to enable timely detection of recurrent aneurysms. Regarding the risk of recurrence after endovascular aneurysm intervention, the \"protective effect\" of age provides a novel perspective for clinical decision-making.\u003c/p\u003e\u003cp\u003eCurrently, research on hemodynamic risk factors influencing aneurysm recurrence remains relatively scarce. In a study by Zhang et al., pre-interventional and immediate post-interventional aneurysm models were constructed using computational modeling approaches. Computational fluid dynamics was employed to quantify four hemodynamic parameters of the enrolled aneurysms: blood flow velocity at the aneurysm neck plane, intra-aneurysmal blood flow velocity, wall shear stress (WSS) at the aneurysm neck, and WSS across the entire aneurysm wall. The hemodynamic reduction rate for each parameter was defined as [(pre-treatment mean value - immediate post-treatment mean value) / pre-treatment mean value]. The study findings indicated that the reduction rate of blood flow velocity at the aneurysm neck plane was significantly associated with aneurysm recurrence (OR\u0026thinsp;=\u0026thinsp;0.98, 95% CI: 0.96\u0026ndash;1.00, P\u0026thinsp;=\u0026thinsp;0.013), with a lower reduction rate correlating with a higher recurrence risk [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The incident angle is defined as the planar projection angle between the centerline of the parent artery and the direction of the aneurysm\u0026rsquo;s maximum diameter. It exhibits a positive correlation with the peak velocity and kinetic energy of blood flow at the aneurysm neck [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Consequently, we deduced that the incident angle is negatively correlated with the aneurysm recurrence rate, and an incident angle\u0026thinsp;\u0026gt;\u0026thinsp;90\u0026deg; constitutes a risk factor for recurrence, which further validates the nomogram.\u003c/p\u003e\u003cp\u003eIn the present study, patients who underwent stent-assisted embolization exhibited a lower postoperative recurrence rate. The advantages of stent-assisted coil embolization include confining coils within the aneurysm cavity to prevent protrusion into the parent artery, reducing the risk of distal vascular embolism, promoting vascular endothelial proliferation and intimal stabilization, achieving more thorough occlusion of the aneurysm neck, and providing effective scaffolding for coil deployment [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This technique addresses the limitation of unstable coil placement associated with standalone coil embolization, enabling secure, complete, and dense packing. This minimizes coil dislodgment and compression-induced deformation, thereby enhancing embolization efficacy and reducing the recurrence rate [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].The use of stents is one of the important factors in preventing the recurrence of aneurysms, which has also been confirmed by our research. There were significant differences observed in the univariate analysis. Stents placement is influenced by multiple factors such as the size of the aneurysm, the width of the aneurysm neck, and the angle of incidence. Additionally, there are certain interactions between stents and other variables. Typically, stents are used for wide-necked aneurysms, while simple coil embolization is employed for narrow-necked aneurysms. Wide-necked aneurysms are more prone to recurrence, whereas narrow-necked aneurysms are less likely to recur. These factors may explain why stents are not identified as an independent influencing factor in the multivariate analysis. In fact, this study is merely a single-center retrospective study with an insufficient sample size. The impact of stent use on the probability of postoperative recurrence is affected by multiple factors. Therefore, further large-sample, multi-center studies are required.\u003c/p\u003e\u003cp\u003eThe Raymond-Roy classification is an imaging-based system designed to assess the immediate and follow-up outcomes of endovascular embolization for intracranial aneurysms, categorized into Grade I (complete occlusion), Grade II (near-complete occlusion), and Grade III (partial occlusion) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Raymond-Roy Occlusion Classification (RROC) II (residual neck) is not infrequent in clinical practice, with a reported incidence ranging from 20% to 60% [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In this study, aneurysms with an immediate post-interventional RROC of Grade II or III had a significantly higher recurrence rate. A study by Kim et al. also confirmed an association between Raymond-Roy Grade II or III and recurrence of posterior communicating artery aneurysms [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The underlying mechanism may involve the formation of complex hemodynamic patterns (e.g., turbulence and eddy currents) within the aneurysm cavity that is not fully packed with coils. These eddy zones represent high-risk regions for coil migration or dislodgment and are subjected to continuous impingement by residual blood flow, ultimately leading to aneurysm recurrence.\u003c/p\u003e\u003cp\u003eIt is crucial to emphasize that the selection of treatment strategies for intracranial aneurysms in our practice is primarily based on a \"risk-benefit\" assessment contingent on aneurysm rupture status. For ruptured aneurysms, the paramount goal is to urgently prevent rebleeding (with a mortality rate of 40%\u0026ndash;60% for rebleeding), thus advocating for a \"proactive packing\" strategy to minimize residual space within the aneurysm cavity. For unruptured aneurysms, the primary objective is to prevent future rupture while balancing treatment-related complications (e.g. thrombosis, vascular injury). Accordingly, packing strategies are more individualized, and \"moderate packing\" may be deemed acceptable. This strategic discrepancy is directly reflected in the degree of intraoperative packing: for ruptured aneurysms, every effort is made to achieve Raymond-Roy Grade I complete occlusion, even if it necessitates increased procedural complexity to avoid Grade II/III residuals. In contrast, for unruptured aneurysms, on the premise of ensuring occlusion of the main aneurysm body, a higher tolerance for Grade II neck residuals is permitted to avoid additional risks arising from the overzealous pursuit of \"perfect occlusion\". Given that numerous studies have documented poor prognostic outcomes associated with ruptured aneurysms, our center adopts a prudent approach in managing such cases [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. This may account for the observed difference in the rupture factor in univariate analysis, which was not replicated in multivariate analysis.\u003c/p\u003e\u003cp\u003eThe prediction model developed in this study is not without limitations, which may hinder its widespread application and the accuracy of its interpretations. First, the model is derived from the analysis of a single dataset, and its generalizability to patient populations of other ethnicities or geographical regions may be limited. Second, the relatively small sample size may have resulted in insufficient statistical power, precluding the capture of all complex relationships between potential predictive variables and the outcome. Third, the variable selection strategy employed during model construction may have introduced overfitting, particularly given the multiplicity and complexity of the variables. Although overfitted models demonstrate excellent performance on the training dataset, their generalization capability to independent validation datasets is often compromised. Additionally, with the advancement of new evidence and technologies, the model will require periodic updates to maintain its accuracy and clinical relevance.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study identifies young age, incident angle\u0026thinsp;\u0026gt;\u0026thinsp;90\u0026deg; and immediate post-interventional RROC Grade II\u0026ndash;III as independent risk factors for recurrence following coil embolization of intracranial aneurysms. The constructed risk model, which integrates clinical and imaging parameters, exhibits robust predictive performance, as validated by calibration curve and decision curve analysis. It holds promise for assisting clinicians in predicting and mitigating the risk of postoperative recurrence in patients undergoing intracranial aneurysm coil embolization. Future research should focus on enhancing the model\u0026rsquo;s accuracy and reliability, as well as exploring its applicability across broader and more diverse patient cohorts.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eWe received funding supported by National Natural Science Foundation Youth Incubation Project of the Second Affiliated Hospital of Anhui Medical University (Grant No. 2019GQFY01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eC. Ma: Writing–original draft, Methodology, Investigation, Funding acquisition\u003c/li\u003e\n \u003cli\u003eC. Ni: Writing–original draft, Methodology, Investigation, Validation\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e3. B. Zhao: Writing–review \u0026amp; editing, Supervision, Resources, Project administration\u003c/p\u003e\n\u003cp\u003e4. Z. Li: Conceptualization, Software, Visualization\u003c/p\u003e\n\u003cp\u003e5. B. Wang: Validation\u003c/p\u003e\n\u003cp\u003e6. Y. Wang: Data curation\u003c/p\u003e\n\u003cp\u003e7. G. Zong: Formal analysis\u003c/p\u003e\n\u003cp\u003e8. Y. Hu: Data curation\u003c/p\u003e\n\u003cp\u003eAll authors have read and approved the final manuscript. B. Zhao is the corresponding author and guarantor of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e \u0026nbsp;The authors confirm that the data supporting the findings of this study are available within the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003eThere are no conflicts of interest to be declared.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical standards\u0026nbsp;\u003c/strong\u003eThe study was approved by the Ethics Committee of the Second Affiliated Hospital at Anhui Medical University (document NO: YX2025-185). This study was performed in line with the ethical standards of the Helsinki Declaration (revised by Brazil in 2013). All patients gave informed consent to enroll in the study.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eEtminan N, Rinkel GJ. 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Interv Neuroradiol. 2020;26(1):45\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eConnolly ES Jr, Rabinstein AA, Carhuapoma JR, Derdeyn CP, Dion J, Higashida RT, Hoh BL, Kirkness CJ, Naidech AM, Ogilvy CS, Patel AB, Thompson BG, Vespa P, American Heart Association Stroke Council; Council on Cardiovascular Radiology and Intervention; Council on Cardiovascular Nursing; Council on Cardiovascular Surgery. Anesthesia; Council on Clinical Cardiology. Guidelines for the management of aneurysmal subarachnoid hemorrhage: a guideline for healthcare professionals from the American Heart Association/american Stroke Association. Stroke. 2012;43(6):1711\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHan Y, Liu J, Tian Z, Lv M, Yang X, Wu Z, Gao BL. Factors affecting recurrence and management of recurrent cerebral aneurysms after initial coiling. Interv Neuroradiol. 2020;26(3):300\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQin F, Liu J, Zhao X, Wu D, Lai N, Zhang Z, Li Z. Endovascular Treatment of Ruptured Very Small Intracranial Aneurysms: Complications, Recurrence Rate, and Clinical Outcomes. Front Neurol. 2022;12:767649.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRinaldo L, Lanzino G. Increased Age Associated with Reduced Likelihood of Recurrence After Coiling of Ruptured Aneurysms. World Neurosurg. 2017;100:381\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang Q, Jing L, Liu J, Wang K, Zhang Y, Paliwal N, Meng H, Wang Y, Wang S, Yang X. Predisposing factors for recanalization of cerebral aneurysms after endovascular embolization: a multivariate study. J Neurointerv Surg. 2018;10(3):252\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIshibashi R, Itani M, Kawashima A, Arakawa Y, Aoki T. JNK2-MMP-9 axis facilitates the progression of intracranial aneurysms. Sci Rep. 2024;14(1):19458. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-024-70493-5\u003c/span\u003e\u003cspan address=\"10.1038/s41598-024-70493-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Erratum in: Sci Rep. 2025;15(1):32593.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKollarova M, Puzserova A, Balis P, Radosinska D, Tothova L, Bartekova M, Barancik M, Radosinska J. Age- and Phenotype-Dependent Changes in Circulating MMP-2 and MMP-9 Activities in Normotensive and Hypertensive Rats. Int J Mol Sci. 2020;21(19):7286.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDhar S, Tremmel M, Mocco J, Kim M, Yamamoto J, Siddiqui AH, Hopkins LN, Meng H. Morphology parameters for intracranial aneurysm rupture risk assessment. Neurosurgery. 2008;63(2):185\u0026ndash;96. discussion 196-7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaharoglu MI, Schirmer CM, Hoit DA, Gao BL, Malek AM. Aneurysm inflow-angle as a discriminant for rupture in sidewall cerebral aneurysms: morphometric and computational fluid dynamic analysis. Stroke. 2010;41(7):1423\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNakajo T, Terada T, Tsumoto T, Matsuda Y, Matsumoto H, Nakayama S, Mizutani T. Stent-Assisted Coil Embolization of Ruptured Aneurysms in the Acute Stage: Advantages and Disadvantages. J Neuroendovasc Ther. 2023;17(10):209\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang H, Sun Y, Jiang Y, Lv X, Zhao Y, Li Y, Liu A. Comparison of Stent-Assisted Coiling vs Coiling Alone in 563 Intracranial Aneurysms: Safety and Efficacy at a High-Volume Center. Neurosurgery. 2015;77(2):241\u0026ndash;7. discussion 247.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHe YL, Ji M, Liao ZP, Shang R, Hu HT, Ma YH, Richard SA, Zhang CW, Niu L. Comparison of Stent-Assisted and Non-Stent-Assisted coil embolization in the treatment of Wide-Neck intracranial aneurysms: A Meta-Analysis. Neurol Sci. 2025;46(10):4875\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDarflinger R, Thompson LA, Zhang Z, Chao K. Recurrence, retreatment, and rebleed rates of coiled aneurysms with respect to the Raymond-Roy scale: a meta-analysis. J Neurointerv Surg. 2016;8(5):507\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMunich SA, Cress MC, Rangel-Castilla L, Sonig A, Ogilvy CS, Lanzino G, Petr O, Mocco J, Morone PJ, Snyder KV, Hopkins LN, Siddiqui AH, Levy EI. Neck Remnants and the Risk of Aneurysm Rupture After Endovascular Treatment With Coiling or Stent-Assisted Coiling. Much Ado About Nothing? Neurosurg. 2019;84(2):421\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim MJ, Chung J, Park KY, Kim DJ, Kim BM, Suh SH, Lee JW, Huh SK, Kim YB, Joo JY, Son NH, Jang CK. Recurrence and risk factors of posterior communicating artery aneurysms after endovascular treatment. Acta Neurochir (Wien). 2021;163(8):2319\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHamming AL, van Dijck JTJM, Visser T, Baarse M, Verbaan D, Schenck H, Haeren RHL, Fakhry R, Dammers R, Aquarius R, Boogaarts JHD, Peul WC, Moojen WA. Study on prognosis of acutely ruptured intracranial aneurysms (SPARTA): a protocol for a multicentre prospective cohort study. BMC Neurol. 2024;24(1):68.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHigashi T. [Ruptured Cerebral Aneurysm:Indications and Outcomes]. No Shinkei Geka. 2023;51(2):230\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\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":"Intracranial aneurysm, nomogram, recurrence, endovascular coiling","lastPublishedDoi":"10.21203/rs.3.rs-8306812/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8306812/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003eIntracranial aneurysm (IA) is a serious cerebrovascular disease with a relatively high incidence, once ruptured, it an cause severely mortality and morbidity rate. Currently, endovascular coiling has become one of the main treatment methods for IAs.The purpose of this study is to develop and validate a novel clinically assessment system dynamic nomogram based on pre- and post-operative clinical and imaging characteristics to predict IAs recurrence after patients treated with endovascular coiling.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis single-institution retrospective study collected 113 patients with single IA who underwent coil embolization. Patients were followed up by using digital subtraction angiography (DSA) or Computed Tomography Angiography (CTA) or Magnetic Resonance Angiography (MRA) to observe IAs recurrence in 12 months after coil embolization. The univariate and multivariate logistic regression analysis were used to select recurrence factors to generate the nomogram. The discrimination and calibration of the nomogram were assessed using concordance index (C-index), area under time-dependent receiver operating characteristic curve (ROC), and calibration curves. Decision curve analysis (DCA) was used to assess clinical utility.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e\u003cp\u003eLogistic regression analysis identified age, angle inflow tract\u0026thinsp;\u0026gt;\u0026thinsp;90℃ and postoperative Raymond grade II or III as predictors of IAs recurrence after patients treated with endovascular coiling (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The area under ROC curve (AUC) of the nomogram was 0.838 suggested satisfactory discriminative ability of the nomogram. The calibration plots with a 1,000 bootstrap resampling indicated that probabilities predicted by the nomogram favorable consistency with the actual observation. The DCA showed that our model can gain a greater net benefit.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThis useful technique of nomogram was developed and validated which can help physicians in predicting the recurrence of patients with endovascular coiling of IAs.\u003c/p\u003e","manuscriptTitle":"An online dynamic nomogram for predicting the recurrence of patients with endovascular treatment of intracranial aneurysms","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-15 16:10:33","doi":"10.21203/rs.3.rs-8306812/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":"5b701ba8-22ee-484a-8af7-bb2a91e5ea70","owner":[],"postedDate":"December 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-06T17:08:59+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-15 16:10:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8306812","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8306812","identity":"rs-8306812","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}