Predictors of epilepsy as presenting symptom of cerebral cavernomas

Predictors of epilepsy as presenting symptom of cerebral cavernomas | 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 Predictors of epilepsy as presenting symptom of cerebral cavernomas Carmelo Lucio Sturiale, Matteo Palermo, Maria Elena Flacco, Giorgio Mantovani, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7123042/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Mar, 2026 Read the published version in Neurosurgical Review → Version 1 posted 19 You are reading this latest preprint version Abstract Background: Cerebral cavernous malformations (CCMs) are vascular lesions frequently presenting with seizures on presentation. Studies have widely analyzed topography as a determinant of epileptogenesis. However, the association between lesion volumetry and epileptic risk remains poorly investigated, as no objective volumetric thresholds have been established to stratify seizure risk. Methods: We conducted a multicentric case-control study including 230 adult patients with CCMs. Patients were grouped according to their initial presentation: epileptic (n=75) versus non-epileptic (n=155). We calculated the volumes of the lesions using the ABC/2 method and categorized them into quartiles. Subsequently, we run a multivariate logistic regression assessing independent predictors of epilepsy, adjusting for demographic, clinical, and radiological factors. We also estimated the diagnostic accuracy of lesion volume thresholds (>11.9 mm³, >80 mm³, >300 mm³). Results: Lesion volume was significantly associated with epilepsy risk. Lesions ≥80 mm³ were shown to have higher odds of seizures on presentation (OR 86.4, 95% CI 9.94–751). We found hemorrhagic presentation (OR 60.3, 95% CI 6.50–558) and frontal or temporal location (OR 6.34, 95% CI 2.99–113.4) to be also independent predictors of epilepsy. Differently, demographic and pharmacologic factors were not independently predictive. Conclusions: Lesion volume, hemorrhage, and cortical location were found to be the major predictors of epilepsy as first manifestation. Therefore, incorporating volumetric assessment into routine MRI evaluation may improve individualized risk stratification and guide early management decisions. cavernomas cavernous angiomas epilepsy seizures epileptogenesis bleeding Figures Figure 1 Introduction Cerebral cavernous malformations (CCMs) are vascular malformations composed of clusters of dilated, thin-walled capillaries lacking intervening brain parenchyma [25]. These lesions are relatively common, with an estimated prevalence of about 0.1–0.5% in the general population, and many are discovered incidentally on MRI [11]. Although often incidentally discovered, sometimes symptomatic CCMs may cause significant ictal neurologic events. Their fragile vessels, in fact, predispose to micro- or macro-hemorrhages, resulting in possible focal deficits depending on their topography; other times, however, the clinical onset may be characterized by sudden partial or generalized tonic-clonic epileptic seizures. Among symptomatic CCMs, epileptic seizures are one of the most frequent and disabling presentations, which may occur in up to roughly 40% of patients with cavernous angiomas, with some series report rates approaching 70–80% [25]. In these cases, epilepsy is the initial clinical manifestation that leads to the diagnosis of a cavernoma, and requires a long-term management, substantially contributing to patient morbidity [7, 25] Several lesion characteristics are known to influence the risk of epilepsy. Lesion location is considered particularly important: CCMs involving the cerebral cortex, in fact, especially in the temporal or frontal lobes, appear highly epileptogenic. Larger lesions and those surrounded by hemosiderin-laden gliotic tissue are also thought to amplify cortical irritability. In summary, classic risk factors for CCM‐related seizures include cortical location, large lesion size/volume, and evidence of prior hemorrhage with hemosiderin deposition [13, 17, 23]. Despite these observations, the quantitative contributions of lesion size and volume to epilepsy risk remain poorly defined. Most prior studies have described demographic and radiological correlates of seizure occurrence in CCMs, but few have rigorously evaluated how cavernoma volume predicts epilepsy. In particular, no robust volumetric threshold has been established to stratify seizure risk [6, 13, 24, 26]. The lack of systematic volume-based analysis means that clinicians currently have no objective cut-off values to guide individualized risk assessment. The present study was therefore designed to address this gap. We aimed to quantify the predictive role of cavernoma volume for epilepsy as the first clinical manifestation of CCM. We also sought optimal volumetric cut-offs that maximize sensitivity and specificity for epilepsy risk. By establishing clear thresholds and clarifying how cavernoma volume and location influence seizure propensity, this work will facilitate more precise risk stratification and inform clinical decision-making in the management of patients with CCM. Methods This is a non-profit, national, multicenter case-control study combining retrospective and prospective data collection across participating centers. The study protocol was reviewed and approved by the Local Ethical Committee (approval ID 670/2021/Oss/AOUFe). All participating institutions adhered to standardized procedures for data collection, patient confidentiality, and ethical conduct in accordance with the Declaration of Helsinki. Inclusion criteria Patients older than 18 years with either a previous or new diagnosis of CCM confirmed by neuroimaging (single CCM, multiple CCMs, or familial CCM) were included. We collected data on CCM characteristics (number, location, Zabramski classification, hemorrhagic events), prior therapies, major adverse cardiovascular events (MACE), alcohol and tobacco use, comorbidities (e.g., diabetes, obesity, hypertension), modified Rankin Scale (mRS) and Glasgow Outcome Scale (GOS) scores, and surgical treatment. All medications were recorded. Lesion volume was calculated using an adapted version of the ABC/2 method for intracerebral hemorrhage volume measurement [15] and categorized into quartiles as follows: 300 mm³. In the epilepsy group (EG), we enrolled patients whose first clinical manifestation was an epileptic seizure. The control group (CG) included patients whose first presentation was a different clinical manifestation, either neurological deficit due to cerebral hemorrhage or headache, or an incidental finding. Ethical statement and patient consent The study protocol was reviewed and approved by the Local Ethical Committee (approval ID 670/2021/Oss/AOUFe). Patient consent was not required by our institution. All participating institutions adhered to standardized procedures for data collection, patient confidentiality, and ethical conduct in accordance with the Declaration of Helsinki. Statistical Analysis Potential differences in the recorded demographic and clinical characteristics among patients with CCM reporting epileptic seizures, versus CCM patients without seizures, were first evaluated using chi- squared test for categorical variables, t-test and Kruskal-Wallis test for normally distributed and non-normally distributed continuous variables, respectively (Shapiro-Wilk test was used to assess the distribution of the continuous variables). The potential independent predictors of seizures were then evaluated using multivariate logistic regression. Covariates were selected for inclusion in final model using a stepwise forward process with the following inclusion criteria: p-value <0.15 at univariate analysis; clinical relevance; age, concomitant use of anti-platelets and b-blockers, and lesions volume forced to entry. The role of lesion volume was investigated both as a continuous variable in its original form and as an ordinal variable by categorizing volume into four groups represented with dummy variable: ≤11.9 mm 3 ; >11.9 to 80 mm 3 ; ≥80 to 300 mm 3 ; >300 mm 3 .A minimum events-to-variable ratio of 10 was maintained in multivariate modeling to avoid overfitting. The goodness-of-fit was checked using Hosmer-Lemeshow test, and the predictive power assessed through C-statistics (area under the Receiving Operator Curve). Additionally, we estimated the potential of: (a) lesions >11.9 mm3 (vs.≤11.9 mm3); (b) lesions >80 mm3 (vs.≤80 mm3); (c) lesions >300 mm3 (vs.≤300 mm3) to predict the onset of seizures computing summary estimates of sensitivity, specificity, positive and negative predictive values (PPV and NPV).95% Confidence Intervals (CI) for specificity and sensitivity and for PPV and NPV were computed according to the efficient-score method, corrected for continuity, described by Newcombe. Statistical significance was defined as a two-sided p-value<0.05, and all analyses were carried out using Stata, version 13.1 (Stata Corp., College Station, Texas, USA, 2013). Results We collected data on 230 patients, including 75 patients in the EG and 155 in the CG. No statistically significant differences were recorded between the two groups regarding sex, alcohol consumption, diabetes, mean BMI, menopause, history of MACE or trauma, anticoagulant drug use, or other pharmacological treatments (Table 1) . In the EG, mean age was significantly lower (39.0 vs 47.2 years; p=0.002), with a shorter median time from diagnosis to surgery (9.0 vs 17.0 months; p=0.020), absence of CCM1 mutations (0.0% vs 35.0%; p=0.005), and a lower prevalence of hypertension (12.0% vs 36.8%; p<0.001), antiplatelet use (6.7% vs 24.5%; p=0.001), and beta-blocker use (4.0% vs 21.3%; p=0.001) (Table 1). No statistically significant differences were observed between the two groups regarding Zabramski classification. Frontal (44% vs 25.8%; p=0.005) and temporal (29.3% vs 16.8%; p=0.03) locations were significantly more frequent in the EG, while multiple lesions were more common in the CG (44.5% vs 6.7%; p<0.001) (see Table 2).Higher lesion volumes were significantly associated with the EG (median volume 2100 mm³ vs 270 mm³; p<0.001), as were bleeding lesions (38.7% vs 20.0%; p=0.003) (Table 2) . No statistically significant difference in clinical outcomes measured by mRS was found between EG and CG (p=0.15).The outcome was good (0–2 points) in most patients (90.4%).Surgery was performed in 93.3% of EG patients, significantly more frequently than in the CG (58.1%; p<0.001) ( Table 3 ). Multivariate analysis confirmed lesion volume as an important predictor of epilepsy. The highest odds ratio (OR 86.4; 95% CI 9.94–751; p<0.001) was observed for lesions with volume between 80 and 300 mm³ (see Table 4).Bleeding was also a strong predictive factor for epilepsy occurrence (OR 60.3; 95% CI 6.50–558; p<0.001).Frontal or temporal lesion sites were confirmed as significant predictors (OR 6.34; 95% CI 2.99–113.4; p<0.001).In contrast, lower age and lower use of beta-blockers and antiplatelet drugs were not confirmed as independent predictors of epilepsy ( Table 4 ). Diagnostic accuracy analysis of lesion volumes ( Table 5, Figure 1 ) showed that a volume >11.9 mm³ was useful for excluding seizure risk due to high sensitivity and negative predictive value. A volume >80 mm³ provided the best balance between sensitivity and specificity, supporting its use for general screening. Finally, a volume >300 mm³ was highly specific and had a high positive predictive value, making it useful for confirming high-risk cases. Discussion Our results highlight several demographic and lesion-related features that significantly influence epilepsy risk in CCM patients. Univariate analysis comparing the EG and the CG showed that epileptic patients were significantly younger, despite similar sex distribution between cohorts. This reflects the current practice, as younger patients tend to present with seizures earlier in the disease course, leading to earlier diagnosis and surgical intervention. Notably, this finding shares common ground with the study by Zhang et al., which reported that age ≤44 years was associated with a higher risk of epilepsy [27]. Furthermore, the time from diagnosis to surgery is significantly shorter in the EG, supporting the idea that seizures are often the presenting symptom accelerating the time to surgical consult. Another noteworthy observation relies on the absence of familial CCM1 mutations among epileptic patients. While this protective association warrants attention, its underlying biological basis remains speculative. Additionally, smoking status appeared to be a relevant factor: current smokers were more prevalent among patients with epilepsy, whereas former smokers were significantly more frequent in the control group. In contrast, hypertension was more commonly found in the CG, plausibly reflecting the older age of the cohort. An intriguing finding emerged from our univariate analysis, as EG patients were less likely to be on beta-blockers or antiplatelet agents[1, 10, 16, 22].This pattern might suggest a protective effect, as some studies have reported that antiplatelet therapy may reduce micro- and macro-hemorrhages and the associated inflammatory cascade, while beta-blockers could indirectly modulate seizure threshold [7, 13, 17, 20, 23, 28]. On the other hand the age could be a confounding factors for this kind of association, older people are more likely to be on that kind of drugs. However, in our multivariate analysis these associations were not significant after adjusting for other variables.It appears these factors were confounded by lesion characteristics: for example, older patients and those on cardio-active medications may have more co-morbid vascular lesions but not necessarily more seizures. This is in agreement with the study by Zhang et al., as sex, obesity, cardiovascular history, or anticoagulant use did not differ between groups (epileptic vs control) [27].However, while beta-blockers and antiplatelet agents were not independent predictors in our cohort, this does not preclude potential indirect effects on lesion stability or comorbidity burden over longer follow-up, as suggested in longitudinal observational data [18]. Volumetry In our large multicenter cohort of 230 patients with CCMs, lesion volume emerged as a particularly important factor. Using an adapted ABC/2 method, lesion volume was stratified into quartiles [1, 2, 14]. Patients in the upper quartiles had much higher epilepsy risk: for example, lesions ≥80 mm³ had 86-fold greater odds of presenting with epilepsy than very small lesions (≤11.9 mm³). This suggests that larger CCMs, which likely produce a greater burden of hemosiderin and gliosis in adjacent cortex, are inherently more epileptogenic. Indeed, lesion volume may serve as a surrogate marker for the extent of chronic blood breakdown products, as prior studies have demonstrated that iron deposition increases neural irritability [15]. Clinically, this implies that quantitative volumetric assessment can enhance risk stratification: even moderate increases in CCM size markedly raise seizure risk. In fact, the logistic regression models confirmed lesion volume, symptomatic presentation, and cortical location as independent predictors of epilepsy. The diagnostic accuracy analysis of volume thresholds further supports its role in risk stratification, with different cut-offs offering varying balances between sensitivity and specificity [19]. Hemorrhagic Presentation and Lesion Topography Hemorrhage was a second key predictor of epilepsy in our cohort.A significantly higher proportion of EG lesions had bled (38.7% vs.20.0%, p=0.003, Table 2), and on multivariate analysis bleeding conferred an OR=60 for seizure presentation. This is biologically plausible: acute or chronic microhemorrhages release hemosiderin that can cause cortical hyperexcitability. Indeed, in an independent Chinese series by Zhang et al., 86% of seizures-associated CCMs showed a hemosiderin rim, and hemosiderin was a strong risk factor (OR=16.5)[15]. Similarly, lesion location in frontal and temporal lobes was significantly over-represented in the epilepsy group (44% vs.25.8% frontal, 29.3% vs.16.8% temporal; p=0.005 and p=0.03 respectively). This reinforces the concept that cortical involvement: mesial temporal and frontal regions predispose to seizures. Our multivariate model confirmed frontal/temporal site as an independent risk factor (OR=6.34). These findings align with prior studies showing that temporal lobe CCMs are highly epileptogenic. For example, Shih et al.found that temporal lesions accounted for the majority of cavernoma-related epilepsy and drug-resistant epilepsy [24]. By contrast, as reported by Dulamea et al., CCMs in deep or non-eloquent regions are less likely to cause seizures [18]. Our data thus support the view that hemorrhagic, superficially located CCMs carry the greatest seizure risk. Surgical Management and Clinical Outcomes We observed markedly higher rates of surgical resection in the epilepsy group (93.3% vs.58.1%, p<0.001).This likely reflects two factors: first, seizures themselves often prompt consideration of resection to achieve seizure control; and second, large or hemorrhagic lesions may be deemed safer or more urgent surgical targets. Notably, time to surgery was significantly shorter in EG. This indicates clinicians tended to operate sooner on seizure-presenting CCMs than on lesions found incidentally or after non-epileptic hemorrhage. Despite these management differences, the overall functional outcomes were similarly favorable in both groups (90.4% of patients had good outcome, mRS 0–2). However, it should be emphasized that our study did not rigorously collect seizure-specific outcome data, such as Engel class or long-term seizure freedom, beyond noting general disability scores. This is a limitation: Engel or ILAE outcome scales would more directly capture the impact of surgery on epilepsy control. Future studies should systematically record postoperative seizure status to correlate preoperative risk factors with surgical success. Clinical implications The clinical implications of our findings are twofold. First, they highlight that large, cortical, hemorrhagic CCMs require vigilant monitoring for seizures. Patients with such lesions may benefit from early neurosurgical consultation or empirical antiseizure therapy[5, 8, 9], given their high risk. Second, our results suggest that incorporating volumetric analysis into routine MRI assessment could improve risk stratification: for example, a lesion exceeding 80 mm³ should raise an alert for epilepsy risk [3, 4, 12, 21]. For future research, prospective studies are needed to validate these risk thresholds and to explore biological mechanisms. Advanced imaging techniques, such as quantitative susceptibility mapping (QSM) to measure iron deposition, might refine our understanding of how hemorrhagic burden correlates with epileptogenesis. Genetic and molecular studies could also determine whether certain CCM genotypes predispose more to seizures when combined with large lesion size. Strengths and Limitations A key strength of this work is its multicenter design with prospective/retrospective data from multiple Italian centers, yielding a large and diverse sample. This improves generalizability compared to single-center series. Another strength is the systematic volumetric classification of CCMs, an approach adapted from hemorrhage studies, which provided objective quantification of lesion size. Our volumetric cut-offs (≤11.9, 12–80, 80–299, ≥300 mm³) were data-driven and enabled us to detect the non-linear effect of size on seizure risk. Nonetheless, limitations exist. The study was observational and partly retrospective, which may introduce selection biases. Imaging protocols varied among centers, so volumetric data may have some measurement variability. We did not analyze some potentially relevant factors, such as presence of associated developmental venous anomalies or detailed genetic subtypes, which could influence epilepsy risk. Crucially, as noted, we did not capture long-term seizure outcomes in a standardized way, limiting our ability to link the identified predictors to postoperative seizure freedom. Also, our use of GOS scores was hampered by incomplete data, so we relied on mRS for functional status. Conclusion This study is the first to provide objective, data-driven volumetric thresholds for predicting epilepsy risk in cerebral cavernous malformations, demonstrating that a lesion volume ≥80 mm³ significantly increases seizure risk alongside hemorrhage and frontal/temporal location, while demographic and medical treatment factors are not independently predictive. By integrating lesion volume with cortical location and hemorrhagic status, our findings offer a novel and more precise approach to individualized risk stratification, supporting the routine inclusion of volumetric analysis in MRI evaluations to guide early management decisions. These findings should inform patient counseling and management, and they provide a foundation for future research into personalized risk assessment in CCM. Abbreviations Cerebral cavernous malformations (CCMs), modified Rankin Scale (mRS), Glasgow Outcome Scale (GOS), epilepsy group (EG), control group (CG), quantitative susceptibility mapping (QSM). Declarations Sources of Funding: This research received no specific grant from any funding. Acknowledge: None Conflict of interest: None Clinical trial number: Not applicable Disclosure: All authors have read and approved the submitted manuscript. The manuscript has not been submitted nor published elsewhere in whole or in part. The authors report no conflict of interest nor financial interest. Ethical statement: The study protocol was reviewed and approved by the Local Ethical Committee (approval ID 670/2021/Oss/AOUFe). All participating institutions adhered to standardized procedures for data collection, patient confidentiality, and ethical conduct in accordance with the Declaration of Helsinki. Authors' contributions: conception and design (CLS, AS), data collection (MP, GM, EMF), data analysis (CLS; EMF; AS), drafting (MP, EMF, AS, CLS), draft revision (CLS; GM; PDB), approval of final version (MP, CLS, AS, PDB; GM; EMF). References Albanese A, Sturiale CL, D’Alessandris QG, Capone G, Maira G (2009) Calcified extra-axial cavernoma involving lower cranial nerves: technical case report. Neurosurgery 64:onsE135-136; discussion onsE136. doi: 10.1227/01.NEU.0000335654.56346.B6 Baumann CR, Schuknecht B, Lo Russo G, Cossu M, Citterio A, Andermann F, Siegel AM (2006) Seizure outcome after resection of cavernous malformations is better when surrounding hemosiderin-stained brain also is removed. Epilepsia 47:563–566. doi: 10.1111/j.1528-1167.2006.00468.x Blackbourn LW, Kim M, Comardelle NJ, Reddy D (2025) Use of Anticoagulation for Secondary Stroke Prevention in Cerebral Cavernous Malformations: A Case Report. Cureus 17:e78913. doi: 10.7759/cureus.78913 Dashti SR, Hoffer A, Hu YC, Selman WR (2006) Molecular genetics of familial cerebral cavernous malformations. Neurosurg Focus 21:e2. doi: 10.3171/foc.2006.21.1.3 De Bonis P, Cavallo MA, Sturiale CL, Martellucci C, Flacco ME, Dughiero M, Auricchio AM, Ricciardi L, Raco A, Bortolotti C, Tosatto L, D’Andrea M, Ruggiero M, Mongardi L, Zona G, Fiaschi P, Cofano F, Garbossa D, Scerrati A (2021) Incidence of hemorrhagic cerebrovascular disease due to vascular malformations during the COVID-19 national quarantine in Italy. Clin Neurol Neurosurg 202:106503. doi: 10.1016/j.clineuro.2021.106503 Dulamea AO, Lupescu IC (2024) Cerebral cavernous malformations - An overview on genetics, clinical aspects and therapeutic strategies. J Neurol Sci 461:123044. doi: 10.1016/j.jns.2024.123044 Flemming KD, Link MJ, Christianson TJH, Brown RD (2013) Use of antithrombotic agents in patients with intracerebral cavernous malformations. J Neurosurg 118:43–46. doi: 10.3171/2012.8.JNS112050 Fontanella MM, Agosti E, Zanin L, di Bergamo LT, Doglietto F (2021) Cerebral cavernous malformation remnants after surgery: a single-center series with long-term bleeding risk analysis. Neurosurg Rev 44:2639–2645. doi: 10.1007/s10143-020-01436-7 Fontanella MM, Panciani PP, Spena G, Roca E, Migliorati K, Ambrosi C, Sturiale CL, Retta SF (2015) Professional athletes and cerebral cavernomas: an obstacle to overcome. J Sports Med Phys Fitness 55:1046–1047 Fontanella MM, Zanin L, Panciani P, Belotti F, Doglietto F, Cremonesi A, Migliorati K, Roca E, De Maria L, Franzin A, Vivaldi O, Griva F, Narducci A, Draghi R, Calbucci F, Borghesi I, Crobeddu E, Cossandi C, Fioravanti A, Arias JA, Scerrati A, De Bonis P, Locatelli D, Agosti E, Veiceschi P, Ceraudo M, Zona G, Gasparotti R, Terzi di Bergamo L, Rigamonti D (2022) Preliminary Validation of FoRCaSco: A New Grading System for Cerebral and Cerebellar Cavernomas. World Neurosurg 162:e597–e604. doi: 10.1016/j.wneu.2022.03.070 Haasdijk RA, Cheng C, Maat-Kievit AJ, Duckers HJ (2012) Cerebral cavernous malformations: from molecular pathogenesis to genetic counselling and clinical management. Eur J Hum Genet 20:134–140. doi: 10.1038/ejhg.2011.155 Hammen T, Romstöck J, Dörfler A, Kerling F, Buchfelder M, Stefan H (2007) Prediction of postoperative outcome with special respect to removal of hemosiderin fringe: a study in patients with cavernous haemangiomas associated with symptomatic epilepsy. Seizure 16:248–253. doi: 10.1016/j.seizure.2007.01.001 Ikramuddin S, Liu S, Ryan D, Hassani S, Hasan D, Feng W (2024) Propranolol or Beta-Blockers for Cerebral Cavernous Malformation: a Systematic Review and Meta-analysis of Literature in Both Preclinical and Clinical Studies. Transl Stroke Res 15:1088–1097. doi: 10.1007/s12975-023-01199-5 Jin Y, Zhao C, Zhang S, Zhang X, Qiu Y, Jiang J (2014) Seizure outcome after surgical resection of supratentorial cavernous malformations plus hemosiderin rim in patients with short duration of epilepsy. Clin Neurol Neurosurg 119:59–63. doi: 10.1016/j.clineuro.2014.01.013 Kothari RU, Brott T, Broderick JP, Barsan WG, Sauerbeck LR, Zuccarello M, Khoury J (1996) The ABCs of measuring intracerebral hemorrhage volumes. Stroke 27:1304–1305. doi: 10.1161/01.str.27.8.1304 Lanfranconi S, Scola E, Bertani GA, Zarino B, Pallini R, d’Alessandris G, Mazzon E, Marino S, Carriero MR, Scelzo E, Faragò G, Castori M, Fusco C, Petracca A, d’Agruma L, Tassi L, d’Orio P, Lampugnani MG, Nicolis EB, Vasamì A, Novelli D, Torri V, Meessen JMTA, Al-Shahi Salman R, Dejana E, Latini R, Treat-CCM Investigators (2020) Propranolol for familial cerebral cavernous malformation (Treat_CCM): study protocol for a randomized controlled pilot trial. Trials 21:401. doi: 10.1186/s13063-020-4202-x Lanfranconi S, Scola E, Meessen JMTA, Pallini R, Bertani GA, Al-Shahi Salman R, Dejana E, Latini R, Treat_CCM Investigators (2023) Safety and efficacy of propranolol for treatment of familial cerebral cavernous malformations (Treat_CCM): a randomised, open-label, blinded-endpoint, phase 2 pilot trial. Lancet Neurol 22:35–44. doi: 10.1016/S1474-4422(22)00409-4 Minuz P, Calabria S, Fava C (2014) Antiplatelet activity of β-blockers: new light on existing data. Br J Clin Pharmacol 78:937–939. doi: 10.1111/bcp.12438 Newcombe RG (1998) Two-sided confidence intervals for the single proportion: comparison of seven methods. Stat Med 17:857–872. doi: 10.1002/(sici)1097-0258(19980430)17:83.0.co;2-e Previch L, Lanzino G, Brown RD, Flemming KD (2022) The Influence of Select Medications on Prospective Hemorrhage Risk in Patients with Spinal or Cerebral Cavernous Malformations. World Neurosurg 163:e678–e683. doi: 10.1016/j.wneu.2022.03.101 Ruan D, Yu X-B, Shrestha S, Wang L, Chen G (2015) The Role of Hemosiderin Excision in Seizure Outcome in Cerebral Cavernous Malformation Surgery: A Systematic Review and Meta-Analysis. PLoS One 10:e0136619. doi: 10.1371/journal.pone.0136619 Scerrati A, Mantovani G, Travaglini F, Bradaschia L, De Bonis P, Farneti M, Cavallo MA, Dones F, Flacco ME, Auricchio AM, Benato A, Albanese A, Sturiale CL (2023) Bleeding risk evaluation in cerebral cavernous malformation, the role of medications, and hemorrhagic factors: a case-control study. Neurosurg Focus 55:E15. doi: 10.3171/2023.7.FOCUS23355 Schneble H-M, Soumare A, Hervé D, Bresson D, Guichard J-P, Riant F, Tournier-Lasserve E, Tzourio C, Chabriat H, Stapf C (2012) Antithrombotic therapy and bleeding risk in a prospective cohort study of patients with cerebral cavernous malformations. Stroke 43:3196–3199. doi: 10.1161/STROKEAHA.112.668533 Shih Y-C, Chou C-C, Peng S-J, Yu H-Y, Hsu SPC, Lin C-F, Lee C-C, Yang H-C, Chen Y-C, Kwan S-Y, Chen C, Wang S-J, Lin C-J, Lirng J-F, Shih Y-H, Yen D-J, Liu Y-T (2022) Clinical characteristics and long-term outcome of cerebral cavernous malformations-related epilepsy. Epilepsia 63:2056–2067. doi: 10.1111/epi.17309 Tripathi M, Ahuja CK, Aggarwal A, Mohindra S (2024) Is There Any “Unbled” Cavernoma? Neurol India 72:1119–1121. doi: 10.4103/neurol-india.NI_32_21 Weber J, Ebinger M, Audebert HJ (2015) Prehospital stroke care: telemedicine, thrombolysis and neuroprotection. Expert Rev Neurother 15:753–761. doi: 10.1586/14737175.2015.1051967 Zhang J, Deng X, Yuan Q, Fu P, Wang M, Wu G, Yang L, Yuan C, Du Z, Hu J (2023) Staged or simultaneous operations for ventriculoperitoneal shunt and cranioplasty: Evidence from a meta-analysis. CNS Neurosci Ther 29:3136–3149. doi: 10.1111/cns.14347 Zuurbier SM, Hickman CR, Tolias CS, Rinkel LA, Leyrer R, Flemming KD, Bervini D, Lanzino G, Wityk RJ, Schneble H-M, Sure U, Al-Shahi Salman R, Scottish Audit of Intracranial Vascular Malformations Steering Committee (2019) Long-term antithrombotic therapy and risk of intracranial haemorrhage from cerebral cavernous malformations: a population-based cohort study, systematic review, and meta-analysis. Lancet Neurol 18:935–941. doi: 10.1016/S1474-4422(19)30231-5 Tables Table 1 . Demography, clinical characteristics and pharmacological treatment overall and in CCM patients with versus without epileptic seizures. Overall sample Epilepsy No epilepsy Variables (n=230) (n=75) (n=155) p * Male gender, % 47.8 49.3 47.1 0.8 Mean age in years (SD) 44.5 (19.0) 39.0 (17.5) 47.2 (19.2) 0.002 Median time from diagnosis to surgery in months, (IQR) 12.7 (3.0-71.0) 9.0 (1.2-29.0) 17.0 (3.0-90.0) 0.020 Familial CCM mutations, % - CCM1 32.6 0.0 35.0 0.005 - CCM2 0.0 0.0 0.0 -- - CCM3 0.0 0.0 0.0 -- Smoking status, % - Current 7.9 10.8 6.4 0.07 - Former 9.6 0.0 14.2 <0.001 - Never 82.5 89.2 79.4 0.3 Alcohol drinking, % B 2.2 2.7 1.9 0.7 Diabetes, % 3.5 1.3 4.5 0.2 Hypertension, % 28.7 12.0 36.8 <0.001 Mean BMI (SD) 25.3 (3.4) 25.5 (3.8) 25.2 (3.2) 0.5 (n=120) (n=38) (n=82) Menopause status, % 28.3 23.7 30.5 0.06 (n=78) (n=3) (n=75) History of MACE, % 51.3 0.0 53.3 0.07 MACE type, % (n=40) (n=0) (n=40) -- - Stroke 5.0 0.0 5.0 - AMI 2.5 0.0 2.5 - Arrhythmias 22.5 0.0 22.5 - DVT/pulmonary embolism 12.5 0.0 12.5 - Other 57.2 0.0 57.2 Anti-platelet drugs use, % 18.7 6.7 24.5 0.001 Anticoagulant drugs use, % 0.6 - None 97.4 98.7 96.8 - TAO 1.7 1.3 1.9 - NAO 0.9 0.0 1.3 B-Blockers use, % 15.6 4.0 21.3 0.001 (N=78) (N=3) (N=75) Other pharmacologic treatments, % 96.2 100 96.0 0.7 SD: Standard deviation; IQR: Interquartile range; ANS: Autonomic nervous system; CNS: Central nervous system; MACE: Major adverse cardiovascular events; DVT: deep vein thrombosis; CCM: cerebral cavernous malformation genes; A More than one answer possible. B Including lesions with the following anatomical locations: thalamus, basal ganglia, insular, spinal and orbital. Table 2 . Radiological characteristics overall and in CCM patients with versus without epileptic seizures. Overall sample Epilepsy No epilepsy Variables (n=230) (n=75) (n=155) p * Zabramski classification, % (n=151) (n=71) (n=80) 0.050 - Accidental 0.0 2.8 0.0 - Type I 50.0 64.8 42.1 - Type II 47.5 28.2 54.7 - Type III 1.3 4.2 1.1 - Type IV 1.2 0.0 2.1 Presence of multiple lesions, % 33.2 6.7 44.5 <0.001 Trauma-associated lesion, % 3.0 4.0 2.6 0.6 Anatomic lesion site, % - Frontal 31.7 44.0 25.8 0.005 - Parietal 12.6 14.7 11.6 0.5 - Temporal 20.9 29.3 16.8 0.03 - Occipital 7.4 4.0 9.0 0.2 - Brain stem 12.6 0.0 18.7 <0.001 - Cerebellum 10.9 2.7 14.8 0.006 - Others B 3.9 5.3 3.2 0.4 Lesion volume in mm 3 : Median volume (IQR) 800 (120-3000) 2100 (800-5600) 270 (90-1200) <0.001 By quartiles of volume: - ≤11.9 mm 3 25.2 1.3 36.8 11.9 to 80 mm 3 27.0 25.3 27.7 0.7 - ≥80 to 300 mm 3 24.4 34.7 19.4 0.011 - >300 mm 3 23.5 38.7 16.1 <0.001 Bleeding lesion, % 26.7 38.7 20.0 0.003 SD: Standard deviation; IQR: Interquartile range; B Including lesions with the following anatomical locations: thalamus, basal ganglia, insular, spinal and orbital. Table 3 Clinical outcome overall and in CCM patients with versus without epileptic seizures. Overall sample Epilepsy No epilepsy Variables (n = 230) (n = 75) (n = 155) p * GOS score, % − 1 0.9 0.0 1.3 0.3 − 2 12.2 5.3 15.5 0.03 − 3 16.5 12.0 18.7 0.2 − 4 70.4 82.7 64.5 0.005 − 5 mRankin Scale: 0.15 − 0 50.0 46.7 51.6 − 1 32.6 40.0 29.0 − 2 7.8 5.3 9.0 − 3 7.0 5.3 7.7 − 4 0.9 0.0 1.3 − 5 0.9 2.7 0.0 − 6 0.8 0.0 1.3 Treated with surgery, % 69.6 93.3 58.1 < 0.001 GOS: Glasgow Outcome Scale. Table 4 Logistic regression model evaluating the potential predictors of epileptic seizures among subjects with cerebral cavernous malformations. Epileptic seizures % Adj. OR (95% CI) p Age, 10-year increase -- 1.11 (0.89–1.39) 0.3 Lesion volume: - ≤11.9 mm 3 1.7 1 (ref. cat.) -- - >11.9 to 80 mm 3 30.7 25.9 (3.16–213) 0.002 - ≥80 to 300 mm 3 46.4 86.4 (9.94–751) 300 mm 3 53.7 63.5 (7.63–528) < 0.001 Symptomatic lesion: - No 2.4 1 (ref. cat.) -- - Yes 39.4 60.3 (6.50–558) < 0.001 Frontal or temporal lesion site: - No 18.4 1 (ref. cat.) -- - Yes 45.5 6.34 (2.99–113.4) < 0.001 Anti-platelet drugs use: - No 37.4 1 (ref. cat.) -- - Yes 11.6 1.73 (0.29–10.3) 0.5 B-blockers drugs use: - No 37.1 1 (ref. cat.) -- - Yes 8.3 0.63 (0.30–1.63) 0.4 Adj.: adjusted; OR: Odds ratio; CI: Confidence Interval. The raw % is the proportion of subjects with the outcome among the exposed and unexposed patients (e.g. the proportion of subjects with seizures among those with asymptomatic or symptomatic lesions). Final model based upon 230 observations, with 75 successes. Area under the ROC curve = 0.88. Table 5 Diagnostic accuracy of each lesion volume cut-off to predict the onset of epileptic seizures: summary estimates of sensitivity, specificity, positive and negative predictive values (PPV and NPV). CI = Confidence interval. Lesion volume Sensitivity % (95% CI) Specificity % (95% CI) PPV % (95% CI) NPV % (95% CI) > 11.9 mm3 98.7 (92.8–100) 36.8 (29.2–44.9) 43.0 (35.5–50.8) 98.3 (90.8–100) > 80 mm3 73.3 (61.9–82.9) 64.5 (56.4–72.0) 50.0 (40.3–59.7) 83.3 (75.4–89.5) > 300 mm3 38.7 (27.6–50.6) 83.9 (77.1–89.3) 53.7 (39.6–67.4) 73.9 (66.7–80.2) Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 28 Mar, 2026 Read the published version in Neurosurgical Review → Version 1 posted Editorial decision: Revision requested 18 Dec, 2025 Reviews received at journal 13 Dec, 2025 Reviews received at journal 11 Dec, 2025 Reviews received at journal 09 Dec, 2025 Reviews received at journal 06 Dec, 2025 Reviews received at journal 06 Dec, 2025 Reviewers agreed at journal 03 Dec, 2025 Reviews received at journal 01 Dec, 2025 Reviewers agreed at journal 26 Nov, 2025 Reviewers agreed at journal 26 Nov, 2025 Reviewers agreed at journal 25 Nov, 2025 Reviewers agreed at journal 24 Nov, 2025 Reviewers agreed at journal 24 Nov, 2025 Reviewers agreed at journal 10 Sep, 2025 Reviewers agreed at journal 23 Aug, 2025 Reviewers invited by journal 22 Jul, 2025 Editor assigned by journal 20 Jul, 2025 Submission checks completed at journal 16 Jul, 2025 First submitted to journal 14 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7123042","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":489599796,"identity":"3b4ac1f7-9e94-4075-abe3-65d047612e30","order_by":0,"name":"Carmelo Lucio Sturiale","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDklEQVRIie2Rv2rDMBCHzxycF6daFQL2K5wxhAx9GJlCMhUCXTIVl0CmQNeWvkQeIUWQLKGPUARdOqabhw49ufTPYLsdC9U3ieM+6e4ngEDgz8IAJwCRM6xTQCmYuYbm0KeQtPBxcVq8K+yVXqdRaHhzmJbVxyVdz6g7u3P1/DGjuILRYGVnm/3g6dnxJIVYbdsU/TCd5Wu+yFfJFgpRzjc2Hk9ksKJrME6S8QjYGNIGzrxyuyRiUcrqRyVzYP1gw98rGqIrWd8oJHR9ij6Q38XILuUSJOT8Gol8yAUhcmtia5TEXk2mYruvpTMjtcOXenGZKnXvWp9pfqQhqj4r+nu9R/kCj93dgUAg8A95A6DjTA6cUQ1fAAAAAElFTkSuQmCC","orcid":"","institution":"Fondazione Policlinico Universitario A. Gemelli IRCCS, Università Cattolica del Sacro Cuore","correspondingAuthor":true,"prefix":"","firstName":"Carmelo","middleName":"Lucio","lastName":"Sturiale","suffix":""},{"id":489599797,"identity":"81c46270-88cd-4650-8b1d-54df1d8d768e","order_by":1,"name":"Matteo Palermo","email":"","orcid":"","institution":"Fondazione Policlinico Universitario A. Gemelli IRCCS, Università Cattolica del Sacro Cuore","correspondingAuthor":false,"prefix":"","firstName":"Matteo","middleName":"","lastName":"Palermo","suffix":""},{"id":489599798,"identity":"5f1bac9d-747c-4df8-b158-169f0da9cd15","order_by":2,"name":"Maria Elena Flacco","email":"","orcid":"","institution":"University of Ferrara","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Elena","lastName":"Flacco","suffix":""},{"id":489599799,"identity":"e9870a85-3df0-4529-a9c8-0cf85ad0234a","order_by":3,"name":"Giorgio Mantovani","email":"","orcid":"","institution":"University of Ferrara","correspondingAuthor":false,"prefix":"","firstName":"Giorgio","middleName":"","lastName":"Mantovani","suffix":""},{"id":489599800,"identity":"dec210fe-6d81-4980-89d1-419089dc9acf","order_by":4,"name":"Pasquale De Bonis","email":"","orcid":"","institution":"University of Ferrara","correspondingAuthor":false,"prefix":"","firstName":"Pasquale","middleName":"","lastName":"De Bonis","suffix":""},{"id":489599801,"identity":"704f294c-a159-4fa1-ac67-2be956fd3fee","order_by":5,"name":"Alba Scerrati","email":"","orcid":"","institution":"University of Ferrara","correspondingAuthor":false,"prefix":"","firstName":"Alba","middleName":"","lastName":"Scerrati","suffix":""}],"badges":[],"createdAt":"2025-07-14 16:10:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7123042/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7123042/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10143-026-04246-5","type":"published","date":"2026-03-28T16:13:25+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87693582,"identity":"c4e2eec3-948e-420b-ab2e-2dcd5540b42e","added_by":"auto","created_at":"2025-07-28 05:32:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":54857,"visible":true,"origin":"","legend":"\u003cp\u003eDiagnostic Accuracy Metrics by Lesion Volume Cut-off\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7123042/v1/aea8272059a1aa4b0b52f578.png"},{"id":105755032,"identity":"49e0d74b-4ce2-4c24-9b1c-04f40a0ea21a","added_by":"auto","created_at":"2026-03-30 16:24:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1024978,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7123042/v1/6b043be4-33ab-471a-8df5-1d20eed37e51.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predictors of epilepsy as presenting symptom of cerebral cavernomas","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCerebral cavernous malformations (CCMs) are vascular malformations composed of clusters of dilated, thin-walled capillaries lacking intervening brain parenchyma [25]. These lesions are relatively common, with an estimated prevalence of about 0.1\u0026ndash;0.5% in the general population, and many are discovered incidentally on MRI [11]. Although often incidentally discovered, sometimes symptomatic CCMs may cause significant ictal neurologic events. Their fragile vessels, in fact, predispose to micro- or macro-hemorrhages, resulting in possible focal deficits depending on their topography; other times, however, the clinical onset may be characterized by sudden partial or generalized tonic-clonic epileptic seizures.\u003c/p\u003e\n\u003cp\u003eAmong symptomatic CCMs, epileptic seizures are one of the most frequent and disabling presentations, which may occur in up to roughly 40% of patients with cavernous angiomas, with some series report rates approaching 70\u0026ndash;80% [25]. In these cases, epilepsy is the initial clinical manifestation that leads to the diagnosis of a cavernoma, and requires a long-term management, substantially contributing to patient morbidity [7, 25]\u003c/p\u003e\n\u003cp\u003eSeveral lesion characteristics are known to influence the risk of epilepsy. Lesion location is considered particularly important: CCMs involving the cerebral cortex, in fact, especially in the temporal or frontal lobes, appear highly epileptogenic. Larger lesions and those surrounded by hemosiderin-laden gliotic tissue are also thought to amplify cortical irritability. In summary, classic risk factors for CCM‐related seizures include cortical location, large lesion size/volume, and evidence of prior hemorrhage with hemosiderin deposition [13, 17, 23]. Despite these observations, the quantitative contributions of lesion size and volume to epilepsy risk remain poorly defined. Most prior studies have described demographic and radiological correlates of seizure occurrence in CCMs, but few have rigorously evaluated how cavernoma volume predicts epilepsy. In particular, no robust volumetric threshold has been established to stratify seizure risk [6, 13, 24, 26]. The lack of systematic volume-based analysis means that clinicians currently have no objective cut-off values to guide individualized risk assessment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe present study was therefore designed to address this gap. We aimed to quantify the predictive role of cavernoma volume for epilepsy as the first clinical manifestation of CCM. We also sought optimal volumetric cut-offs that maximize sensitivity and specificity for epilepsy risk. By establishing clear thresholds and clarifying how cavernoma volume and location influence seizure propensity, this work will facilitate more precise risk stratification and inform clinical decision-making in the management of patients with CCM.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis is a non-profit, national, multicenter case-control study combining retrospective and prospective data collection across participating centers. The study protocol was reviewed and approved by the Local Ethical Committee (approval ID 670/2021/Oss/AOUFe). All participating institutions adhered to standardized procedures for data collection, patient confidentiality, and ethical conduct in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eInclusion criteria\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePatients older than 18 years with either a previous or new diagnosis of CCM confirmed by neuroimaging (single CCM, multiple CCMs, or familial CCM) were included. We collected data on CCM characteristics (number, location, Zabramski classification, hemorrhagic events), prior therapies, major adverse cardiovascular events (MACE), alcohol and tobacco use, comorbidities (e.g., diabetes, obesity, hypertension), modified Rankin Scale (mRS) and Glasgow Outcome Scale (GOS) scores, and surgical treatment. All medications were recorded.\u003c/p\u003e\n\u003cp\u003eLesion volume was calculated using an adapted version of the ABC/2 method for intracerebral hemorrhage volume measurement [15] and categorized into quartiles as follows: \u0026lt;11.9 mm\u0026sup3;, 11.9\u0026ndash;79 mm\u0026sup3;, 80\u0026ndash;299 mm\u0026sup3;, and \u0026gt;300 mm\u0026sup3;.\u003c/p\u003e\n\u003cp\u003eIn the epilepsy group (EG), we enrolled patients whose first clinical manifestation was an epileptic seizure. The control group (CG) included patients whose first presentation was a different clinical manifestation, either neurological deficit due to cerebral hemorrhage or headache, or an incidental finding.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEthical statement and patient consent\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was reviewed and approved by the Local Ethical Committee (approval ID 670/2021/Oss/AOUFe). Patient consent was not required by our institution. All participating institutions adhered to standardized procedures for data collection, patient confidentiality, and ethical conduct in accordance with the Declaration of Helsinki.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eStatistical Analysis\u0026nbsp;\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003ePotential differences in the recorded demographic and clinical characteristics among patients with CCM reporting epileptic seizures, versus CCM patients without seizures, were first evaluated using chi- squared test for categorical variables, t-test and Kruskal-Wallis test for normally distributed and non-normally distributed continuous variables, respectively (Shapiro-Wilk test was used to assess the distribution of the continuous variables).\u003c/p\u003e\n\u003cp\u003eThe potential independent predictors of seizures were then evaluated using multivariate logistic regression. Covariates were selected for inclusion in final model using a stepwise forward process with the following inclusion criteria: p-value \u0026lt;0.15 at univariate analysis; clinical relevance; age, concomitant use of anti-platelets and b-blockers, and lesions volume forced to entry. The role of lesion volume was investigated both as a continuous variable in its original form and as an ordinal variable by categorizing volume into four groups represented with dummy variable: \u0026le;11.9 mm\u003csup\u003e3\u003c/sup\u003e; \u0026gt;11.9 to 80 mm\u003csup\u003e3\u003c/sup\u003e; \u0026ge;80 to 300 mm\u003csup\u003e3\u003c/sup\u003e; \u0026gt;300 mm\u003csup\u003e3\u003c/sup\u003e.A minimum events-to-variable ratio of 10 was maintained in multivariate modeling to avoid overfitting. The goodness-of-fit was checked using Hosmer-Lemeshow test, and the predictive power assessed through C-statistics (area under the Receiving Operator Curve).\u003c/p\u003e\n\u003cp\u003eAdditionally, we estimated the potential of: (a) lesions \u0026gt;11.9 mm3 (vs.\u0026le;11.9 mm3); (b) lesions \u0026gt;80 mm3 (vs.\u0026le;80 mm3); (c) lesions \u0026gt;300 mm3 (vs.\u0026le;300 mm3) to predict the onset of seizures computing summary estimates of sensitivity, specificity, positive and negative predictive values (PPV and NPV).95% Confidence Intervals (CI) for specificity and sensitivity and for PPV and NPV were computed according to the efficient-score method, corrected for continuity, described by Newcombe. Statistical significance was defined as a two-sided p-value\u0026lt;0.05, and all analyses were carried out using Stata, version 13.1 (Stata Corp., College Station, Texas, USA, 2013).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eWe collected data on 230 patients, including 75 patients in the EG and 155 in the CG.\u003c/p\u003e\n\u003cp\u003eNo statistically significant differences were recorded between the two groups regarding sex, alcohol consumption, diabetes, mean BMI, menopause, history of MACE or trauma, anticoagulant drug use, or other pharmacological treatments \u003cstrong\u003e(Table 1)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eIn the EG, mean age was significantly lower (39.0 vs 47.2 years; p=0.002), with a shorter median time from diagnosis to surgery (9.0 vs 17.0 months; p=0.020), absence of CCM1 mutations (0.0% vs 35.0%; p=0.005), and a lower prevalence of hypertension (12.0% vs 36.8%; p\u0026lt;0.001), antiplatelet use (6.7% vs 24.5%; p=0.001), and beta-blocker use (4.0% vs 21.3%; p=0.001) \u003cstrong\u003e(Table 1).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo statistically significant differences were observed between the two groups regarding Zabramski classification. Frontal (44% vs 25.8%; p=0.005) and temporal (29.3% vs 16.8%; p=0.03) locations were significantly more frequent in the EG, while multiple lesions were more common in the CG (44.5% vs 6.7%; p\u0026lt;0.001) (see Table 2).Higher lesion volumes were significantly associated with the EG (median volume 2100 mm\u0026sup3; vs 270 mm\u0026sup3;; p\u0026lt;0.001), as were bleeding lesions (38.7% vs 20.0%; p=0.003) \u003cstrong\u003e(Table 2)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eNo statistically significant difference in clinical outcomes measured by mRS was found between EG and CG (p=0.15).The outcome was good (0\u0026ndash;2 points) in most patients (90.4%).Surgery was performed in 93.3% of EG patients, significantly more frequently than in the CG (58.1%; p\u0026lt;0.001) (\u003cstrong\u003eTable 3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eMultivariate analysis confirmed lesion volume as an important predictor of epilepsy. The highest odds ratio (OR 86.4; 95% CI 9.94\u0026ndash;751; p\u0026lt;0.001) was observed for lesions with volume between 80 and 300 mm\u0026sup3; (see Table 4).Bleeding was also a strong predictive factor for epilepsy occurrence (OR 60.3; 95% CI 6.50\u0026ndash;558; p\u0026lt;0.001).Frontal or temporal lesion sites were confirmed as significant predictors (OR 6.34; 95% CI 2.99\u0026ndash;113.4; p\u0026lt;0.001).In contrast, lower age and lower use of beta-blockers and antiplatelet drugs were not confirmed as independent predictors of epilepsy (\u003cstrong\u003eTable 4\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eDiagnostic accuracy analysis of lesion volumes (\u003cstrong\u003eTable 5, Figure 1\u003c/strong\u003e) showed that a volume \u0026gt;11.9 mm\u0026sup3; was useful for excluding seizure risk due to high sensitivity and negative predictive value. A volume \u0026gt;80 mm\u0026sup3; provided the best balance between sensitivity and specificity, supporting its use for general screening. Finally, a volume \u0026gt;300 mm\u0026sup3; was highly specific and had a high positive predictive value, making it useful for confirming high-risk cases.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur results highlight several demographic and lesion-related features that significantly influence epilepsy risk in CCM patients. Univariate analysis comparing the EG and the CG showed that epileptic patients were significantly younger, despite similar sex distribution between cohorts. This reflects the current practice, as younger patients tend to present with seizures earlier in the disease course, leading to earlier diagnosis and surgical intervention. Notably, this finding shares common ground with the study by Zhang et al., which reported that age \u0026le;44 years was associated with a higher risk of epilepsy [27].\u003c/p\u003e\n\u003cp\u003eFurthermore, the time from diagnosis to surgery is significantly shorter in the EG, supporting the idea that seizures are often the presenting symptom accelerating the time to surgical consult. Another noteworthy observation relies on the absence of familial CCM1 mutations among epileptic patients. While this protective association warrants attention, its underlying biological basis remains speculative.\u003c/p\u003e\n\u003cp\u003eAdditionally, smoking status appeared to be a relevant factor: current smokers were more prevalent among patients with epilepsy, whereas former smokers were significantly more frequent in the control group. In contrast, hypertension was more commonly found in the CG, plausibly reflecting the older age of the cohort.\u003c/p\u003e\n\u003cp\u003eAn intriguing finding emerged from our univariate analysis, as EG patients were less likely to be on beta-blockers or antiplatelet agents[1, 10, 16, 22].This pattern might suggest a protective effect, as some studies have reported that antiplatelet therapy may reduce micro- and macro-hemorrhages and the associated inflammatory cascade, while beta-blockers could indirectly modulate seizure threshold [7, 13, 17, 20, 23, 28]. On the other hand the age could be a confounding factors for this kind of association, older people are more likely to be on that kind of drugs.\u0026nbsp;However, in our\u0026nbsp;multivariate analysis these associations were not significant after adjusting for other variables.It appears these factors were confounded by lesion characteristics: for example, older patients and those on cardio-active medications may have more co-morbid vascular lesions but not necessarily more seizures. This is in agreement with the study by Zhang et al., as sex, obesity, cardiovascular history, or anticoagulant use did not differ between groups (epileptic vs control) [27].However, while beta-blockers and antiplatelet agents were not independent predictors in our cohort, this does not preclude potential indirect effects on lesion stability or comorbidity burden over longer follow-up, as suggested in longitudinal observational data [18].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eVolumetry\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn our large multicenter cohort of 230 patients with CCMs, lesion volume emerged as a particularly important factor. Using an adapted ABC/2 method, lesion volume was stratified into quartiles [1, 2, 14]. Patients in the upper quartiles had much higher epilepsy risk: for example, lesions \u0026ge;80 mm\u0026sup3; had 86-fold greater odds of presenting with epilepsy than very small lesions (\u0026le;11.9 mm\u0026sup3;). This suggests that larger CCMs, which likely produce a greater burden of hemosiderin and gliosis in adjacent cortex, are inherently more epileptogenic. Indeed, lesion volume may serve as a surrogate marker for the extent of chronic blood breakdown products, as prior studies have demonstrated that iron deposition increases neural irritability [15]. Clinically, this implies that quantitative volumetric assessment can enhance risk stratification: even moderate increases in CCM size markedly raise seizure risk. In fact, the logistic regression models confirmed lesion volume, symptomatic presentation, and cortical location as independent predictors of epilepsy. The diagnostic accuracy analysis of volume thresholds further supports its role in risk stratification, with different cut-offs offering varying balances between sensitivity and specificity [19].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHemorrhagic Presentation and Lesion Topography\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eHemorrhage was a second key predictor of epilepsy in our cohort.A significantly higher proportion of EG lesions had bled (38.7% vs.20.0%, p=0.003, Table 2), and on multivariate analysis bleeding conferred an OR=60 for seizure presentation. This is biologically plausible: acute or chronic microhemorrhages release hemosiderin that can cause cortical hyperexcitability. Indeed, in an independent Chinese series by Zhang et al., 86% of seizures-associated CCMs showed a hemosiderin rim, and hemosiderin was a strong risk factor (OR=16.5)[15]. Similarly, lesion location in frontal and temporal lobes was significantly over-represented in the epilepsy group (44% vs.25.8% frontal, 29.3% vs.16.8% temporal; p=0.005 and p=0.03 respectively). This reinforces the concept that cortical involvement: mesial temporal and frontal regions predispose to seizures. Our multivariate model confirmed frontal/temporal site as an independent risk factor (OR=6.34). These findings align with prior studies showing that temporal lobe CCMs are highly epileptogenic. For example, Shih et al.found that temporal lesions accounted for the majority of cavernoma-related epilepsy and drug-resistant epilepsy [24]. By contrast, as reported by Dulamea et al., CCMs in deep or non-eloquent regions are less likely to cause seizures [18]. Our data thus support the view that hemorrhagic, superficially located CCMs carry the greatest seizure risk.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSurgical Management and Clinical Outcomes\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe observed markedly higher rates of surgical resection in the epilepsy group (93.3% vs.58.1%, p\u0026lt;0.001).This likely reflects two factors: first, seizures themselves often prompt consideration of resection to achieve seizure control; and second, large or hemorrhagic lesions may be deemed safer or more urgent surgical targets. Notably, time to surgery was significantly shorter in EG. This indicates clinicians tended to operate sooner on seizure-presenting CCMs than on lesions found incidentally or after non-epileptic hemorrhage. Despite these management differences, the overall functional outcomes were similarly favorable in both groups (90.4% of patients had good outcome, mRS 0\u0026ndash;2). However, it should be emphasized that our study did not rigorously collect seizure-specific outcome data, such as Engel class or long-term seizure freedom, beyond noting general disability scores. This is a limitation: Engel or ILAE outcome scales would more directly capture the impact of surgery on epilepsy control. Future studies should systematically record postoperative seizure status to correlate preoperative risk factors with surgical success.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eClinical implications\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe clinical implications of our findings are twofold. First, they highlight that large, cortical, hemorrhagic CCMs require vigilant monitoring for seizures. Patients with such lesions may benefit from early neurosurgical consultation or empirical antiseizure therapy[5, 8, 9], given their high risk. Second, our results suggest that incorporating volumetric analysis into routine MRI assessment could improve risk stratification: for example, a lesion exceeding 80 mm\u0026sup3; should raise an alert for epilepsy risk [3, 4, 12, 21].\u003c/p\u003e\n\u003cp\u003eFor future research, prospective studies are needed to validate these risk thresholds and to explore biological mechanisms. Advanced imaging techniques, such as quantitative susceptibility mapping (QSM) to measure iron deposition, might refine our understanding of how hemorrhagic burden correlates with epileptogenesis. Genetic and molecular studies could also determine whether certain CCM genotypes predispose more to seizures when combined with large lesion size.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStrengths and Limitations\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA key strength of this work is its multicenter design with prospective/retrospective data from multiple Italian centers, yielding a large and diverse sample. This improves generalizability compared to single-center series. Another strength is the systematic volumetric classification of CCMs, an approach adapted from hemorrhage studies, which provided objective quantification of lesion size. Our volumetric cut-offs (\u0026le;11.9, 12\u0026ndash;80, 80\u0026ndash;299, \u0026ge;300 mm\u0026sup3;) were data-driven and enabled us to detect the non-linear effect of size on seizure risk. Nonetheless, limitations exist. The study was observational and partly retrospective, which may introduce selection biases. Imaging protocols varied among centers, so volumetric data may have some measurement variability. We did not analyze some potentially relevant factors, such as presence of associated developmental venous anomalies or detailed genetic subtypes, which could influence epilepsy risk. Crucially, as noted, we did not capture long-term seizure outcomes in a standardized way, limiting our ability to link the identified predictors to postoperative seizure freedom. Also, our use of GOS scores was hampered by incomplete data, so we relied on mRS for functional status.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study is the first to provide objective, data-driven volumetric thresholds for predicting epilepsy risk in cerebral cavernous malformations, demonstrating that a lesion volume \u0026ge;80 mm\u0026sup3; significantly increases seizure risk alongside hemorrhage and frontal/temporal location, while demographic and medical treatment factors are not independently predictive.\u003c/p\u003e\n\u003cp\u003eBy integrating lesion volume with cortical location and hemorrhagic status, our findings offer a novel and more precise approach to individualized risk stratification, supporting the routine inclusion of volumetric analysis in MRI evaluations to guide early management decisions.\u003c/p\u003e\n\u003cp\u003eThese findings should inform patient counseling and management, and they provide a foundation for future research into personalized risk assessment in CCM.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCerebral cavernous malformations (CCMs), modified Rankin Scale (mRS), Glasgow Outcome Scale (GOS), epilepsy group (EG), control group (CG), quantitative susceptibility mapping (QSM).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eSources of Funding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledge:\u003c/strong\u003e None\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u003c/strong\u003e None\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure:\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eAll authors have read and approved the submitted manuscript.\u003c/li\u003e\n \u003cli\u003eThe manuscript has not been submitted nor published elsewhere in whole or in part.\u003c/li\u003e\n \u003cli\u003eThe authors report no conflict of interest nor financial interest.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eEthical statement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was reviewed and approved by the Local Ethical Committee (approval ID 670/2021/Oss/AOUFe). All participating institutions adhered to standardized procedures for data collection, patient confidentiality, and ethical conduct in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003econception and design (CLS, AS), data collection (MP, GM, EMF), data analysis (CLS; EMF; AS), drafting (MP, EMF, AS, CLS), draft revision (CLS; GM; PDB), approval of final version (MP, CLS, AS, PDB; GM; EMF).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlbanese A, Sturiale CL, D\u0026rsquo;Alessandris QG, Capone G, Maira G (2009) Calcified extra-axial cavernoma involving lower cranial nerves: technical case report. Neurosurgery 64:onsE135-136; discussion onsE136. doi: 10.1227/01.NEU.0000335654.56346.B6\u003c/li\u003e\n\u003cli\u003eBaumann CR, Schuknecht B, Lo Russo G, Cossu M, Citterio A, Andermann F, Siegel AM (2006) Seizure outcome after resection of cavernous malformations is better when surrounding hemosiderin-stained brain also is removed. Epilepsia 47:563\u0026ndash;566. doi: 10.1111/j.1528-1167.2006.00468.x\u003c/li\u003e\n\u003cli\u003eBlackbourn LW, Kim M, Comardelle NJ, Reddy D (2025) Use of Anticoagulation for Secondary Stroke Prevention in Cerebral Cavernous Malformations: A Case Report. Cureus 17:e78913. doi: 10.7759/cureus.78913\u003c/li\u003e\n\u003cli\u003eDashti SR, Hoffer A, Hu YC, Selman WR (2006) Molecular genetics of familial cerebral cavernous malformations. Neurosurg Focus 21:e2. doi: 10.3171/foc.2006.21.1.3\u003c/li\u003e\n\u003cli\u003eDe Bonis P, Cavallo MA, Sturiale CL, Martellucci C, Flacco ME, Dughiero M, Auricchio AM, Ricciardi L, Raco A, Bortolotti C, Tosatto L, D\u0026rsquo;Andrea M, Ruggiero M, Mongardi L, Zona G, Fiaschi P, Cofano F, Garbossa D, Scerrati A (2021) Incidence of hemorrhagic cerebrovascular disease due to vascular malformations during the COVID-19 national quarantine in Italy. Clin Neurol Neurosurg 202:106503. doi: 10.1016/j.clineuro.2021.106503\u003c/li\u003e\n\u003cli\u003eDulamea AO, Lupescu IC (2024) Cerebral cavernous malformations - An overview on genetics, clinical aspects and therapeutic strategies. J Neurol Sci 461:123044. doi: 10.1016/j.jns.2024.123044\u003c/li\u003e\n\u003cli\u003eFlemming KD, Link MJ, Christianson TJH, Brown RD (2013) Use of antithrombotic agents in patients with intracerebral cavernous malformations. J Neurosurg 118:43\u0026ndash;46. doi: 10.3171/2012.8.JNS112050\u003c/li\u003e\n\u003cli\u003eFontanella MM, Agosti E, Zanin L, di Bergamo LT, Doglietto F (2021) Cerebral cavernous malformation remnants after surgery: a single-center series with long-term bleeding risk analysis. Neurosurg Rev 44:2639\u0026ndash;2645. doi: 10.1007/s10143-020-01436-7\u003c/li\u003e\n\u003cli\u003eFontanella MM, Panciani PP, Spena G, Roca E, Migliorati K, Ambrosi C, Sturiale CL, Retta SF (2015) Professional athletes and cerebral cavernomas: an obstacle to overcome. J Sports Med Phys Fitness 55:1046\u0026ndash;1047\u003c/li\u003e\n\u003cli\u003eFontanella MM, Zanin L, Panciani P, Belotti F, Doglietto F, Cremonesi A, Migliorati K, Roca E, De Maria L, Franzin A, Vivaldi O, Griva F, Narducci A, Draghi R, Calbucci F, Borghesi I, Crobeddu E, Cossandi C, Fioravanti A, Arias JA, Scerrati A, De Bonis P, Locatelli D, Agosti E, Veiceschi P, Ceraudo M, Zona G, Gasparotti R, Terzi di Bergamo L, Rigamonti D (2022) Preliminary Validation of FoRCaSco: A New Grading System for Cerebral and Cerebellar Cavernomas. World Neurosurg 162:e597\u0026ndash;e604. doi: 10.1016/j.wneu.2022.03.070\u003c/li\u003e\n\u003cli\u003eHaasdijk RA, Cheng C, Maat-Kievit AJ, Duckers HJ (2012) Cerebral cavernous malformations: from molecular pathogenesis to genetic counselling and clinical management. Eur J Hum Genet 20:134\u0026ndash;140. doi: 10.1038/ejhg.2011.155\u003c/li\u003e\n\u003cli\u003eHammen T, Romst\u0026ouml;ck J, D\u0026ouml;rfler A, Kerling F, Buchfelder M, Stefan H (2007) Prediction of postoperative outcome with special respect to removal of hemosiderin fringe: a study in patients with cavernous haemangiomas associated with symptomatic epilepsy. Seizure 16:248\u0026ndash;253. doi: 10.1016/j.seizure.2007.01.001\u003c/li\u003e\n\u003cli\u003eIkramuddin S, Liu S, Ryan D, Hassani S, Hasan D, Feng W (2024) Propranolol or Beta-Blockers for Cerebral Cavernous Malformation: a Systematic Review and Meta-analysis of Literature in Both Preclinical and Clinical Studies. Transl Stroke Res 15:1088\u0026ndash;1097. doi: 10.1007/s12975-023-01199-5\u003c/li\u003e\n\u003cli\u003eJin Y, Zhao C, Zhang S, Zhang X, Qiu Y, Jiang J (2014) Seizure outcome after surgical resection of supratentorial cavernous malformations plus hemosiderin rim in patients with short duration of epilepsy. Clin Neurol Neurosurg 119:59\u0026ndash;63. doi: 10.1016/j.clineuro.2014.01.013\u003c/li\u003e\n\u003cli\u003eKothari RU, Brott T, Broderick JP, Barsan WG, Sauerbeck LR, Zuccarello M, Khoury J (1996) The ABCs of measuring intracerebral hemorrhage volumes. Stroke 27:1304\u0026ndash;1305. doi: 10.1161/01.str.27.8.1304\u003c/li\u003e\n\u003cli\u003eLanfranconi S, Scola E, Bertani GA, Zarino B, Pallini R, d\u0026rsquo;Alessandris G, Mazzon E, Marino S, Carriero MR, Scelzo E, Farag\u0026ograve; G, Castori M, Fusco C, Petracca A, d\u0026rsquo;Agruma L, Tassi L, d\u0026rsquo;Orio P, Lampugnani MG, Nicolis EB, Vasam\u0026igrave; A, Novelli D, Torri V, Meessen JMTA, Al-Shahi Salman R, Dejana E, Latini R, Treat-CCM Investigators (2020) Propranolol for familial cerebral cavernous malformation (Treat_CCM): study protocol for a randomized controlled pilot trial. Trials 21:401. doi: 10.1186/s13063-020-4202-x\u003c/li\u003e\n\u003cli\u003eLanfranconi S, Scola E, Meessen JMTA, Pallini R, Bertani GA, Al-Shahi Salman R, Dejana E, Latini R, Treat_CCM Investigators (2023) Safety and efficacy of propranolol for treatment of familial cerebral cavernous malformations (Treat_CCM): a randomised, open-label, blinded-endpoint, phase 2 pilot trial. Lancet Neurol 22:35\u0026ndash;44. doi: 10.1016/S1474-4422(22)00409-4\u003c/li\u003e\n\u003cli\u003eMinuz P, Calabria S, Fava C (2014) Antiplatelet activity of \u0026beta;-blockers: new light on existing data. Br J Clin Pharmacol 78:937\u0026ndash;939. doi: 10.1111/bcp.12438\u003c/li\u003e\n\u003cli\u003eNewcombe RG (1998) Two-sided confidence intervals for the single proportion: comparison of seven methods. Stat Med 17:857\u0026ndash;872. doi: 10.1002/(sici)1097-0258(19980430)17:8\u0026lt;857::aid-sim777\u0026gt;3.0.co;2-e\u003c/li\u003e\n\u003cli\u003ePrevich L, Lanzino G, Brown RD, Flemming KD (2022) The Influence of Select Medications on Prospective Hemorrhage Risk in Patients with Spinal or Cerebral Cavernous Malformations. World Neurosurg 163:e678\u0026ndash;e683. doi: 10.1016/j.wneu.2022.03.101\u003c/li\u003e\n\u003cli\u003eRuan D, Yu X-B, Shrestha S, Wang L, Chen G (2015) The Role of Hemosiderin Excision in Seizure Outcome in Cerebral Cavernous Malformation Surgery: A Systematic Review and Meta-Analysis. PLoS One 10:e0136619. doi: 10.1371/journal.pone.0136619\u003c/li\u003e\n\u003cli\u003eScerrati A, Mantovani G, Travaglini F, Bradaschia L, De Bonis P, Farneti M, Cavallo MA, Dones F, Flacco ME, Auricchio AM, Benato A, Albanese A, Sturiale CL (2023) Bleeding risk evaluation in cerebral cavernous malformation, the role of medications, and hemorrhagic factors: a case-control study. Neurosurg Focus 55:E15. doi: 10.3171/2023.7.FOCUS23355\u003c/li\u003e\n\u003cli\u003eSchneble H-M, Soumare A, Herv\u0026eacute; D, Bresson D, Guichard J-P, Riant F, Tournier-Lasserve E, Tzourio C, Chabriat H, Stapf C (2012) Antithrombotic therapy and bleeding risk in a prospective cohort study of patients with cerebral cavernous malformations. Stroke 43:3196\u0026ndash;3199. doi: 10.1161/STROKEAHA.112.668533\u003c/li\u003e\n\u003cli\u003eShih Y-C, Chou C-C, Peng S-J, Yu H-Y, Hsu SPC, Lin C-F, Lee C-C, Yang H-C, Chen Y-C, Kwan S-Y, Chen C, Wang S-J, Lin C-J, Lirng J-F, Shih Y-H, Yen D-J, Liu Y-T (2022) Clinical characteristics and long-term outcome of cerebral cavernous malformations-related epilepsy. Epilepsia 63:2056\u0026ndash;2067. doi: 10.1111/epi.17309\u003c/li\u003e\n\u003cli\u003eTripathi M, Ahuja CK, Aggarwal A, Mohindra S (2024) Is There Any \u0026ldquo;Unbled\u0026rdquo; Cavernoma? Neurol India 72:1119\u0026ndash;1121. doi: 10.4103/neurol-india.NI_32_21\u003c/li\u003e\n\u003cli\u003eWeber J, Ebinger M, Audebert HJ (2015) Prehospital stroke care: telemedicine, thrombolysis and neuroprotection. Expert Rev Neurother 15:753\u0026ndash;761. doi: 10.1586/14737175.2015.1051967\u003c/li\u003e\n\u003cli\u003eZhang J, Deng X, Yuan Q, Fu P, Wang M, Wu G, Yang L, Yuan C, Du Z, Hu J (2023) Staged or simultaneous operations for ventriculoperitoneal shunt and cranioplasty: Evidence from a meta-analysis. CNS Neurosci Ther 29:3136\u0026ndash;3149. doi: 10.1111/cns.14347\u003c/li\u003e\n\u003cli\u003eZuurbier SM, Hickman CR, Tolias CS, Rinkel LA, Leyrer R, Flemming KD, Bervini D, Lanzino G, Wityk RJ, Schneble H-M, Sure U, Al-Shahi Salman R, Scottish Audit of Intracranial Vascular Malformations Steering Committee (2019) Long-term antithrombotic therapy and risk of intracranial haemorrhage from cerebral cavernous malformations: a population-based cohort study, systematic review, and meta-analysis. Lancet Neurol 18:935\u0026ndash;941. doi: 10.1016/S1474-4422(19)30231-5\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cdiv class=\"gridtable\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e. Demography, clinical characteristics and pharmacological treatment overall and in CCM patients with versus without epileptic seizures.\u003c/p\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"549\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall sample\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEpilepsy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo epilepsy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u003cem\u003eVariables\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e(n=230)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e(n=75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e(n=155)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003ep *\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003eMale gender, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e47.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e49.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e47.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003eMean age in years (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e44.5 (19.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e39.0 (17.5)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e47.2 (19.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003eMedian time from diagnosis to surgery in months, (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e12.7 (3.0-71.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e9.0 (1.2-29.0)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e17.0 (3.0-90.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.020\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003eFamilial CCM mutations, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e- CCM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e32.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e35.0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e- CCM2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e- CCM3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003eSmoking status, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e- Current\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10.8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.07\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e- Former\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14.2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e- Never\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e82.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e89.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e79.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003eAlcohol drinking, % \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003eDiabetes, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003eHypertension, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e28.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e12.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e36.8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003eMean BMI (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e25.3 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e25.5 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e25.2 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e(n=120)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e(n=38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e(n=82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003eMenopause status, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e28.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e23.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e30.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e(n=78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e(n=3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e(n=75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003eHistory of MACE, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e51.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e53.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003eMACE type, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e(n=40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e(n=0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e(n=40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e- Stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e- AMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e- Arrhythmias\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e22.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e22.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e- DVT/pulmonary embolism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e- Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e57.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e57.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003eAnti-platelet drugs use, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e18.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e24.5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003eAnticoagulant drugs use, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e- None\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e97.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e98.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e96.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e- TAO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e- NAO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003eB-Blockers use, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e15.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21.3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e(N=78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e(N=3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e(N=75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003eOther pharmacologic treatments, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e96.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e96.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003eSD: Standard deviation; \u0026nbsp;IQR: Interquartile range; \u0026nbsp;ANS: Autonomic nervous system; CNS: Central nervous system; \u0026nbsp;MACE: Major adverse cardiovascular events; \u0026nbsp;DVT: deep vein thrombosis; \u0026nbsp;CCM: cerebral cavernous malformation genes; \u0026nbsp;\u003csup\u003eA\u003c/sup\u003e More than one answer possible. \u0026nbsp;\u003csup\u003eB\u003c/sup\u003e Including lesions with the following anatomical locations: thalamus, basal ganglia, insular, spinal and orbital.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e. Radiological characteristics overall and in CCM patients with versus without epileptic seizures.\u003c/p\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"549\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall sample\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEpilepsy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo epilepsy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 39.0511%;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.5182%;\"\u003e\n \u003cp\u003e(n=230)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e(n=75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.4234%;\"\u003e\n \u003cp\u003e(n=155)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5839%;\"\u003e\n \u003cp\u003ep *\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"549\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eZabramski classification, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 96px;\"\u003e\n \u003cp\u003e(n=151)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e(n=71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 90px;\"\u003e\n \u003cp\u003e(n=80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e- Accidental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e- Type I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 96px;\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e64.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 90px;\"\u003e\n \u003cp\u003e42.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e- Type II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 96px;\"\u003e\n \u003cp\u003e47.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e28.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 90px;\"\u003e\n \u003cp\u003e54.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e- Type III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 96px;\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e- Type IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 96px;\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003ePresence of multiple lesions, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 96px;\"\u003e\n \u003cp\u003e33.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e44.5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eTrauma-associated lesion, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 96px;\"\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eAnatomic lesion site, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e- Frontal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e31.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e44.0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e25.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e- Parietal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e12.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e14.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e11.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e- Temporal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e20.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e29.3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e16.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e- Occipital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e9.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e- Brain stem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e12.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18.7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e- Cerebellum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14.8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e- Others \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eLesion volume in mm\u003csup\u003e3\u003c/sup\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eMedian volume (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e800 (120-3000)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2100 (800-5600)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e270 (90-1200)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eBy quartiles of volume:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e- \u0026le;11.9 mm\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e25.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e36.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e- \u0026gt;11.9 to 80 mm\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e27.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e25.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e27.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e- \u0026ge;80 to 300 mm\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e24.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e34.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e19.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e- \u0026gt;300 mm\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e23.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e38.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e16.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 214px;\"\u003e\n \u003cp\u003eBleeding lesion, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e26.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e38.7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003eSD: Standard deviation; \u0026nbsp;IQR: Interquartile range; \u0026nbsp;\u003csup\u003eB\u003c/sup\u003e Including lesions with the following anatomical locations: thalamus, basal ganglia, insular, spinal and orbital.\u003c/p\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eClinical outcome overall and in CCM patients with versus without epileptic seizures.\u003c/div\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eOverall sample\u003c/div\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eEpilepsy\u003c/div\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eNo epilepsy\u003c/div\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eVariables\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e(n\u0026thinsp;=\u0026thinsp;230)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e(n\u0026thinsp;=\u0026thinsp;75)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e(n\u0026thinsp;=\u0026thinsp;155)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003ep *\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eGOS score, %\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026minus;\u0026thinsp;1\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.9\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.0\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1.3\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.3\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026minus;\u0026thinsp;2\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e12.2\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e5.3\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e15.5\u003c/span\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e0.03\u003c/span\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026minus;\u0026thinsp;3\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e16.5\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e12.0\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e18.7\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.2\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026minus;\u0026thinsp;4\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e70.4\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e82.7\u003c/span\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e64.5\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e0.005\u003c/span\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026minus;\u0026thinsp;5\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003emRankin Scale:\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.15\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026minus;\u0026thinsp;0\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e50.0\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e46.7\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e51.6\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026minus;\u0026thinsp;1\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e32.6\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e40.0\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e29.0\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026minus;\u0026thinsp;2\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e7.8\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e5.3\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e9.0\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026minus;\u0026thinsp;3\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e7.0\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e5.3\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e7.7\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026minus;\u0026thinsp;4\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.9\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.0\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1.3\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026minus;\u0026thinsp;5\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.9\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e2.7\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.0\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026minus;\u0026thinsp;6\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.8\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.0\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1.3\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eTreated with surgery, %\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e69.6\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e93.3\u003c/span\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e58.1\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/span\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eGOS: Glasgow Outcome Scale.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLogistic regression model evaluating the potential predictors of epileptic seizures among subjects with cerebral cavernous malformations.\u003c/div\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eEpileptic seizures\u003c/div\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e%\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eAdj. OR (95% CI)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003ep\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eAge, 10-year increase\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e--\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1.11 (0.89\u0026ndash;1.39)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.3\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLesion volume:\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e- \u0026le;11.9 mm\u003csup\u003e3\u003c/sup\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1.7\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1 (ref. cat.)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e--\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e- \u0026gt;11.9 to 80 mm\u003csup\u003e3\u003c/sup\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e30.7\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e25.9 (3.16\u0026ndash;213)\u003c/span\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e0.002\u003c/span\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e- \u0026ge;80 to 300 mm\u003csup\u003e3\u003c/sup\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e46.4\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e86.4 (9.94\u0026ndash;751)\u003c/span\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/span\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e- \u0026gt;300 mm\u003csup\u003e3\u003c/sup\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e53.7\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e63.5 (7.63\u0026ndash;528)\u003c/span\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/span\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eSymptomatic lesion:\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e- No\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e2.4\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1 (ref. cat.)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e--\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e- Yes\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e39.4\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e60.3 (6.50\u0026ndash;558)\u003c/span\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/span\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eFrontal or temporal lesion site:\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e- No\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e18.4\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1 (ref. cat.)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e--\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e- Yes\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e45.5\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e6.34 (2.99\u0026ndash;113.4)\u003c/span\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Bold\" class=\"Bold\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/span\u003e\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eAnti-platelet drugs use:\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e- No\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e37.4\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1 (ref. cat.)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e--\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e- Yes\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e11.6\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1.73 (0.29\u0026ndash;10.3)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.5\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eB-blockers drugs use:\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e- No\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e37.1\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1 (ref. cat.)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e--\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e- Yes\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e8.3\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.63 (0.30\u0026ndash;1.63)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.4\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eAdj.: adjusted; OR: Odds ratio; CI: Confidence Interval.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eThe raw % is the proportion of subjects with the outcome among the exposed and unexposed patients (e.g. the proportion of subjects with seizures among those with asymptomatic or symptomatic lesions).\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eFinal model based upon 230 observations, with 75 successes. Area under the ROC curve\u0026thinsp;=\u0026thinsp;0.88.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eDiagnostic accuracy of each lesion volume cut-off to predict the onset of epileptic seizures: summary estimates of sensitivity, specificity, positive and negative predictive values (PPV and NPV). CI\u0026thinsp;=\u0026thinsp;Confidence interval.\u003c/div\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u003cspan type=\"Italic\" class=\"Italic\" name=\"Emphasis\"\u003eLesion volume\u003c/span\u003e\u003c/div\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eSensitivity\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e% (95% CI)\u003c/div\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eSpecificity\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e% (95% CI)\u003c/div\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003ePPV\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e% (95% CI)\u003c/div\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eNPV\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e% (95% CI)\u003c/div\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026gt;\u0026thinsp;11.9 mm3\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e98.7\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e(92.8\u0026ndash;100)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e36.8\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e(29.2\u0026ndash;44.9)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e43.0\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e(35.5\u0026ndash;50.8)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e98.3\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e(90.8\u0026ndash;100)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026gt;\u0026thinsp;80 mm3\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e73.3\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e(61.9\u0026ndash;82.9)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e64.5\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e(56.4\u0026ndash;72.0)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e50.0\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e(40.3\u0026ndash;59.7)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e83.3\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e(75.4\u0026ndash;89.5)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026gt;\u0026thinsp;300 mm3\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e38.7\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e(27.6\u0026ndash;50.6)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e83.9\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e(77.1\u0026ndash;89.3)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e53.7\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e(39.6\u0026ndash;67.4)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e73.9\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e(66.7\u0026ndash;80.2)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"neurosurgical-review","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nrev","sideBox":"Learn more about [Neurosurgical Review](https://www.springer.com/journal/10143)","snPcode":"10143","submissionUrl":"https://submission.nature.com/new-submission/10143/3","title":"Neurosurgical Review","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"cavernomas, cavernous angiomas, epilepsy, seizures, epileptogenesis, bleeding","lastPublishedDoi":"10.21203/rs.3.rs-7123042/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7123042/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eCerebral cavernous malformations (CCMs) are vascular lesions frequently presenting with seizures on presentation. Studies have widely analyzed topography as a determinant of epileptogenesis. However, the association between lesion volumetry and epileptic risk remains poorly investigated, as no objective volumetric thresholds have been established to stratify seizure risk.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe conducted a multicentric case-control study including 230 adult patients with CCMs. Patients were grouped according to their initial presentation: epileptic (n=75) versus non-epileptic (n=155). We calculated the volumes of the lesions using the ABC/2 method and categorized them into quartiles. Subsequently, we run a multivariate logistic regression assessing independent predictors of epilepsy, adjusting for demographic, clinical, and radiological factors. We also estimated the diagnostic accuracy of lesion volume thresholds (\u0026gt;11.9 mm³, \u0026gt;80 mm³, \u0026gt;300 mm³).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eLesion volume was significantly associated with epilepsy risk. \u0026nbsp;Lesions ≥80 mm³ were shown to have higher odds of seizures on presentation (OR \u0026nbsp;86.4, 95% CI 9.94–751). We found hemorrhagic presentation (OR 60.3, 95% CI \u0026nbsp;6.50–558) and frontal or temporal location (OR 6.34, 95% CI 2.99–113.4) to be \u0026nbsp;also independent predictors of epilepsy. Differently, demographic and \u0026nbsp;pharmacologic factors were not independently predictive.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eLesion volume, hemorrhage, and cortical location were found to be the major predictors of epilepsy as first manifestation. Therefore, incorporating volumetric assessment into routine MRI evaluation may improve individualized risk stratification and guide early management decisions.\u003c/p\u003e","manuscriptTitle":"Predictors of epilepsy as presenting symptom of cerebral cavernomas","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-28 05:32:29","doi":"10.21203/rs.3.rs-7123042/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-18T05:18:28+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-13T14:36:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-11T13:41:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-09T22:27:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-06T15:14:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-06T09:54:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"248569845652583152745965186594227398086","date":"2025-12-03T18:40:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-01T20:53:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"299157465145228207184776181875081829617","date":"2025-11-26T12:16:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"319423846576877443600248893660796325087","date":"2025-11-26T06:15:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"213193704776221431632067254977496116924","date":"2025-11-25T12:51:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"173145866459723617472721478788685973923","date":"2025-11-24T14:10:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"165346343361828060386395728252932428577","date":"2025-11-24T07:09:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"285507914481360721324638257217918409929","date":"2025-09-10T07:24:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"174888525179101119785562021498578167778","date":"2025-08-24T01:27:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-22T15:38:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-20T16:38:15+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-16T09:20:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Neurosurgical Review","date":"2025-07-14T15:55:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"neurosurgical-review","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nrev","sideBox":"Learn more about [Neurosurgical Review](https://www.springer.com/journal/10143)","snPcode":"10143","submissionUrl":"https://submission.nature.com/new-submission/10143/3","title":"Neurosurgical Review","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"a03ef5ae-ca4a-4033-a4bd-024f89ba768a","owner":[],"postedDate":"July 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T16:19:15+00:00","versionOfRecord":{"articleIdentity":"rs-7123042","link":"https://doi.org/10.1007/s10143-026-04246-5","journal":{"identity":"neurosurgical-review","isVorOnly":false,"title":"Neurosurgical Review"},"publishedOn":"2026-03-28 16:13:25","publishedOnDateReadable":"March 28th, 2026"},"versionCreatedAt":"2025-07-28 05:32:29","video":"","vorDoi":"10.1007/s10143-026-04246-5","vorDoiUrl":"https://doi.org/10.1007/s10143-026-04246-5","workflowStages":[]},"version":"v1","identity":"rs-7123042","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7123042","identity":"rs-7123042","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}