Postoperative Seizure in Patients with Malignant Glioma Undergoing Tumor Resection with Intraoperative Mapping: Risk Factors, Management Strategies, and the Utility of Bayesian Analysis in a Case-Control Cohort

Postoperative Seizure in Patients with Malignant Glioma Undergoing Tumor Resection with Intraoperative Mapping: Risk Factors, Management Strategies, and the Utility of Bayesian Analysis in a Case-Control Cohort | 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 Postoperative Seizure in Patients with Malignant Glioma Undergoing Tumor Resection with Intraoperative Mapping: Risk Factors, Management Strategies, and the Utility of Bayesian Analysis in a Case-Control Cohort Yifei Sun, Mina Lobbous, Kristen Riley, Pedram Maleknia, John Stein, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8705953/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract BACKGROUND Postoperative seizures can occur secondary to cortical irritation from malignant glioma resection or from direct electrical stimulation of the cortical surface during intraoperative brain mapping. A paucity of literature exists with regards to the use of appropriate seizure risk-reduction strategies for this patient population. The objective of the study was to identify primary risk factors for early and late postoperative seizures following intraoperative brain mapping. METHODS The authors performed a case-control study with 30 patients who had postoperative clinical seizures within 6 months following craniotomies with intraoperative mapping for glioma resection from 2013 to 2021 at a single academic institution. An unmatched control population of all patients (n=52) who had undergone craniotomies with ICM during the same period and had no clinical seizures within 6 months following their operation were used for comparative analysis. Primary endpoint was any postoperative seizure within 6 months of surgery. Outcomes were analyzed both via frequentist and Bayesian statistical approaches. RESULTS Bayesian analysis using non-informative priors demonstrated that the probability of an odds ratio (OR) > 1 for prior history of seizures being a risk factor for postoperative seizures is 73%. The probability that OR < 1 for a patient with post op seizures who underwent motor mapping was 91%. If patients experienced an intraoperative seizure during mapping, the probability of having a postoperative seizure was 84%. Probability that awake mapping is protective of post op seizure when compared to asleep mapping is 88%. Complex anti-epileptic drug (AED) regimen (increasing dose + adding additional AEDs or 2 dose adjustments) had 64% probability of protection from late postoperative seizures. CONCLUSION Patients with a preoperative history of seizures may be at higher risk for postoperative seizures. More aggressive perioperative seizure prophylaxis may provide a protective benefit from postoperative seizures in patients who undergo intraoperative mapping. glioma resection seizure risk factors management bayesian analysis intraoperative mapping Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION Gliomas are the leading cause of malignant brain tumors and remain a challenging and heterogeneous tumor population to treat. Currently, maximal resection of these tumors followed by adjuvant therapies such as radiotherapy and chemotherapy remain the mainstay of treatment. Preservation of neurological function with this approach is essential and is associated with improved outcomes. 1 , 2 To achieve this surgical goal, intraoperative cortical mapping (ICM) is frequently performed in order to maximize tumor resection while protecting eloquent, non-resectable regions of tumor. 3 However, intraoperative and postoperative seizures remain unacceptably common adverse events in ICM despite improvements in technique. 4 , 5 These seizures occur in 17% to 50% of patients undergoing resection with ICM, with seizures seen more often with tumors affecting the frontal, parietal, and temporal lobes on the cortical surface. 6–10 There is a paucity of understanding of risk and protective factors for seizure occurrence following glioma resection with ICM. Recent studies have shown that longer stimulus durations can induce seizures. 11 , 12 Studies have found that patient factors such as preoperative epilepsy may also predispose to seizures intraoperatively, and there is concern that intraoperative seizures may predispose to further postoperative events, though few studies have specifically investigated this relationship. 5 , 11 – 13 Preoperative seizure history has also been found to increase the risk of postoperative seizures following ICM as well. 14 While some studies suggest that appropriate preoperative seizure prophylaxis may decrease the harmful sequelae of postoperative seizures, there also exists a paucity of data on the appropriate management strategy for seizure prevention specifically in patients undergoing ICM. 6 , 15 – 18 The primary aims of this study were to identify risk and protective factors for postoperative seizures in patients undergoing ICM via awake or asleep craniotomies and to provide insight into appropriate preventive management strategies. We hypothesized that a postoperative anti-epileptic drug (AED) regimen (either addition of new AEDs or dose increase) would be protective against postoperative seizures in this patient population. We also highlight the potential utility of a Bayesian analysis approach through a post-hoc comparison with our pre-hoc frequentist analysis results. METHODS This retrospective study was designed as a case-control study with approval from the Institutional Review Board at our institution, and informed consent was waived given the nature of the study. This manuscript was prepared in accordance to the EQUATOR network and The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines. 19 , 20 Variables and Data Management We identified 30 patients who had postoperative clinical seizures within 6 months following craniotomies with ICM for supratentorial brain tumor resection between 2013 to 2021 performed by 3 neurosurgeons at our institution. We used an unmatched control population of all patients (n = 52) who had undergone craniotomies with ICM during the same period and who had no clinical seizures within 6 months following their operation. Relevant variables were defined via consensus expertise by senior authors (M.L., K.R., B.N., and J.M.M.) and literature review on known postoperative seizure risk factors in this patient population. All variables were collected via electronic chart review. Most variables were binary or categorical except for age and income, all groups were defined according to standard practices to facilitate comparison. AED regimen categories were defined preoperatively (categorized as either monotherapy or polytherapy (at least 2 different medications) AEDs), and postoperative AED regimen (defined as any adjustment to AEDs or lack thereof at time of discharge). AED regimens were further categorized as monotherapy AED regimen, which was defined as only one medication, polytherapy AED regimen, which was defined as at least 2 medications, and complex AED regimen, which was defined as either increasing dose and adding additional AEDs or at least 2 dose adjustments postoperatively. Other variables collected included patient demographics, patient clinical and tumor characteristics, relevant dates, anesthesia modality (awake vs. asleep), mapping type and time, extent of resection, prior history of seizure and characteristics, intraoperative seizures, and AED regimen. We performed multiple imputations (incorporating previous outcome values and relevant demographic and clinical variables) and last observation carried forward on the outcome variable for 7 patients lost to follow up at 6 months with similar results. 21 , 22 Further details of variable collection and data management can be found in the Supplementary Digital Content. The primary outcome of interest was any clinical postoperative seizure within a 6-month period following surgical resection with ICM. Patients were assessed for postoperative seizures immediately after surgery and again at the 1- and 6-month outpatient follow-up visits. Seizures were defined as either focal or generalized seizures identified in the chart by observation, clinical and history evaluation by a neurologist, or electroencephalography (EEG). Early seizures were defined as seizures occurring within 7 days post operatively and late seizures were defined as seizures occurring after 7 days within 6 months post operatively. Statistical Methods This study with 82 participants had 0.8 power to detect an odd ratio (OR) of 0.28 and 6.4 assuming the proportion of controls exposed was 70% and OR of 0.16 and 3.6 assuming the proportion of controls exposed was 30%. Descriptive statistics were reported as numbers and percentages for categorical variables Age, given its bimodal distribution, was reported as means and interquartile ranges. Univariable comparisons were performed using Wilcoxon rank-sum test for age and Pearson’s χ2 or Fisher’s exact test when appropriate. Multivariable analysis was done using logistic regression for binary outcome with variables selected by consensus based on either known association or suspected potential clinical association with the outcome. To account for unmeasured or uncontrolled confounding, sensitivity analysis was performed using the methodology proposed by VanderWeele and Ding (Supplementary Digital Content, Figures S1 -S2). 23 Post-hoc Bayesian Analysis To aid in the identification of protective and risk factors, we conducted a post hoc Bayesian analysis. We adhered to the when to Worry and how to Avoid the Misuse of Bayesian Statistics (WAMBS-v2) guidelines. 24 A minimally informative reference prior (assumed mean coefficient 0 – OR 1 – and variance 10,000) was used to produce results dependent on data from this study alone. This noninformative prior regards all possible OR values to be equally likely and is equivalent to holding no prior belief on whether variables selected for analysis are either protective or risk factors for the specified outcome. An informative data-derived prior (mean coefficient 0.732 – OR 2.08 – for a history of seizures as a risk factor for postoperative seizures in a multivariable model and assumed variance of 1) with data from Eseonu et al . (2017) 14 was also used. Separate Bayesian models were run for each prior distribution. Each model used the same logistic regression construct (with tested assumptions) as in the primary analysis. Markov chain Monte Carlo (MCMC) with random-walk Metropolis-Hasting sampling algorithm (with 4 chains, 25,000 iterations burn-in and 40,000 total saved iterations per chain by saving every 15i + 1 iteration) was used to derive OR estimates and highest posterior density (HDP) 95% credible intervals (CrIs) from the median and to estimate the posterior probabilities of exposure variables exceeding thresholds for protective or risk factors as appropriate. 24 , 25 Model convergence was assessed visually (using trace, histogram, density, and autocorrelation plots) and using the Gelman-Rubin statistic ( Rc-hat ) Rc-hat values, plots, and effective sample size for all parameters as well as results from sensitivity analysis performed can be found in the Supplemental Digital Content (Supplementary Digital Content, Tables S5-S11, Figure S3). 26,27 All statistical analyses were done using STATA v17. 28 Further details of this analysis can be found in the Supplementary Digital Content. 24 – 27 RESULTS Patient Characteristics We identified 82 patients from January 2013 to March 2021 with supratentorial gliomas located in eloquent areas of the brain who had undergone craniotomy for resection with ICM. Thirty (37%) of these patients had at least one postoperative seizure within 6 months of initial resection (Table 1 ). Table 1 Patient Characteristics Variable No Seizure Seizure p-value n = 52 n = 30 Gender, N (%) Female 26(50%) 11(37%) 0.24 Male 26(50%) 19(63%) Age, Mean (IQR) 51.1(35.4–60.5) 54.4(38.7–67.7) 0.26 Age Categories < 45 24(46%) 9(30%) 0.66 45–54 9(17%) 7(23%) 55–64 9(17%) 6(20%) 65–74 7(13%) 5(17%) 75+ 3(6%) 3(10%) Race White 42(81%) 25(83%) 0.65 African American 8(15%) 3(10%) Other 2(4%) 2(7%) Income Below U.S. Median Household Income 34(65%) 17(57%) 0.43 Above U.S. Median Household Income 18(35%) 13(43%) RUCA Metropolitan 38(73%) 21(70%) 0.81 Micropolitan 6(12%) 5(17%) Small Town/Rural 6(12%) 4(13%) Glioma Type High Grade Glioma 41(79%) 26(87%) 0.38 Low Grade Glioma 11(21%) 4(13%) Diagnosis GBM 35(67%) 21(70%) 0.86 Anaplastic Oligodendroglioma 2(4%) 2(7%) Diffuse Astrocytoma 5(10%) 2(7%) Oligodendroglioma 3(6%) 2(7%) Anaplastic Astrocytoma 3(6%) 3(10%) LGG, NOS 3(6%) 0(0%) Anaplastic Ganglioglioma 1(2%) 0(0%) Lesion Laterality Left Side 35(67%) 19(63%) 0.71 Right Side 17(33%) 11(37%) Disease Progression 7(13%) 5(17%) 0.69 History of Disease Recurrence 18(35%) 7(23%) 0.29 History of Seizures Pre-op 26(50%) 20(67%) 0.14 Type of Seizure Pre-op None 26(50%) 10(33%) 0.01 Focal 11(21%) 16(53%) Generalized 15(29%) 4(13%) Pre-op AED (PPXvsTRX) No AED Prior to Surgery 14(27%) 4(13%) 0.27 Seizure Prophylaxis 12(23%) 6(20%) Seizure Treatment 26(50%) 20(67%) Pre-op AED Regimen No AEDs 14(27%) 4(13%) One AED 34(65%) 18(60%) Two or More AEDs 4(8%) 8(27%) 0.041 Anesthesia Type Awake 42(81%) 22(73%) 0.43 Asleep 10(19%) 8(27%) Mapping Motor 40(77%) 22(73%) 0.6 Speech 27(52%) 15(50%) 0.8 SSEP 10(19%) 9(30%) 0.29 Mapping Time 30 minutes or less 23(44%) 16(53%) 0.16 Greater than 30 minutes 19(37%) 6(20%) Immediate Pre-Monitoring AED Adjustment/Increase 14(27%) 10(33%) 0.54 Extent of Resection STR 32(62%) 18(60%) 1 GTR 20(38%) 12(40%) Neurosurgeon Neurosurgeon No. 1 39(75%) 25(83%) 0.73 Neurosurgeon No. 2 12(23%) 5(17%) Neurosurgeon No. 3 1(2%) 0(0%) Seizures - Intraoperative 6(12%) 4(13%) 0.81 Seizures - Immediately post-op 0(0%) 15(50%) < 0.001 AED at Discharge - Adjustment 34(65%) 26(87%) 0.036 AED at Discharge - Adjustment No change in pre-op AED regimen or dose 18(35%) 4(13%) < 0.001 Monotherapy with dose increase 24(46%) 7(23%) Complex Adjustment 10(19%) 19(63%) AED Type Levetiracetam 50(96%) 28(93%) 0.57 Lacosamide 6(12%) 17(57%) < 0.001 Other AED 6(12%) 14(47%) < 0.001 Demographics of the patient and characteristics of the tumors themselves were very similar (Table 1 ). The mean age was 51.0 (IQR 35.4–60.5) years in the control group and 54.4 (38.7–67.7) years amongst the seizure group (p = .26). Amongst the controls, 26 (50%) had a preoperative history of seizures (of which 73% were on preoperative AEDs) compared to 20 (67%) of the seizure cases (87% on preoperative AEDs) (p= .14). Six (12%) of the controls and 4 (13%) of the seizure group had intraoperative seizures (p= .81). Most of the patients in both groups were placed on levetiracetam postoperatively [50 (96%) v. 28 (93%)]. There were more patients amongst the seizure cases who were placed on lacosamide postoperatively [6 (12%) vs 17 (57%), p< .001]. Other patient characteristics, pathological diagnosis, intraoperative mapping/resection techniques were found to be similar between groups (Table 1 ). A Kaplan-Meier estimate of the proportion of patients who experienced at least one postoperative clinical seizure within 6 months was generated. The median time to first postoperative seizure was 7.5 days, with 50% of seizures occurring early. A range of 0 to 190 days to seizure recurrence was observed. Incidence rate of postoperative seizures was 2.61 seizures per 1,000 person-days (Fig. 1 ). Primary Outcome Results of sensitivity analysis using methodology proposed by VanderWeele and Ding are presented in the Supplementary Digital Content. 23 After multivariate logistic regression analysis, we found that patients with a preoperative history of seizures and concurrently taking more than one AED were more likely to have postoperative seizures following surgery (OR 28.45, 95% CI 2.15-375.57, p = 0.011). However, history of preoperative seizures alone was not an independent risk factor for postoperative seizures (OR 1.48, 95% CI 0.34–6.49, p = 0.606). Figure 2 shows the multivariate logistic regression comparison between cases and controls for postoperative seizure (Supplementary Digital Content, Table S2). Post-hoc Analysis of Secondary Outcomes Post-hoc analysis was performed for patients with early seizures and patients with late seizures (Supplementary Digital Content, Tables S3-S4). Upon multivariate logistic regression analysis, preoperative history of seizures, history of preoperative AED usage, and seizures intraoperatively during the mapping portion of the procedure did not confer a higher odds of having early postoperative seizures. Results of this analysis are shown in Fig. 3 . On multivariate logistic regression analysis in patients with late postoperative seizures, patients were found to have a lower odds ratio of having motor mapping during their resection (OR 0.08, 95% CI 0.01–0.86, p=.037). This association was not seen with regards to speech mapping (OR 0.26, 95% CI 0.01–6.33, p=.409). Results of this analysis with odds ratios and 95% confidence intervals can be seen in Fig. 4 . Post-hoc Bayesian Analysis without Informative Priors ORs with 95% credible intervals are shown in Table 2 . Several hypotheses were tested. The probability of a prior history of seizures being a risk factor (OR > 1) for postoperative seizures was 72.5%. The probability that the use of motor mapping was protective (OR < 1) was 91.5%. The probability that awake mapping is protective of postoperative seizures when compared to asleep mapping is 88.1%. The probability that gross total resection was a risk factor for postoperative seizures when compared to those who had subtotal resections was 70.6%. The probability of intraoperative seizures being a risk factor for postoperative seizures was 84.4%. Interestingly, the probability that sensory or language mapping was a risk factor for postoperative seizures was 94.2% and 65.8%, respectively. Monotherapy AED with dose increase alone had a 18.87% probability of acting as a protective factor for late postoperative seizures. A complex AED regimen had 63.35% probability of acting as a protective factor from late postoperative seizures. Post Hoc Bayesian Analysis using Informative Priors ORs with 95% credible intervals are shown in Table 2 . Eseonu et al . (2017) 14 reports a history of seizures as an independent risk factor for postoperative seizures, and we subsequently updated our priors with this information. The probability that OR > 1 for prior history of seizures being a risk factor for postoperative seizures was updated to 82.0%, from 72.5% using non-informative priors (Table 2 ). Table 2 Probability of Odds Ratio Estimated by Bayesian Analysis in Patients Undergoing Intraoperative Mapping Risk Factors Posterior Probability That True OR Is >Specified Threshold, % Posterior Median OR (95% Credible Interval) OR > 1 OR > 1.2 OR > 1.5 OR > 1.8 OR > 2 Minimally Informative Priors Prior History of Seizures 2.42 (0.11–6.89) 72.5 64.7 54.3 45.6 40.7 High Grade Glioma 1.95 (0.02–6.37) 52.7 45.8 37.7 31.4 27.9 Age 55–64 6.67 (0.09–21.25) 91.5 88.2 83.2 78.3 75.0 Age 65–74 6.82 (0.10-22.03) 90.7 87.3 82.1 77.0 73.7 Age > 75 17.59 (0.01–63.88) 90.6 88.2 84.7 81.5 79.3 Language Mapping 2.86 (0.02–9.39) 65.8 59.2 50.8 43.9 40.1 Sensory Mapping 7.47 (0.15–23.42) 94.2 91.6 87.1 82.5 79.5 Intraoperative Seizures 5.93 (0.04–19.83) 84.4 80.2 74.1 68.4 64.9 Gross Total Resection 1.98 (0.14–5.15) 70.6 61.6 49.9 40.1 34.8 History of AED monotherapy 9.98 (0.10-34.01) 92.5 89.7 85.4 81.2 78.4 History of taking 2 or more AEDs 275.33 (0.22-1007.972) 99.9 99.8 99.7 99.6 99.5 Data Derived Priors Prior History of Seizures 82.0 73.6 61.1 50.1 43.6 Protective Factors Posterior Probability That True OR Is <Specified Threshold, % Posterior Median RR (95% Credible Interval) OR < 1 OR < 0.8 OR < 0.6 OR < 0.5 OR < 0.4 Minimally Informative Priors Motor Mapping 0.44 (0.01–1.28) 91.5 86.9 79.0 72.7 63.8 Awake Mapping 0.51 (0.01–1.56) 88.1 82.7 74.0 67.4 58.4 DISCUSSION Risk Factors In traditional frequentist analysis, we found that preoperative polytherapy AED regimen for preoperative seizure control was a risk factor for postoperative seizures after glioma resection with ICM, but the presence of preoperative seizures alone was not an independent risk factor (Fig. 2 ). This may be that patients requiring multiple AEDs have poorly controlled or refractory seizures preoperatively and surgery only serves to exacerbate the condition. 29 , 30 Upon Bayesian analysis without informative priors, we observed that a history of prior seizures, intraoperative seizures, sensory mapping, language mapping, gross total resection rather than subtotal resection, being of older age, and having a history of monotherapy AED or polytherapy AED were implicated as potential risk factors for seizure following glioma resection with ICM. Several of these results are in line with findings by Conte et al . (2015) 31 , who found frontal tumor location, antiepileptic polytherapy, intraoperative seizures during mapping, and postoperative blood products on imaging to be independent predictors of immediate postoperative seizures. Of note, a history of prior seizures was a potential risk factor, likely because a history of prior seizures may indicate some underlying seizure pathology that would only be aggravated by ICM during glioma resection. 32 Gross total resection rather than subtotal resection has an increased likelihood of being a risk factor possibly due to resection closer to epileptogenic regions, increasing the likelihood of potential irritation to these regions. Intraoperative seizures were found to have increased likelihood of being a risk factor possibly for a combination of reasons. High-intensity currents applied directly on the cortex can result in after-discharges (ADs), which can then propagate into clinical seizures, and may occur due to pathological network connectivity, among others. 33–37 Thus, this seizure provocation that triggered the intraoperative seizure likely persisted into the post-operative period, predisposing the patient to further seizures. Sensory mapping and language mapping were also found to be potential risk factors. These findings can be explained by a study by Chaichana et. al (2009) 38 , who found that parietal lobe infiltration by glioma predicted poor seizure control; thus, sensory mapping implies a tumor involvement in a region involved with poor seizure outcomes. Language mapping centers are found in regions of the brain highly associated with seizures as well, explaining the high probability of being a seizure risk factor. 39 Interestingly, we further found awake mapping to be a potential protective factor for seizures after glioma resection with ICM. This observation can be explained by a potentially increased resolution of eloquent areas and problematic foci during awake mapping rather than asleep. 40 We also found motor mapping to be a likely protective factor. This may be because motor mapping may be a surrogate for tumor location, as these tumors may have a significant frontal component. In such circumstances, a greater extent of resection may be achievable especially for tumors isolated to the frontal lobes. This more aggressive resection may decrease the odds of seizures in the long-term once patients are past the perioperative period. 41 However, these findings may emphasize a couple of potential confounders issues. The definition of seizures is heterogeneous and often subjective; therefore, there may be a misclassification bias. If patients have tumors extending into clinically silent or non-eloquent regions, then their incidence of seizures may be under-reported or clinically silent altogether, affecting our data. Management of Seizures following Glioma Resection with ICM Prophylaxis against intra- and post-operative seizures remains a contested issue. 9 , 42 , 43 Dineen et al. (2019) 13 found that preoperative loading with intravenous AEDs (levetiracetam, fosphenytoin, lacosamide) decreased the odds of an intraoperative seizure (OR 0.55, p = 0.009). However, a prospective randomized trial by Wu et al . (2013) 15 found that postoperative prophylaxis with phenytoin did not decrease the risk of seizures and was associated with increased medication adverse events. Al-Dorzi et al . (2017) 9 similarly did not find that postoperative AED prophylaxis decreased seizure incidence. We had hypothesized that the initiation of or dose increase in a postoperative AED regimen would be protective against seizures in patients who had resection with ICM. However, via the frequentist approach, we did not find a significant association. But via a Bayesian model, the relationship can be more clearly delineated. We found that AED monotherapy with a postoperative dose increase had less than a 20% probability of protecting against seizures. However, a complex AED regimen (increasing dose + adding additional AEDs or 2 dose adjustments postop) had 63.35% probability of protecting against late postoperative seizures. This discrepancy between frequentist and Bayesian approaches emphasizes one of the other aims of this study. The Utility of Bayesian Analysis Bayesian analysis re-allocates relative credibilities within the set of considered possibilities. 44 There are several advantages to using Bayesian analysis such as allowing researchers to incorporate prior information into current analysis and providing a conceptually simpler multilevel analysis. 44 – 46 However, to conduct Bayesian statistics, prespecified “priors” is often required. In the present study, we performed analysis both with and without information priors (Table 2 ), and we relied on various thresholds risk factor thresholds and found the probability of preoperative seizure history increasing the odds of postoperative seizures (OR > 1) to be 72.5%. After accounting for findings reported by Eseonu et al . (2017) 14 the probability of preoperative seizures increasing the odds of postoperative events rose to 82.0%. 14 Bayesian methods allow for the probabilities of associations to be reported and adjusted given prior information (Fig. 3 ). This framework may be useful in the study of topics that may be otherwise underpowered and may be clinically useful when utilizing different thresholds in order to account for clinical experience. Although a frequentist analytic framework is far more common in the neurosurgical literature, this study highlights the potential utility of using a Bayesian framework. Results from this approach are more intuitive in a clinical setting, especially when considering extant associations or strong a priori clinical assumptions, and can be very useful in settings with few participants often at risk of an underpowered analysis Limitations This is a single-institution, retrospective study with all the limitations therein. Multiple oncologic neurosurgeons were included in this series, and differences in intraoperative technique or aggressiveness in ICM may be reflected in the data. However, given that we did not find a significant association between ICM and postoperative seizures, we suspect these technical differences to be marginal. The definition of seizure used as the primary outcome of this study included both subjective and objective criteria. As such, the frequency of these events may be under- or over-reported. However, similar limitations are noted throughout literature and the use of solely objective criteria (EEG findings correlating with clinical events) would likely greatly underestimate seizure frequency. For the present study, we chose to potentially overestimate clinical seizures. For our Bayesian analysis, there was a paucity of informative priors. As such, the majority of the analyses assume non-informative priors and may under-value the results of this technique. CONCLUSION Patients with a preoperative history of seizures may be at higher risk for postoperative seizures, and aggressive perioperative seizure prophylaxis may provide a protective benefit from postoperative seizures in patients who undergo intraoperative mapping. Abbreviations AED Anti-epileptic drug AD After-Discharges ICM intraoperative cortical mapping Declarations COMPLIANCE WITH ETHICAL STANDARDS Funding: This project was supported in part by the National Institute of Neurological Disorders and Stroke of the National Institutes of Health under award number R25NS079188 (DEO). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. DEO was also a Cornwall Clinical Scholar supported by the University of Alabama at Birmingham. Conflicts of Interest: All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent, licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript. Human Ethics and Consent to Participate declarations All procedures performed in studies involving human participants were in accordance with the ethical standards of the University of Alabama at Birmingham IRB and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was not sought due to the retrospective nature of this study. Author Contribution Y.S. and D.E.O. wrote the main manuscript text, and prepared all tables and figures. D.E.O. performed primary analysis. P.M. and J.S. performed data extraction. All authors critically reviewed the manuscript. Data Availability Data is available upon reasonable request. References Hervey-Jumper SL, Berger MS (2016) Maximizing safe resection of low- and high-grade glioma. Journal of Neuro-Oncology . /11 2016;130(2):269–282. 10.1007/s11060-016-2110-4 Ma R, Taphoorn MJB, Plaha P (2021) Advances in the management of glioblastoma. J Neurol Neurosurg Psychiatry 10(10):1103–1111. 10.1136/jnnp-2020-325334 . /01 2021 Wang Y-C, Lee C-C, Takami H et al (2019) Awake craniotomies for epileptic gliomas: intraoperative and postoperative seizure control and prognostic factors. J Neurooncol 2019/05(3):577–586. 10.1007/s11060-019-03131-0 Szelényi A, Bello L, Duffau H et al Intraoperative electrical stimulation in awake craniotomy: methodological aspects of current practice. 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Curr Opin Anaesthesiol . /10 2010;23(5):564–567. 10.1097/ACO.0b013e32833e14f2 Siomin V, Angelov L, Li L, Vogelbaum MA (2005) Results of a survey of neurosurgical practice patterns regarding the prophylactic use of anti-epilepsy drugs in patients with brain tumors. J Neurooncol 2005/09(2):211–215. 10.1007/s11060-004-6912-4 Rossetti AO, Stupp R (2010) Epilepsy in brain tumor patients. Current Opinion in Neurology . /12 2010;23(6):603–609. 10.1097/WCO.0b013e32833e996c von Elm E, Altman DG, Egger M et al (2007) The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet 370(9596):1453–1457. 10.1016/S0140-6736(07)61602-X . /10/20 2007 About us | The EQUATOR Network Rubin DB (1996) Multiple Imputation after 18 + Years. Journal of the American Statistical Association . /06/01 1996;91(434):473–489. 10.1080/01621459.1996.10476908 Schafer JL (1997) Analysis of Incomplete Multivariate Data VanderWeele TJ, Ding P (2017) Sensitivity Analysis in Observational Research: Introducing the E-Value. Ann Intern Med . /08/15 2017;167(4):268–274. 10.7326/M16-2607 van de Schoot R, Depaoli S, King R et al (2021) Bayesian statistics and modelling. Nat Rev Methods Primers . /01/14 2021;1(1):1–26. 10.1038/s43586-020-00001-2 Kruschke JK (2015) Highest Density Interval - an overview. Doing Bayesian Data Anal Gelman A, Rubin DB (1992) Inference from Iterative Simulation Using Multiple Sequences. Statistical Science . /11 1992;7(4):457–472. 10.1214/ss/1177011136 Brooks SP, Gelman A (1998) General Methods for Monitoring Convergence of Iterative Simulations. Journal of Computational and Graphical Statistics . /12/01 1998;7(4):434–455. 10.1080/10618600.1998.10474787 Stata . 17 ed. (2021) Thomas SV, Koshy S, Nair CR, Sarma SP (2005) Frequent seizures and polytherapy can impair quality of life in persons with epilepsy. Neurol India Mar 53(1):46–50. 10.4103/0028-3886.15054 Lee JW, Dworetzky B (2010) Rational Polytherapy with Antiepileptic Drugs. Pharmaceuticals (Basel) . Jul 26. ;3(8):2362–2379. 10.3390/ph3082362 Conte V, Carrabba G, Magni L et al (2015) Risk of perioperative seizures in patients undergoing craniotomy with intraoperative brain mapping. Minerva Anestesiol 2015/04(4):379–388 Ersoy TF, Ridwan S, Grote A, Coras R, Simon M (2020) Early postoperative seizures (EPS) in patients undergoing brain tumour surgery. Scientific Reports . /08/13 2020;10(1):13674. 10.1038/s41598-020-70754-z Karakis I, Leeman-Markowski BA, Leveroni CL et al Intra-stimulation discharges: An overlooked cortical electrographic entity triggered by direct electrical stimulation. Clin Neurophysiol. 2015/05/01 2015;126(5):882–888. 10.1016/j.clinph.2014.08.011 Cordella R, Acerbi F, Marras CE et al (2013) Risk of seizures during intraoperative electrocortical stimulation of brain motor areas: a retrospective study on 50 patients. Neurol Sci 2013/01(1):63–70. 10.1007/s10072-012-0968-2 Kalamangalam GP, Tandon N, Slater JD (2014) Dynamic mechanisms underlying afterdischarge: a human subdural recording study. Clin Neurophysiol . /07 2014;125(7):1324–1338. 10.1016/j.clinph.2013.11.027 Pouratian N, Cannestra AF, Bookheimer SY, Martin NA, Toga AW (2004) Variability of intraoperative electrocortical stimulation mapping parameters across and within individuals. J Neurosurg . /09 2004;101(3):458–466. 10.3171/jns.2004.101.3.0458 Lesser RP, Lee HW, Webber WRS, Prince B, Crone NE, Miglioretti DL (2008) Short-term variations in response distribution to cortical stimulation. Brain 2008/06(Pt 6):1528–1539. 10.1093/brain/awn044 Chaichana KL, Parker SL, Olivi A, Quiñones-Hinojosa A (2009) Long-term seizure outcomes in adult patients undergoing primary resection of malignant brain astrocytomas. Clinical article. J Neurosurg Aug 111(2):282–292. 10.3171/2009.2.Jns081132 Chauhan P, Philip SE, Chauhan G, Mehra S (2022) The Anatomical Basis of Seizures. In: Czuczwar SJ, ed. Epilepsy . Exon Publications Copyright: The Authors.; The authors confirm that the materials included in this chapter do not violate copyright laws. Where relevant, appropriate permissions have been obtained from the original copyright holder(s), and all original sources have been appropriately acknowledged or referenced Suarez-Meade P, Marenco-Hillembrand L, Prevatt C et al (2020) Awake vs. asleep motor mapping for glioma resection: a systematic review and meta-analysis. Acta Neurochirurgica . /07/01 2020;162(7):1709–1720. 10.1007/s00701-020-04357-y Englot DJ, Han SJ, Berger MS, Barbaro NM, Chang EF (2012) Extent of Surgical Resection Predicts Seizure Freedom in Low-Grade Temporal Lobe Brain Tumors. Neurosurgery 70(4):921–928. 10.1227/NEU.0b013e31823c3a30 Youngerman BE, Joiner EF, Wang X et al (2020) Patterns of seizure prophylaxis after oncologic neurosurgery. Journal of Neuro-Oncology . /01 2020;146(1):171–180. 10.1007/s11060-019-03362-1 Wali AR, Rennert RC, Wang SG, Chen CC (2017) Prophylactic anticonvulsants in patients with primary glioblastoma. J Neurooncol 2017/11(2):229–235. 10.1007/s11060-017-2584-8 Kruschke JK, Liddell TM (2018) Bayesian data analysis for newcomers. Psychon Bull Rev . /02 2018;25(1):155–177. 10.3758/s13423-017-1272-1 Yuan Y, MacKinnon DP (2009) Bayesian mediation analysis. Psychol Methods . /12 2009;14(4):301–322. 10.1037/a0016972 Rendón-Macías ME, Riojas-Garza A, Contreras-Estrada D, Martínez-Ezquerro JD (2018) [Bayesian analysis. Basic and practical concepts for its interpretation and use]. Rev Alerg Mex 2018/09(3):285–298. 10.29262/ram.v65i3.512 Additional Declarations No competing interests reported. Supplementary Files revisedSupplementalDigitalContent.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8705953","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":587805909,"identity":"df1c966c-6af2-45a2-a5a5-c318722f8f90","order_by":0,"name":"Yifei Sun","email":"","orcid":"","institution":"University of Alabama at Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Yifei","middleName":"","lastName":"Sun","suffix":""},{"id":587805910,"identity":"3ee2c577-d3ba-4999-8877-a117f6747923","order_by":1,"name":"Mina Lobbous","email":"","orcid":"","institution":"Cleveland 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Markert","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYBACxgYIZuBnYGCDCB0gUouEZAOxWmDaJAwOEKuFedrhZx9nVNyrM76R/OzRjRoGOb4bCQRsmJ1mPHPDmWIJsxtp5sY5xxiMJQlrSTBmfNiWANSSYCad28CQuIGwlvTPjA//JUgYz0j/BtJST4SWHGPGjQ0JEgYSOWBbEgyI0FLMOONYguSMM2/KgX6RMJx55gF+LYaz0zcz9tQk8PO3p297nFNjI893nIAthg2ofAn8ykFAnrCSUTAKRsEoGPEAAGStRn+hzZxiAAAAAElFTkSuQmCC","orcid":"","institution":"University of Alabama at Birmingham","correspondingAuthor":true,"prefix":"","firstName":"James","middleName":"","lastName":"Markert","suffix":""},{"id":587805922,"identity":"75c0582b-c922-4a53-9e4e-e26ec6b78276","order_by":8,"name":"Dagoberto Estevez-Ordonez","email":"","orcid":"","institution":"University of Miami Health System","correspondingAuthor":false,"prefix":"","firstName":"Dagoberto","middleName":"","lastName":"Estevez-Ordonez","suffix":""},{"id":587805923,"identity":"dba98c9c-1eb9-45bd-aa62-1ec690897090","order_by":9,"name":"Burt Nabors","email":"","orcid":"","institution":"University of Alabama at Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Burt","middleName":"","lastName":"Nabors","suffix":""}],"badges":[],"createdAt":"2026-01-27 05:23:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8705953/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8705953/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102337292,"identity":"ab2b8090-6737-4916-a233-f598fb0580de","added_by":"auto","created_at":"2026-02-10 16:12:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":141174,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier estimate of the proportion of patients who experienced at least one postoperative clinical seizure within 6 months\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8705953/v1/612d44cea5752c74b80b2fdd.png"},{"id":102337321,"identity":"db8252a0-3701-4ee4-b4c1-a3c4f5f45ab0","added_by":"auto","created_at":"2026-02-10 16:12:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":210313,"visible":true,"origin":"","legend":"\u003cp\u003eMultivariate logistic regression for factors associated with postoperative seizure\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8705953/v1/3aaa9f061b6557378c1999c2.png"},{"id":102337289,"identity":"f2f70c1f-e23d-4b28-bd9c-fd0078275aee","added_by":"auto","created_at":"2026-02-10 16:12:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":214026,"visible":true,"origin":"","legend":"\u003cp\u003eMultivariate logistic regression for factors associated with early postoperative seizure\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8705953/v1/fd084dcb87376ff094cb1a73.png"},{"id":102337287,"identity":"8b3dc285-6b1b-46a7-b62c-d65c7ffaa07c","added_by":"auto","created_at":"2026-02-10 16:12:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":226824,"visible":true,"origin":"","legend":"\u003cp\u003eMultivariate logistic regression for factors associated with late postoperative seizures\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8705953/v1/5d9603fbcc1f56c395e461af.png"},{"id":104399687,"identity":"fd34e198-53b3-43b2-9e27-348804e52491","added_by":"auto","created_at":"2026-03-11 12:07:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2009308,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8705953/v1/8fc0d31e-da3b-4704-aa2b-3726d69adb8b.pdf"},{"id":102399794,"identity":"7b04b898-22e6-42ef-80ec-c48fd69ea4ea","added_by":"auto","created_at":"2026-02-11 10:37:01","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":708450,"visible":true,"origin":"","legend":"","description":"","filename":"revisedSupplementalDigitalContent.docx","url":"https://assets-eu.researchsquare.com/files/rs-8705953/v1/5133ecee63a128cc3495cbd9.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Postoperative Seizure in Patients with Malignant Glioma Undergoing Tumor Resection with Intraoperative Mapping: Risk Factors, Management Strategies, and the Utility of Bayesian Analysis in a Case-Control Cohort","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eGliomas are the leading cause of malignant brain tumors and remain a challenging and heterogeneous tumor population to treat. Currently, maximal resection of these tumors followed by adjuvant therapies such as radiotherapy and chemotherapy remain the mainstay of treatment. Preservation of neurological function with this approach is essential and is associated with improved outcomes.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e To achieve this surgical goal, intraoperative cortical mapping (ICM) is frequently performed in order to maximize tumor resection while protecting eloquent, non-resectable regions of tumor.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eHowever, intraoperative and postoperative seizures remain unacceptably common adverse events in ICM despite improvements in technique.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e These seizures occur in 17% to 50% of patients undergoing resection with ICM, with seizures seen more often with tumors affecting the frontal, parietal, and temporal lobes on the cortical surface. \u003csup\u003e6\u0026ndash;10\u003c/sup\u003e There is a paucity of understanding of risk and protective factors for seizure occurrence following glioma resection with ICM. Recent studies have shown that longer stimulus durations can induce seizures.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Studies have found that patient factors such as preoperative epilepsy may also predispose to seizures intraoperatively, and there is concern that intraoperative seizures may predispose to further postoperative events, though few studies have specifically investigated this relationship.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e Preoperative seizure history has also been found to increase the risk of postoperative seizures following ICM as well.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e While some studies suggest that appropriate preoperative seizure prophylaxis may decrease the harmful sequelae of postoperative seizures, there also exists a paucity of data on the appropriate management strategy for seizure prevention specifically in patients undergoing ICM.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe primary aims of this study were to identify risk and protective factors for postoperative seizures in patients undergoing ICM via awake or asleep craniotomies and to provide insight into appropriate preventive management strategies. We hypothesized that a postoperative anti-epileptic drug (AED) regimen (either addition of new AEDs or dose increase) would be protective against postoperative seizures in this patient population. We also highlight the potential utility of a Bayesian analysis approach through a post-hoc comparison with our pre-hoc frequentist analysis results.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e This retrospective study was designed as a case-control study with approval from the Institutional Review Board at our institution, and informed consent was waived given the nature of the study. This manuscript was prepared in accordance to the EQUATOR network and The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eVariables and Data Management\u003c/h2\u003e \u003cp\u003eWe identified 30 patients who had postoperative clinical seizures within 6 months following craniotomies with ICM for supratentorial brain tumor resection between 2013 to 2021 performed by 3 neurosurgeons at our institution. We used an unmatched control population of all patients (n\u0026thinsp;=\u0026thinsp;52) who had undergone craniotomies with ICM during the same period and who had no clinical seizures within 6 months following their operation.\u003c/p\u003e \u003cp\u003eRelevant variables were defined via consensus expertise by senior authors (M.L., K.R., B.N., and J.M.M.) and literature review on known postoperative seizure risk factors in this patient population. All variables were collected via electronic chart review. Most variables were binary or categorical except for age and income, all groups were defined according to standard practices to facilitate comparison. AED regimen categories were defined preoperatively (categorized as either monotherapy or polytherapy (at least 2 different medications) AEDs), and postoperative AED regimen (defined as any adjustment to AEDs or lack thereof at time of discharge). AED regimens were further categorized as monotherapy AED regimen, which was defined as only one medication, polytherapy AED regimen, which was defined as at least 2 medications, and complex AED regimen, which was defined as either increasing dose and adding additional AEDs or at least 2 dose adjustments postoperatively. Other variables collected included patient demographics, patient clinical and tumor characteristics, relevant dates, anesthesia modality (awake vs. asleep), mapping type and time, extent of resection, prior history of seizure and characteristics, intraoperative seizures, and AED regimen. We performed multiple imputations (incorporating previous outcome values and relevant demographic and clinical variables) and last observation carried forward on the outcome variable for 7 patients lost to follow up at 6 months with similar results.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Further details of variable collection and data management can be found in the Supplementary Digital Content.\u003c/p\u003e \u003cp\u003eThe primary outcome of interest was any clinical postoperative seizure within a 6-month period following surgical resection with ICM. Patients were assessed for postoperative seizures immediately after surgery and again at the 1- and 6-month outpatient follow-up visits. Seizures were defined as either focal or generalized seizures identified in the chart by observation, clinical and history evaluation by a neurologist, or electroencephalography (EEG). Early seizures were defined as seizures occurring within 7 days post operatively and late seizures were defined as seizures occurring after 7 days within 6 months post operatively.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStatistical Methods\u003c/h3\u003e\n\u003cp\u003eThis study with 82 participants had 0.8 power to detect an odd ratio (OR) of 0.28 and 6.4 assuming the proportion of controls exposed was 70% and OR of 0.16 and 3.6 assuming the proportion of controls exposed was 30%. Descriptive statistics were reported as numbers and percentages for categorical variables Age, given its bimodal distribution, was reported as means and interquartile ranges. Univariable comparisons were performed using Wilcoxon rank-sum test for age and Pearson\u0026rsquo;s χ2 or Fisher\u0026rsquo;s exact test when appropriate. Multivariable analysis was done using logistic regression for binary outcome with variables selected by consensus based on either known association or suspected potential clinical association with the outcome. To account for unmeasured or uncontrolled confounding, sensitivity analysis was performed using the methodology proposed by VanderWeele and Ding (Supplementary Digital Content, Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e-S2).\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003ch3\u003ePost-hoc Bayesian Analysis\u003c/h3\u003e\n\u003cp\u003eTo aid in the identification of protective and risk factors, we conducted a post hoc Bayesian analysis. We adhered to the when to Worry and how to Avoid the Misuse of Bayesian Statistics (WAMBS-v2) guidelines.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e A minimally informative reference prior (assumed mean coefficient 0 \u0026ndash; OR 1 \u0026ndash; and variance 10,000) was used to produce results dependent on data from this study alone. This noninformative prior regards all possible OR values to be equally likely and is equivalent to holding no prior belief on whether variables selected for analysis are either protective or risk factors for the specified outcome. An informative data-derived prior (mean coefficient 0.732 \u0026ndash; OR 2.08 \u0026ndash; for a history of seizures as a risk factor for postoperative seizures in a multivariable model and assumed variance of 1) with data from Eseonu \u003cem\u003eet al\u003c/em\u003e. (2017)\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e was also used. Separate Bayesian models were run for each prior distribution. Each model used the same logistic regression construct (with tested assumptions) as in the primary analysis. Markov chain Monte Carlo (MCMC) with random-walk Metropolis-Hasting sampling algorithm (with 4 chains, 25,000 iterations burn-in and 40,000 total saved iterations per chain by saving every 15i\u0026thinsp;+\u0026thinsp;1 iteration) was used to derive OR estimates and highest posterior density (HDP) 95% credible intervals (CrIs) from the median and to estimate the posterior probabilities of exposure variables exceeding thresholds for protective or risk factors as appropriate.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Model convergence was assessed visually (using trace, histogram, density, and autocorrelation plots) and using the Gelman-Rubin statistic (\u003cem\u003eRc-hat\u003c/em\u003e) \u003cem\u003eRc-hat\u003c/em\u003e values, plots, and effective sample size for all parameters as well as results from sensitivity analysis performed can be found in the Supplemental Digital Content (Supplementary Digital Content, Tables S5-S11, Figure S3). \u003csup\u003e26,27\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAll statistical analyses were done using STATA v17.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e Further details of this analysis can be found in the Supplementary Digital Content.\u003csup\u003e\u003cspan additionalcitationids=\"CR25 CR26\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePatient Characteristics\u003c/h2\u003e \u003cp\u003eWe identified 82 patients from January 2013 to March 2021 with supratentorial gliomas located in eloquent areas of the brain who had undergone craniotomy for resection with ICM. Thirty (37%) of these patients had at least one postoperative seizure within 6 months of initial resection (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient Characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eNo Seizure\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eSeizure\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;52\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;30\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26(50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26(50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge, Mean (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.1(35.4\u0026ndash;60.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.4(38.7\u0026ndash;67.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge Categories\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9(30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u0026ndash;54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55\u0026ndash;64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u0026ndash;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42(81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25(83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAfrican American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBelow U.S. Median Household Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34(65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17(57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbove U.S. Median Household Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18(35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRUCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMetropolitan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38(73%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMicropolitan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSmall Town/Rural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlioma Type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh Grade Glioma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41(79%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26(87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow Grade Glioma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGBM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35(67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnaplastic Oligodendroglioma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiffuse Astrocytoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOligodendroglioma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnaplastic Astrocytoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLGG, NOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnaplastic Ganglioglioma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLesion Laterality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLeft Side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35(67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRight Side\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17(33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDisease Progression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHistory of Disease Recurrence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18(35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHistory of Seizures Pre-op\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26(50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20(67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of Seizure Pre-op\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26(50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFocal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16(53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneralized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-op AED (PPXvsTRX)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo AED Prior to Surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSeizure Prophylaxis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSeizure Treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26(50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20(67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-op AED Regimen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo AEDs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOne AED\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34(65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18(60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTwo or More AEDs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnesthesia Type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAwake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42(81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22(73%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAsleep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMapping\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMotor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40(77%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22(73%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpeech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27(52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSSEP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9(30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMapping Time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 minutes or less\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23(44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16(53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGreater than 30 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19(37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eImmediate Pre-Monitoring AED Adjustment/Increase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExtent of Resection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSTR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32(62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18(60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGTR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeurosurgeon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeurosurgeon No. 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39(75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25(83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeurosurgeon No. 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeurosurgeon No. 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSeizures - Intraoperative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSeizures - Immediately post-op\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAED at Discharge - Adjustment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34(65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26(87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAED at Discharge - Adjustment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo change in pre-op AED regimen or dose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18(35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMonotherapy with dose increase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplex Adjustment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19(63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAED Type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLevetiracetam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50(96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28(93%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLacosamide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17(57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther AED\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDemographics of the patient and characteristics of the tumors themselves were very similar (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The mean age was 51.0 (IQR 35.4\u0026ndash;60.5) years in the control group and 54.4 (38.7\u0026ndash;67.7) years amongst the seizure group (p = .26). Amongst the controls, 26 (50%) had a preoperative history of seizures (of which 73% were on preoperative AEDs) compared to 20 (67%) of the seizure cases (87% on preoperative AEDs) (p= .14). Six (12%) of the controls and 4 (13%) of the seizure group had intraoperative seizures (p= .81). Most of the patients in both groups were placed on levetiracetam postoperatively [50 (96%) v. 28 (93%)]. There were more patients amongst the seizure cases who were placed on lacosamide postoperatively [6 (12%) vs 17 (57%), p\u0026lt; .001]. Other patient characteristics, pathological diagnosis, intraoperative mapping/resection techniques were found to be similar between groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA Kaplan-Meier estimate of the proportion of patients who experienced at least one postoperative clinical seizure within 6 months was generated. The median time to first postoperative seizure was 7.5 days, with 50% of seizures occurring early. A range of 0 to 190 days to seizure recurrence was observed. Incidence rate of postoperative seizures was 2.61 seizures per 1,000 person-days (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePrimary Outcome\u003c/h2\u003e \u003cp\u003eResults of sensitivity analysis using methodology proposed by VanderWeele and Ding are presented in the Supplementary Digital Content.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e After multivariate logistic regression analysis, we found that patients with a preoperative history of seizures and concurrently taking more than one AED were more likely to have postoperative seizures following surgery (OR 28.45, 95% CI 2.15-375.57, p\u0026thinsp;=\u0026thinsp;0.011). However, history of preoperative seizures alone was not an independent risk factor for postoperative seizures (OR 1.48, 95% CI 0.34\u0026ndash;6.49, p\u0026thinsp;=\u0026thinsp;0.606). Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the multivariate logistic regression comparison between cases and controls for postoperative seizure (Supplementary Digital Content, Table S2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePost-hoc Analysis of Secondary Outcomes\u003c/h3\u003e\n\u003cp\u003ePost-hoc analysis was performed for patients with early seizures and patients with late seizures (Supplementary Digital Content, Tables S3-S4). Upon multivariate logistic regression analysis, preoperative history of seizures, history of preoperative AED usage, and seizures intraoperatively during the mapping portion of the procedure did not confer a higher odds of having early postoperative seizures. Results of this analysis are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOn multivariate logistic regression analysis in patients with late postoperative seizures, patients were found to have a lower odds ratio of having motor mapping during their resection (OR 0.08, 95% CI 0.01\u0026ndash;0.86, p=.037). This association was not seen with regards to speech mapping (OR 0.26, 95% CI 0.01\u0026ndash;6.33, p=.409). Results of this analysis with odds ratios and 95% confidence intervals can be seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003ePost-hoc Bayesian Analysis without Informative Priors\u003c/h3\u003e\n\u003cp\u003eORs with 95% credible intervals are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Several hypotheses were tested. The probability of a prior history of seizures being a risk factor (OR\u0026thinsp;\u0026gt;\u0026thinsp;1) for postoperative seizures was 72.5%. The probability that the use of motor mapping was protective (OR\u0026thinsp;\u0026lt;\u0026thinsp;1) was 91.5%. The probability that awake mapping is protective of postoperative seizures when compared to asleep mapping is 88.1%. The probability that gross total resection was a risk factor for postoperative seizures when compared to those who had subtotal resections was 70.6%. The probability of intraoperative seizures being a risk factor for postoperative seizures was 84.4%. Interestingly, the probability that sensory or language mapping was a risk factor for postoperative seizures was 94.2% and 65.8%, respectively. Monotherapy AED with dose increase alone had a 18.87% probability of acting as a protective factor for late postoperative seizures. A complex AED regimen had 63.35% probability of acting as a protective factor from late postoperative seizures.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePost Hoc Bayesian Analysis using Informative Priors\u003c/h2\u003e \u003cp\u003eORs with 95% credible intervals are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Eseonu \u003cem\u003eet al\u003c/em\u003e. (2017)\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e reports a history of seizures as an independent risk factor for postoperative seizures, and we subsequently updated our priors with this information. The probability that OR\u0026thinsp;\u0026gt;\u0026thinsp;1 for prior history of seizures being a risk factor for postoperative seizures was updated to 82.0%, from 72.5% using non-informative priors (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eProbability of Odds Ratio Estimated by Bayesian Analysis in Patients Undergoing Intraoperative Mapping\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eRisk Factors\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c8\" namest=\"c4\"\u003e \u003cp\u003ePosterior Probability That True OR Is \u0026gt;Specified Threshold, %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePosterior Median OR (95% Credible Interval)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR\u0026thinsp;\u0026gt;\u0026thinsp;1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR\u0026thinsp;\u0026gt;\u0026thinsp;1.2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR\u0026thinsp;\u0026gt;\u0026thinsp;1.5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eOR\u0026thinsp;\u0026gt;\u0026thinsp;1.8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR\u0026thinsp;\u0026gt;\u0026thinsp;2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMinimally Informative Priors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrior History of Seizures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.42 (0.11\u0026ndash;6.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e40.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh Grade Glioma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.95 (0.02\u0026ndash;6.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge 55\u0026ndash;64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.67 (0.09\u0026ndash;21.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e78.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e75.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge 65\u0026ndash;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.82 (0.10-22.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e87.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e77.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e73.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge\u0026thinsp;\u0026gt;\u0026thinsp;75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.59 (0.01\u0026ndash;63.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e84.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e81.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e79.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLanguage Mapping\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.86 (0.02\u0026ndash;9.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e40.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensory Mapping\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.47 (0.15\u0026ndash;23.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e87.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e79.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIntraoperative Seizures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.93 (0.04\u0026ndash;19.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e74.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e68.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e64.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGross Total Resection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.98 (0.14\u0026ndash;5.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e49.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHistory of AED monotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.98 (0.10-34.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e85.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e81.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e78.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHistory of taking 2 or more AEDs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e275.33 (0.22-1007.972)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e99.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e99.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e99.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eData Derived Priors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrior History of Seizures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e43.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProtective Factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c8\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003ePosterior Probability That True OR Is \u0026lt;Specified Threshold, %\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ePosterior Median RR (95% Credible Interval)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eOR\u0026thinsp;\u0026lt;\u0026thinsp;1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eOR\u0026thinsp;\u0026lt;\u0026thinsp;0.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eOR\u0026thinsp;\u0026lt;\u0026thinsp;0.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eOR\u0026thinsp;\u0026lt;\u0026thinsp;0.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eOR\u0026thinsp;\u0026lt;\u0026thinsp;0.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMinimally Informative Priors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMotor Mapping\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.44 (0.01\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e79.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e72.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e63.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAwake Mapping\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.51 (0.01\u0026ndash;1.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e74.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e67.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e58.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eRisk Factors\u003c/h2\u003e \u003cp\u003eIn traditional frequentist analysis, we found that preoperative polytherapy AED regimen for preoperative seizure control was a risk factor for postoperative seizures after glioma resection with ICM, but the presence of preoperative seizures alone was not an independent risk factor (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This may be that patients requiring multiple AEDs have poorly controlled or refractory seizures preoperatively and surgery only serves to exacerbate the condition.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eUpon Bayesian analysis without informative priors, we observed that a history of prior seizures, intraoperative seizures, sensory mapping, language mapping, gross total resection rather than subtotal resection, being of older age, and having a history of monotherapy AED or polytherapy AED were implicated as potential risk factors for seizure following glioma resection with ICM. Several of these results are in line with findings by Conte \u003cem\u003eet al\u003c/em\u003e. (2015)\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, who found frontal tumor location, antiepileptic polytherapy, intraoperative seizures during mapping, and postoperative blood products on imaging to be independent predictors of immediate postoperative seizures. Of note, a history of prior seizures was a potential risk factor, likely because a history of prior seizures may indicate some underlying seizure pathology that would only be aggravated by ICM during glioma resection.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e Gross total resection rather than subtotal resection has an increased likelihood of being a risk factor possibly due to resection closer to epileptogenic regions, increasing the likelihood of potential irritation to these regions. Intraoperative seizures were found to have increased likelihood of being a risk factor possibly for a combination of reasons. High-intensity currents applied directly on the cortex can result in after-discharges (ADs), which can then propagate into clinical seizures, and may occur due to pathological network connectivity, among others. \u003csup\u003e33\u0026ndash;37\u003c/sup\u003e Thus, this seizure provocation that triggered the intraoperative seizure likely persisted into the post-operative period, predisposing the patient to further seizures.\u003c/p\u003e \u003cp\u003eSensory mapping and language mapping were also found to be potential risk factors. These findings can be explained by a study by Chaichana et. al (2009)\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, who found that parietal lobe infiltration by glioma predicted poor seizure control; thus, sensory mapping implies a tumor involvement in a region involved with poor seizure outcomes. Language mapping centers are found in regions of the brain highly associated with seizures as well, explaining the high probability of being a seizure risk factor.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eInterestingly, we further found awake mapping to be a potential protective factor for seizures after glioma resection with ICM. This observation can be explained by a potentially increased resolution of eloquent areas and problematic foci during awake mapping rather than asleep.\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e We also found motor mapping to be a likely protective factor. This may be because motor mapping may be a surrogate for tumor location, as these tumors may have a significant frontal component. In such circumstances, a greater extent of resection may be achievable especially for tumors isolated to the frontal lobes. This more aggressive resection may decrease the odds of seizures in the long-term once patients are past the perioperative period.\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eHowever, these findings may emphasize a couple of potential confounders issues. The definition of seizures is heterogeneous and often subjective; therefore, there may be a misclassification bias. If patients have tumors extending into clinically silent or non-eloquent regions, then their incidence of seizures may be under-reported or clinically silent altogether, affecting our data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eManagement of Seizures following Glioma Resection with ICM\u003c/h2\u003e \u003cp\u003eProphylaxis against intra- and post-operative seizures remains a contested issue.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e Dineen \u003cem\u003eet al.\u003c/em\u003e (2019)\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e found that preoperative loading with intravenous AEDs (levetiracetam, fosphenytoin, lacosamide) decreased the odds of an intraoperative seizure (OR 0.55, p\u0026thinsp;=\u0026thinsp;0.009). However, a prospective randomized trial by Wu \u003cem\u003eet al\u003c/em\u003e. (2013)\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e found that postoperative prophylaxis with phenytoin did not decrease the risk of seizures and was associated with increased medication adverse events. Al-Dorzi \u003cem\u003eet al\u003c/em\u003e. (2017)\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e similarly did not find that postoperative AED prophylaxis decreased seizure incidence.\u003c/p\u003e \u003cp\u003eWe had hypothesized that the initiation of or dose increase in a postoperative AED regimen would be protective against seizures in patients who had resection with ICM. However, via the frequentist approach, we did not find a significant association. But via a Bayesian model, the relationship can be more clearly delineated. We found that AED monotherapy with a postoperative dose increase had less than a 20% probability of protecting against seizures. However, a complex AED regimen (increasing dose\u0026thinsp;+\u0026thinsp;adding additional AEDs or 2 dose adjustments postop) had 63.35% probability of protecting against late postoperative seizures. This discrepancy between frequentist and Bayesian approaches emphasizes one of the other aims of this study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eThe Utility of Bayesian Analysis\u003c/h2\u003e \u003cp\u003eBayesian analysis re-allocates relative credibilities within the set of considered possibilities.\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e There are several advantages to using Bayesian analysis such as allowing researchers to incorporate prior information into current analysis and providing a conceptually simpler multilevel analysis.\u003csup\u003e\u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e However, to conduct Bayesian statistics, prespecified \u0026ldquo;priors\u0026rdquo; is often required. In the present study, we performed analysis both with and without information priors (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), and we relied on various thresholds risk factor thresholds and found the probability of preoperative seizure history increasing the odds of postoperative seizures (OR\u0026thinsp;\u0026gt;\u0026thinsp;1) to be 72.5%. After accounting for findings reported by Eseonu \u003cem\u003eet al\u003c/em\u003e. (2017)\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e the probability of preoperative seizures increasing the odds of postoperative events rose to 82.0%.\u003csup\u003e14\u003c/sup\u003e Bayesian methods allow for the probabilities of associations to be reported and adjusted given prior information (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This framework may be useful in the study of topics that may be otherwise underpowered and may be clinically useful when utilizing different thresholds in order to account for clinical experience. Although a frequentist analytic framework is far more common in the neurosurgical literature, this study highlights the potential utility of using a Bayesian framework. Results from this approach are more intuitive in a clinical setting, especially when considering extant associations or strong \u003cem\u003ea priori\u003c/em\u003e clinical assumptions, and can be very useful in settings with few participants often at risk of an underpowered analysis\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis is a single-institution, retrospective study with all the limitations therein. Multiple oncologic neurosurgeons were included in this series, and differences in intraoperative technique or aggressiveness in ICM may be reflected in the data. However, given that we did not find a significant association between ICM and postoperative seizures, we suspect these technical differences to be marginal. The definition of seizure used as the primary outcome of this study included both subjective and objective criteria. As such, the frequency of these events may be under- or over-reported. However, similar limitations are noted throughout literature and the use of solely objective criteria (EEG findings correlating with clinical events) would likely greatly underestimate seizure frequency. For the present study, we chose to potentially overestimate clinical seizures. For our Bayesian analysis, there was a paucity of informative priors. As such, the majority of the analyses assume non-informative priors and may under-value the results of this technique.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003ePatients with a preoperative history of seizures may be at higher risk for postoperative seizures, and aggressive perioperative seizure prophylaxis may provide a protective benefit from postoperative seizures in patients who undergo intraoperative mapping.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAED\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAnti-epileptic drug\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAfter-Discharges\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eintraoperative cortical mapping\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCOMPLIANCE WITH ETHICAL STANDARDS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This project was supported in part by the National Institute of Neurological Disorders and Stroke of the National Institutes of Health under award number R25NS079188 (DEO). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. DEO was also a Cornwall Clinical Scholar supported by the University of Alabama at Birmingham.\u003c/p\u003e\u003ch2\u003eConflicts of Interest:\u003c/h2\u003e \u003cp\u003eAll authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers\u0026rsquo; bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent, licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eHuman Ethics and Consent to Participate declarations\u003c/strong\u003e \u003cp\u003e All procedures performed in studies involving human participants were in accordance with the ethical standards of the University of Alabama at Birmingham IRB and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was not sought due to the retrospective nature of this study.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eY.S. and D.E.O. wrote the main manuscript text, and prepared all tables and figures. D.E.O. performed primary analysis. P.M. and J.S. performed data extraction. All authors critically reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is available upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHervey-Jumper SL, Berger MS (2016) Maximizing safe resection of low- and high-grade glioma. \u003cem\u003eJournal of Neuro-Oncology\u003c/em\u003e. /11 2016;130(2):269\u0026ndash;282. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11060-016-2110-4\u003c/span\u003e\u003cspan address=\"10.1007/s11060-016-2110-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMa R, Taphoorn MJB, Plaha P (2021) Advances in the management of glioblastoma. 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Where relevant, appropriate permissions have been obtained from the original copyright holder(s), and all original sources have been appropriately acknowledged or referenced\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuarez-Meade P, Marenco-Hillembrand L, Prevatt C et al (2020) Awake vs. asleep motor mapping for glioma resection: a systematic review and meta-analysis. \u003cem\u003eActa Neurochirurgica\u003c/em\u003e. /07/01 2020;162(7):1709\u0026ndash;1720. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00701-020-04357-y\u003c/span\u003e\u003cspan address=\"10.1007/s00701-020-04357-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEnglot DJ, Han SJ, Berger MS, Barbaro NM, Chang EF (2012) Extent of Surgical Resection Predicts Seizure Freedom in Low-Grade Temporal Lobe Brain Tumors. 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Basic and practical concepts for its interpretation and use]. Rev Alerg Mex 2018/09(3):285\u0026ndash;298. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.29262/ram.v65i3.512\u003c/span\u003e\u003cspan address=\"10.29262/ram.v65i3.512\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"glioma, resection, seizure, risk factors, management, bayesian analysis, intraoperative mapping","lastPublishedDoi":"10.21203/rs.3.rs-8705953/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8705953/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"BACKGROUND\nPostoperative seizures can occur secondary to cortical irritation from malignant glioma resection or from direct electrical stimulation of the cortical surface during intraoperative brain mapping. A paucity of literature exists with regards to the use of appropriate seizure risk-reduction strategies for this patient population. The objective of the study was to identify primary risk factors for early and late postoperative seizures following intraoperative brain mapping.\nMETHODS\nThe authors performed a case-control study with 30 patients who had postoperative clinical seizures within 6 months following craniotomies with intraoperative mapping for glioma resection from 2013 to 2021 at a single academic institution. An unmatched control population of all patients (n=52) who had undergone craniotomies with ICM during the same period and had no clinical seizures within 6 months following their operation were used for comparative analysis. Primary endpoint was any postoperative seizure within 6 months of surgery. Outcomes were analyzed both via frequentist and Bayesian statistical approaches.\nRESULTS\nBayesian analysis using non-informative priors demonstrated that the probability of an odds ratio (OR) \u003e 1 for prior history of seizures being a risk factor for postoperative seizures is 73%. The probability that OR \u003c 1 for a patient with post op seizures who underwent motor mapping was 91%. If patients experienced an intraoperative seizure during mapping, the probability of having a postoperative seizure was 84%. Probability that awake mapping is protective of post op seizure when compared to asleep mapping is 88%. Complex anti-epileptic drug (AED) regimen (increasing dose + adding additional AEDs or 2 dose adjustments) had 64% probability of protection from late postoperative seizures.\nCONCLUSION\nPatients with a preoperative history of seizures may be at higher risk for postoperative seizures. More aggressive perioperative seizure prophylaxis may provide a protective benefit from postoperative seizures in patients who undergo intraoperative mapping.","manuscriptTitle":"Postoperative Seizure in Patients with Malignant Glioma Undergoing Tumor Resection with Intraoperative Mapping: Risk Factors, Management Strategies, and the Utility of Bayesian Analysis in a Case-Control Cohort","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-10 16:10:11","doi":"10.21203/rs.3.rs-8705953/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"75897e13-2dbf-4106-a202-4cd190d6abdc","owner":[],"postedDate":"February 10th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-28T14:10:10+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-10 16:10:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8705953","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8705953","identity":"rs-8705953","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}