Prognostic models for predicting posttraumatic seizures during acute hospitalization, and at 1 and 2 years following traumatic brain injury

Seizure Risk Associated With the Use of Transcranial Magnetic Stimulation for Coma Recovery in Individuals With Disordered Consciousness After Severe Traumatic Brain Injury

OBJECTIVE

Repetitive Transcranial Magnetic Stimulation (rTMS) is emerging as a promising treatment for persons with disorder of consciousness (DoC) following traumatic brain injury (TBI). Clinically, however, there are concerns about rTMS exacerbating baseline seizure risk. To advance understanding of risks, this article reports evidence of DoC-TBI rTMS-related seizure risk.

SETTING

Acute and sub-acute hospitals.

PARTICIPANTS

Persons in states of DoC 6.5 months to 15 years after TBI (n = 20) who received active rTMS (n = 17) or placebo rTMS (n = 3). After completing placebo procedures, placebo participants completed active rTMS procedures. These 3 participants are included in the active group.

DESIGN

Meta-analysis of data from 3 clinical trials; 2 within-subject, 1 double blind randomized placebo-controlled. Each trial used the same rTMS protocol, provided at least 30 rTMS sessions, and delivered rTMS to the dorsolateral prefrontal cortex.

MAIN MEASURES

During each study's rTMS treatment phase, seizure occurrences were compared between active and placebo groups using logistic regression. After stratifying active group by presence/absence of seizure occurrences, sub-groups were compared using contingency chi-square tests of independence and relative risk (RR) ratios.

RESULTS

Two unique participants experienced seizures (1 active, 1 placebo). Post seizure, both participants returned to baseline neurobehavioral function. Both participants received antiepileptics during remaining rTMS sessions, which were completed without further seizures. rTMS-related seizure incidence rate is 59 per 1000 persons. Logistic regression revealed no difference in seizure occurrence by treatment condition (active vs placebo) or when examined with seizure risk factors (P > .1). Presence of ventriculoperitoneal shunt elevated seizure risk (RR = 2.0).

CONCLUSION

Collectively, findings indicate a low-likelihood that the specified rTMS protocol exacerbates baseline seizure rates in persons with DoC after TBI. In presence of VP shunts, however, rTMS likely elevates baseline seizure risk and mitigation of this increased risk with pharmacological seizure prophylaxis should be considered.

Prognostic Implications of Early Prediction in Posttraumatic Epilepsy

Posttraumatic epilepsy (PTE) is a complication of traumatic brain injury that can increase morbidity, but predicting which patients may develop PTE remains a challenge. Much work has been done to identify a variety of risk factors and biomarkers, or a combination thereof, for patients at highest risk of PTE. However, several issues have hampered progress toward fully adapted PTE models. Such issues include the need for models that are well-validated, cost-effective, and account for competing outcomes like death. Additionally, while an accurate PTE prediction model can provide quantitative prognostic information, how such information is communicated to inform shared decision-making and treatment strategies requires consideration of an individual patient's clinical trajectory and unique values, especially given the current absence of direct anti-epileptogenic treatments. Future work exploring approaches integrating individualized communication of prediction model results are needed.

Insights into epileptogenesis from post-traumatic epilepsy

Post-traumatic epilepsy (PTE) accounts for 5% of all epilepsies. The incidence of PTE after traumatic brain injury (TBI) depends on the severity of injury, approaching one in three in groups with the most severe injuries. The repeated seizures that characterize PTE impair neurological recovery and increase the risk of poor outcomes after TBI. Given this high risk of recurrent seizures and the relatively short latency period for their development after injury, PTE serves as a model disease to understand human epileptogenesis and trial novel anti-epileptogenic therapies. Epileptogenesis is the process whereby previously normal brain tissue becomes prone to recurrent abnormal electrical activity, ultimately resulting in seizures. In this Review, we describe the clinical course of PTE and highlight promising research into epileptogenesis and treatment using animal models of PTE. Clinical, imaging, EEG and fluid biomarkers are being developed to aid the identification of patients at high risk of PTE who might benefit from anti-epileptogenic therapies. Studies in preclinical models of PTE have identified tractable pathways and novel therapeutic strategies that can potentially prevent epilepsy, which remain to be validated in humans. In addition to improving outcomes after TBI, advances in PTE research are likely to provide therapeutic insights that are relevant to all epilepsies.

The Australian Traumatic Brain Injury Initiative: Systematic Review and Consensus Process to Determine the Predictive Value of Demographic, Injury Event, and Social Characteristics on Outcomes for People With Moderate-Severe Traumatic Brain Injury

The objective of the Australian Traumatic Brain Injury (AUS-TBI) Initiative is to develop a data dictionary to inform data collection and facilitate prediction of outcomes of people who experience moderate-severe TBI in Australia. The aim of this systematic review was to summarize the evidence of the association between demographic, injury event, and social characteristics with outcomes, in people with moderate-severe TBI, to identify potentially predictive indicators. Standardized searches were implemented across bibliographic databases to March 31, 2022. English-language reports, excluding case series, which evaluated the association between demographic, injury event, and social characteristics, and any clinical outcome in at least 10 patients with moderate-severe TBI were included. Abstracts and full text records were independently screened by at least two reviewers in Covidence. A pre-defined algorithm was used to assign a judgement of predictive value to each observed association. The review findings were discussed with an expert panel to determine the feasibility of incorporation of routine measurement into standard care. The search strategy retrieved 16,685 records; 867 full-length records were screened, and 111 studies included. Twenty-two predictors of 32 different outcomes were identified; 7 were classified as high-level (age, sex, ethnicity, employment, insurance, education, and living situation at the time of injury). After discussion with an expert consensus group, 15 were recommended for inclusion in the data dictionary. This review identified numerous predictors capable of enabling early identification of those at risk for poor outcomes and improved personalization of care through inclusion in routine data collection.

Incidence and predictors of early posttraumatic seizures among patients with moderate or severe traumatic brain injury in Northwest Ethiopia: an institution-based prospective study

BACKGROUND

Early posttraumatic seizure (PTS) is a well-known complication of traumatic brain injury (TBI) that can induce the development of secondary brain injuries, including increased intracranial pressure, brain death, and metabolic crisis which may result in worse outcomes. It is also a well-recognized risk factor for the development of late post-traumatic seizure and epilepsy. This study was aimed to assess the incidence and predictors of PTS among patients with moderate or severe TBI admitted to Debre Tabor Comprehensive Specialized Hospital, Northwest Ethiopia.

METHODS AND SETTING

An institutional-based prospective follow-up study was conducted on 402 patients with TBI admitted to the neurologic unit from June 1, 2022 to January 30, 2023. A systematic sampling technique was employed. The incidence rate of occurrence of early PTS was calculated. Both bivariable and multivariable Cox proportional hazard regression was performed. The strength of the association was measured using adjusted hazard ratios with a 95% confidence interval and p-values < 0.05.

RESULTS

The incidence rate of early PTS was 2.7 per 100 person-days observation. Early PTS was observed in 17.7% of TBI patients. Age 75 and above (AHR = 2.85, 95%CI: 1.58-5.39), severe TBI (AHR = 2.06, 95%CI: 1.03-3.71), epidural hematoma (AHR = 2.4, 95% CI: 1.28-4.57), brain contusion (AHR = 2.6, 95%CI: 1.07-4.09), surgical intervention (AHR = 1.7, 95%CI: 1.03-3.82), posttraumatic amnesia (AHR = 1.99, 95%CI: 1.08-3.48), history of comorbidities (AHR = 1.56, 95%CI: 1.08-3.86), and history of alcohol abuse (AHR = 3.1, 95%CI: 1.89-5.23) were potential predictors of early PTS.

CONCLUSION

The incidence of early PTS was high. Since, early PTS can worsen secondary brain damage, knowing the predictors helps to provide an effective management plan for patients likely to develop early PTS and improve their outcome.

Machine Learning and Artificial Intelligence Applications to Epilepsy: a Review for the Practicing Epileptologist

PURPOSE OF REVIEW

Machine Learning (ML) and Artificial Intelligence (AI) are data-driven techniques to translate raw data into applicable and interpretable insights that can assist in clinical decision making. Some of these tools have extremely promising initial results, earning both great excitement and creating hype. This non-technical article reviews recent developments in ML/AI in epilepsy to assist the current practicing epileptologist in understanding both the benefits and limitations of integrating ML/AI tools into their clinical practice.

RECENT FINDINGS

ML/AI tools have been developed to assist clinicians in almost every clinical decision including (1) predicting future epilepsy in people at risk, (2) detecting and monitoring for seizures, (3) differentiating epilepsy from mimics, (4) using data to improve neuroanatomic localization and lateralization, and (5) tracking and predicting response to medical and surgical treatments. We also discuss practical, ethical, and equity considerations in the development and application of ML/AI tools including chatbots based on Large Language Models (e.g., ChatGPT). ML/AI tools will change how clinical medicine is practiced, but, with rare exceptions, the transferability to other centers, effectiveness, and safety of these approaches have not yet been established rigorously. In the future, ML/AI will not replace epileptologists, but epileptologists with ML/AI will replace epileptologists without ML/AI.

Vagus nerve stimulation for refractory posttraumatic epilepsy: Efficacy and predictors of seizure outcome

Background

Traumatic brain injury (TBI) has been recognized as an important and common cause of epilepsy since antiquity. Posttraumatic epilepsy (PTE) is usually associated with drug resistance and poor surgical outcomes, thereby increasing the burden of the illness on patients and their families. Vagus nerve stimulation (VNS) is an adjunctive treatment for medically refractory epilepsy. This study aimed to determine the efficacy of VNS for refractory PTE and to initially evaluate the potential predictors of efficacy.

Methods

We retrospectively collected the outcomes of VNS with at least a 1-year follow-up in all patients with refractory PTE. Subgroups were classified as responders and non-responders according to the efficacy of VNS (≥50% or <50% reduction in seizure frequency). Preoperative data were analyzed to screen for potential predictors of VNS efficacy.

Results

In total, forty-five patients with refractory PTE who underwent VNS therapy were enrolled. Responders were found in 64.4% of patients, and 15.6% of patients achieved seizure freedom at the last follow-up. In addition, the responder rate increased over time, with 37.8, 44.4, 60, and 67.6% at the 3-, 6-, 12-, and 24-month follow-ups, respectively. After multivariate analysis, generalized interictal epileptic discharges (IEDs) were found to be a negative predictor (OR: 4.861, 95% CI: 1.145–20.632) of VNS efficacy.

Conclusion

The results indicated that VNS therapy was effective in refractory PTE patients and was well tolerated over a 1-year follow-up period. Patients with focal or multifocal IEDs were recognized to have better efficacy after VNS therapy.

Frequency of epileptic seizures in patients undergoing decompressive craniectomy after ischemic stroke

BACKGROUND

Decompressive surgery has proven to be lifesaving in patients with a malignant anterior circulation ischemic stroke. Recently, some studies have shown a high frequency of epileptic seizures in patients undergoing this procedure. However, the quantification of this risk and its associated factors have not been extensively investigated.

OBJECTIVE

To determine the frequency of epileptic seizures and epilepsy in patients with an anterior circulation ischemic stroke admitted to our Stroke Unit from January 2006 to March 2019 that have been submitted to craniectomy and to study their associated demographic, clinical, imagiological and neurophysiological features.

METHODS

Retrospective observational study of 56 consecutive patients with an anterior circulation ischemic stroke that have undergone craniectomy. The frequency of seizures was both clinically and neurophysiologically assessed after reviewing clinical records, discharge or death reports and all EEGs performed during the hospital admission. Bivariate analysis was used to compare patients with and without seizures.

RESULTS

Sixteen patients (28,6%) had epileptic seizures. Bivariate analysis showed an association between the occurrence of unprovoked seizures and the median ASPECTS from the first CT performed.

CONCLUSIONS

In this study, the frequency of epileptic seizures after a malignant stroke submitted to craniectomy was high, albeit lower than that reported in previous studies. The size of infarction at hospital admission appears to be a risk factor for the occurrence of epilepsy in this group of patients.

Risk Factors and Prognosis of Early Posttraumatic Seizures in Moderate to Severe Traumatic Brain Injury

IMPORTANCE

Early posttraumatic seizures (EPS) that may occur following a traumatic brain injury (TBI) are associated with poorer outcomes and development of posttraumatic epilepsy (PTE).

OBJECTIVE

To evaluate risk factors for EPS, associated morbidity and mortality, and contribution to PTE.

DESIGN, SETTING, AND PARTICIPANTS

Data were collected from an Australian registry-based cohort study of adults (age ≥18 years) with moderate to severe TBI from January 2005 to December 2019, with 2-year follow-up. The statewide trauma registry, conducted on an opt-out basis in Victoria (population 6.5 million), had 15 152 patients with moderate to severe TBI identified via Abbreviated Injury Scale (AIS) head severity score, with an opt-out rate less than 0.5% (opt-out n = 136).

MAIN OUTCOMES AND MEASURES

EPS were identified via International Statistical Classification of Diseases, Tenth Revision, Australian Modification (ICD-10-AM) codes recorded after the acute admission. Outcome measures also included in-hospital metrics, 2-year outcomes including PTE, and post-discharge mortality. Adaptive least absolute shrinkage and selection operator (LASSO) regression was used to build a prediction model for risk factors of EPS.

RESULTS

Among the 15 152 participants (10 457 [69%] male; median [IQR] age, 60 [35-79] y), 416 (2.7%) were identified with EPS, including 27 (0.2%) with status epilepticus. Significant risk factors on multivariable analysis for developing EPS were younger age, higher Charlson Comorbidity Index, TBI sustained from a low fall, subdural hemorrhage, subarachnoid hemorrhage, higher Injury Severity Score, and greater head injury severity, measured using the AIS and Glasgow Coma Score. After adjustment for confounders, EPS were associated with increased ICU admission and ICU length of stay, ventilation and duration, hospital length of stay, and discharge to inpatient rehabilitation rather than home, but not in-hospital mortality. Outcomes in TBI admission survivors at 24 months, including mortality (relative risk [RR] = 2.14; 95% CI, 1.32-3.46; P = .002), development of PTE (RR = 2.91; 95% CI, 2.22-3.81; P < .001), and use of antiseizure medications (RR = 2.44; 95% CI, 1.98-3.02; P < .001), were poorer for cases with EPS after adjustment for confounders. The prediction model for EPS had an area under the receiver operating characteristic curve of 0.72 (95% CI, 0.66-0.79), sensitivity of 66%, and specificity of 73% in the validation set.

DISCUSSION

We identified important risk factors for EPS following moderate to severe TBI. Early posttraumatic seizures were associated with longer ICU and hospital admissions, ICU ventilation, and poorer 24-month outcomes including mortality and development of PTE.

An Artificial Neural Network Prediction Model for Posttraumatic Epilepsy: Retrospective Cohort Study

Background

Posttraumatic epilepsy (PTE) is a common sequela after traumatic brain injury (TBI), and identifying high-risk patients with PTE is necessary for their better treatment. Although artificial neural network (ANN) prediction models have been reported and are superior to traditional models, the ANN prediction model for PTE is lacking.

Objective

We aim to train and validate an ANN model to anticipate the risks of PTE.

Methods

The training cohort was TBI patients registered at West China Hospital. We used a 5-fold cross-validation approach to train and test the ANN model to avoid overfitting; 21 independent variables were used as input neurons in the ANN models, using a back-propagation algorithm to minimize the loss function. Finally, we obtained sensitivity, specificity, and accuracy of each ANN model from the 5 rounds of cross-validation and compared the accuracy with a nomogram prediction model built in our previous work based on the same population. In addition, we evaluated the performance of the model using patients registered at Chengdu Shang Jin Nan Fu Hospital (testing cohort 1) and Sichuan Provincial People’s Hospital (testing cohort 2) between January 1, 2013, and March 1, 2015.

Results

For the training cohort, we enrolled 1301 TBI patients from January 1, 2011, to December 31, 2017. The prevalence of PTE was 12.8% (166/1301, 95% CI 10.9%-14.6%). Of the TBI patients registered in testing cohort 1, PTE prevalence was 10.5% (44/421, 95% CI 7.5%-13.4%). Of the TBI patients registered in testing cohort 2, PTE prevalence was 6.1% (25/413, 95% CI 3.7%-8.4%). The results of the ANN model show that, the area under the receiver operating characteristic curve in the training cohort was 0.907 (95% CI 0.889-0.924), testing cohort 1 was 0.867 (95% CI 0.842-0.893), and testing cohort 2 was 0.859 (95% CI 0.826-0.890). Second, the average accuracy of the training cohort was 0.557 (95% CI 0.510-0.620), with 0.470 (95% CI 0.414-0.526) in testing cohort 1 and 0.344 (95% CI 0.287-0.401) in testing cohort 2. In addition, sensitivity, specificity, positive predictive values and negative predictors in the training cohort (testing cohort 1 and testing cohort 2) were 0.80 (0.83 and 0.80), 0.86 (0.80 and 0.84), 91% (85% and 78%), and 86% (80% and 83%), respectively. When calibrating this ANN model, Brier scored 0.121 in testing cohort 1 and 0.127 in testing cohort 2. Compared with the nomogram model, the ANN prediction model had a higher accuracy (P=.01).

Conclusions

This study shows that the ANN model can predict the risk of PTE and is superior to the risk estimated based on traditional statistical methods. However, the calibration of the model is a bit poor, and we need to calibrate it on a large sample size set and further improve the model.

Repeated traumatic brain injury and risk of epilepsy: a Danish nationwide cohort study

Traumatic brain injury is associated with increased risk of epilepsy, but the importance of repeated traumatic brain injuries has not yet been established. We performed a nationwide population-based cohort study of 2 476 905 individuals born in Denmark between 1977 and 2016. We estimated hazard ratios (HRs) and the cumulative incidence of epilepsy following traumatic brain injury using Cox and competing risk regression, respectively. To estimate the cumulative incidence of epilepsy in the population without traumatic brain injury, we matched 10 controls for each subject with traumatic brain injury on year of birth, sex, and date of brain insult in the index person. In the cohort, traumatic brain injury was sustained by 167 051 subjects (71 162 females and 95 889 males), and 37 200 individuals developed epilepsy (17 905 females and 19 295 males). Compared with subjects without traumatic brain injury, the relative risk of epilepsy increased after a first traumatic brain injury [HR 2.04, 95% confidence interval (CI) 1.96-2.13] and even more after a second traumatic brain injury (HR 4.45, 95% CI 4.09-4.84). The risk increased with the severity of the first and the second traumatic brain injury, most notably after severe traumatic brain injuries. Females were more likely than males to develop epilepsy after mild traumatic brain injury (HR 2.13, 95% CI 2.00-2.28 versus HR 1.77, 95% CI 1.66-1.88; P < 0.0001); in contrast, males were more likely than females to develop epilepsy after severe traumatic brain injury (HR 5.00, 95% CI 4.31-5.80 versus 3.21, 95% CI 2.56-4.03; P = 0.0012). The risk remained increased for decades after the traumatic brain injury. This knowledge may inform efforts to prevent the development of post-traumatic epilepsy.

Antiepileptogenesis and disease modification: Clinical and regulatory issues

This is a summary report of clinical and regulatory issues discussed at the 2018 NINDS workshop, entitled “Accelerating Therapies for Antiepileptogenesis and Disease Modification.” The intent of the workshop was to optimize and accelerate development of therapies for antiepileptogenesis (AEG) and disease modification in the epilepsies. The working group discussed nomenclature for antiepileptogenic therapies, subdividing them into “antiepileptogenic therapies” and “disease modifying therapies,” both of which are urgently needed. We use the example of traumatic brain injury to explain issues and complexities in designing a trial for disease‐preventing antiepileptogenic therapies, including identifying timing of intervention, selecting the appropriate dose, and the need for biomarkers. We discuss the recent trials of vigabatrin to prevent onset and modify epilepsy outcome in children with tuberous sclerosis (Epistop and PreVeNT). We describe a potential approach to a disease modification trial in adults, using patients with temporal lobe epilepsy. Finally, we discuss regulatory hurdles for antiepileptogenesis and disease‐modifying trials.

Development and external validation of a predictive nomogram model of posttraumatic epilepsy: A retrospective analysis

OBJECTIVE

We aimed to develop and validate a predictive model of posttraumatic epilepsy (PTE).

METHODS

The training cohort was patients registered at West China Hospital and diagnosed as traumatic brain injury (TBI) between January 1, 2011, and December 31, 2017. On the basis of multivariable cox proportional hazards model using a forward stepwise method, the nomogram was generated. We externally validated this instrument in 834 participants from two independent cohorts to assess its performance.

RESULTS

The nomogram was built based on the results of multivariable cox proportional hazards regression analysis of 1301patients from West China Hospital. The prevalence of PTE was 12.8% (95% confidence interval [CI], 10.9-14.6%) in training cohort, 10.5% (95% CI, 7.5-13.4%) in the testing 1 cohort, and 6.1% (95% CI, 3.7-8.4%) in the testing 2 cohort. 7 independent predictors of PTE composed the nomogram (sex, time of loss of consciousness, subdural hemorrhage, contusion sites, early posttraumatic seizures, TBI severity, and treatment). The C-index was 0.846 (95% CI, 0.817-0.876), and the corresponding sensitivity and specificity were 0.867 and 0.738. External validations showed good discrimination in overall testing cohorts with a C-index of 0.895 (95% CI, 0.859-0.930), in the testing 1 cohort (C-index 0.897, 95% CI, 0.855-0.938) and testing 2 cohort (C-index, 0.883, 95% CI, 0.814-0.952). Calibration of this model was also good since the calibration plots were close to the ideal line.

CONCLUSIONS

This nomogram was developed and validated in a large cohort for individualized prediction of PTE, which can identify individuals at high risk of epilepsy and help us find preventive drugs based on these targeted population.

The Traumatic Brain Injury Model Systems National Database: A Review of Published Research

The Traumatic Brain Injury Model Systems (TBIMS) is the largest longitudinal TBI data set in the world. Our study reviews the works using TBIMS data for analysis in the last 5 years. A search (2015–2020) was conducted across PubMed, EMBASE, and Google Scholar for studies that used the National Institute on Disability, Independent Living and Rehabilitation Research NIDILRR/VA-TBIMS data. Search terms were as follows: [“TBIMS” national database] within PubMed and Google Scholar, and [“TBIMS” AND national AND database] on EMBASE. Data sources, study foci (in terms of data processing and outcomes), study outcomes, and follow-up information usage were collected to categorize the studies included in this review. Variable usage in terms of TBIMS' form-based variable groups and limitations from each study were also noted. Assessment was made on how TBIMS' objectives were met by the studies. Of the 74 articles reviewed, 23 used TBIMS along with other data sets. Fifty-four studies focused on specific outcome measures only, 6 assessed data aspects as a major focus, and 13 explored both. Sample sizes of the included studies ranged from 11 to 15,835. Forty-two of the 60 longitudinal studies assessed follow-up from 1 to 5 years, and 15 studies used 10 to 25 years of the same. Prominent variable groups as outcome measures were “Employment,” “FIM,” “DRS,” “PART-O,” “Satisfaction with Life,” “PHQ-9,” and “GOS-E.” Limited numbers of studies were published regarding tobacco consumption, the Brief Test of Adult Cognition by Telephone (BTACT), the Supervision Rating Scale (SRS), general health, and comorbidities as variables of interest. Generalizability was the most significant limitation mentioned by the studies. The TBIMS is a rich resource for large-sample longitudinal analyses of various TBI outcomes. Future efforts should focus on under-utilized variables and improving generalizability by validation of results across large-scale TBI data sets to better understand the heterogeneity of TBI.

Resective surgery for drug-resistant posttraumatic epilepsy: predictors of seizure outcome

OBJECTIVE

The object of this study was to evaluate surgical outcomes and prognosis factors in patients with drug-resistant posttraumatic epilepsy (PTE) who had undergone resective surgery.

METHODS

The authors retrospectively reviewed the records of all patients with drug-resistant PTE who had undergone resective surgery at Sanbo Brain Hospital, Capital Medical University, in the period from January 2008 to December 2016. All patients had a follow-up period of at least 2 years. Seizure outcomes were evaluated according to the International League Against Epilepsy (ILAE) classification. Patients in ILAE classes 1 and 2 during the last 2 years of follow-up were classified as having a favorable outcome; patients in all other classes were considered to have an unfavorable outcome. Univariate analysis and a multivariate logistic regression model in a backward fashion were used to identify the potential predictors of seizure outcomes.

RESULTS

Among 90 patients with a follow-up of 2-10 years (mean ± standard deviation, 5.79 ± 2.84 years), 70% (63 patients) were seizure free, of whom 68.9% (62 patients) had an ILAE class 1 outcome and 1.1% (1 patient) had an ILAE class 2 outcome. Permanent neurological deficits were observed in 10 patients (11.1%). Univariate and multivariate analyses revealed that only the duration of seizures ≤ 8 years was an independent predictor of a favorable seizure outcome (OR 0.34, 95% CI 0.13-0.92).

CONCLUSIONS

Resective surgery is an effective treatment for patients with drug-resistant PTE with an acceptable incidence of complications. The information on prognosis factors suggests that early surgery may offer more benefits to patients with drug-resistant PTE.

Prophylactic levetiracetam-induced pancytopenia with traumatic extra-dural hematoma: Case report

BACKGROUND

Pancytopenia has only rarely been reported with Levetiracetam use. It is a potentially life threatening adverse effect that requires cessation of therapy.

CASE DESCRIPTION

We describe a case of an otherwise well thirty-two-year-old man who underwent an emergent craniotomy for evacuation of a traumatic extra-dural haematoma. Post-operatively, he developed pancytopenia which corrected with cessation of levetiracetam.

CONCLUSION

This report aims to increase awareness of this rare side effect and reiterates the judicious use of prophylactic levetiracetam in brain trauma.

Epilepsy after severe traumatic brain injury: frequency and injury severity

Objective: To estimate national frequency of posttraumatic epilepsy (PTE) after severe traumatic brain injury (TBI) and assess injury severity (Glasgow Coma Scale (GCS) and posttraumatic amnesia (PTA)) as prognostic factors for PTE.

METHODS

Data on patients ≥18 years surviving severe TBI 2004-2016 were retrieved from the Danish Head Trauma Database (n = 1010). The cumulative incidence proportion (CIP) was estimated using death as competing event. The association between injury severity and PTE was assessed using multivariable competing risk regressions.

RESULTS

CIP of PTE 28 days and one year post-TBI was 6.8% (95% confidence interval (CI) 5.4-8.5) and 18.5% (95% CI 16.1-21.1%), respectively. Injury severity was not associated with PTE within 28 days post-TBI but indicated higher PTE-rates in less severely injured patients. PTA-duration >70 days was associated with PTE 29-365 days post-TBI (Adjusted sub-hazard ratio 4.23 (95% CI 1.79-9.99)). GCS was not associated with PTE 29-365 days post-TBI.

CONCLUSION

The PTE frequency was higher compared to previous estimates. Increasing injury severity was associated with PTE 29-365 days post-TBI when measured with PTA, but not with GCS. Though nonsignificant, the increased PTE-risk within 28 days in lower severity suggests an underdiagnosing of PTE.

Epidemiology of traumatic brain injury-associated epilepsy in western China: An analysis of multicenter data

OBJECTIVES

This study aims to explore the probability of developing posttraumatic epilepsy (PTE) in the following 8 years after traumatic brain injury (TBI), the risk factors associated with PTE and its cumulative prevalence.

METHODS

This is a retrospective follow-up study of patients with traumatic brain injury (TBI) discharged from the West China Hospital between January 1, 2011 and December 31, 2017, Chengdu Shang Jin Nan Fu Hospital and Sichuan Provincial People's Hospital from January 1, 2013 to March 1, 2015. We used forward stepwise method to build the final multivariate cox proportional hazard regression model to obtain estimates of hazard ratio (HR) of PTE and 95% confidence intervals (CI). We also conducted Kaplan-Meier survival analysis to investigate the cumulative prevalence of PTE.

RESULTS

The cumulative incidence of PTE rose from 6.2% in one year to 10.6% in eight years. There were more male patients in PTE group and generally older. Besides, patients with PTE tended to have abnormal CT scan results. The risk factors of PTE were male (HR = 1.6, 95% CI: 1.1-2.2, P = 0.009), early posttraumatic seizures (HR = 2.9, 95% CI: 2.2-4.1, P < 0.001), TBI severity (moderate TBI: HR = 3.0, 95% CI: 1.8-5.0, P = 0.001; severe TBI: HR = 4.3, 95% CI: 2.3-7.6, P < 0.029), loss of consciousness (LOC) more than 30 min (30 min-24 h: HR = 1.8, 95% CI: 1.02-3.1, P = 0.041; >24 h: HR = 2.4, 95% CI: 1.4-2.4, P = 0.001), subdural hematoma (SDH) (HR = 1.9, 95% CI: 1.4-2.5, P < 0.001), brain contusion sites (frontal-temporal lobe: HR = 2.7, 95% CI: 1.9-3.9, P < 0.001; other sites: HR = 1.5, 95% CI: 1.01-2.3, P = 0.042) and cranial surgery (HR = 1.7, 95% CI: 1.3-2.3, P < 0.001).

SIGNIFICANCE

The probability of developing PTE increased during the study period. In addition, the risk of developing PTE was significantly associated with gender, EPTS, LOC time, SDH, brain contusion sites, surgery and TBI severity. However, further researches may be needed to predict the risk of PTE in combination with quantitative factors.

The coexistence of psychogenic nonepileptic and epileptic seizures in the same patient is more frequent than expected: Is there any clinical feature for defining these patients?

OBJECTIVES

This study aimed to investigate the prevalence of psychogenic nonepileptic seizures (PNES) and PNES-epilepsy coexistence within all video-electroencephalography (EEG) monitoring unit (VEMU) referrals and to identify semiological and electrophysiological features to differentiate patients with PNES-epilepsy coexistence from PNES-only.

METHODS

We retrospectively reviewed medical files, VEMU reports, and videos of 1983 adult patients. Demographical, historical, clinical, neuroimaging, and electrophysiological parameters of all patients were recorded. We classified patients into five groups as definite PNES-only, definite PNES-epilepsy coexistence, definite PNES-probable epilepsy coexistence, probable PNES-definite epilepsy coexistence, and probable PNES-only. We defined a "definite" group when we saw the ictal EEG and/or video recording of the seizure. The "probable" term is used when there is strong evidence from the history of a particular seizure type and suggestive interictal EEGs without video recordings.

RESULTS

Two hundred and three of 1983 patients (10.23%) had PNES. Sixty-six of patients with PNES (32.51%) had definite PNES-epilepsy coexistence. When probable cases were included, the PNES-epilepsy coexistence ratio was 53.69% within all patients with PNES. The prevalence of PNES-epilepsy coexistence was 3.32% within all our VEMU referrals. Lower high school graduation rate, earlier age of disease onset, history of status epilepticus, febrile convulsion and brain surgery, use of three or more antiepileptic drugs, and abnormal magnetic resonance imaging (MRI) findings supported PNES-epilepsy coexistence (p < 0.05). On the contrary, seizure duration longer than 10 min was in favor of PNES-only (p < 0.05).

CONCLUSIONS

The prevalence of PNES-epilepsy coexistence might be more frequent in VEMUs than expected. Some demographic and semiological features and electrophysiological findings might be useful in differentiating patients with PNES-epilepsy coexistence from patients with PNES-only.

Predictive Risk Factors for Early Seizures in Traumatic Brain Injury

Background Early posttraumatic seizure (PTS) is a significant cause of unfavorable outcomes in traumatic brain injury (TBI). This study was aimed to investigate the incidence and determine a predictive model for early PTS.

Materials and Methods A prospective cohort study of 484 TBI patients was conducted. All patients were evaluated for seizure activities within 7 days after the injury. Risk factors for early PTS were identified using univariate analysis. The candidate risk factors with p < 0.1 were selected into multivariable logistic regression analysis to identify predictors of early PTS. The fitting model and the power of discrimination with the area under the receiver operating characteristic (AUROC) curve were demonstrated. The nomogram for prediction of early PTS was developed for individuals.

Results There were 27 patients (5.6%) with early PTS in this study. The final model illustrated chronic alcohol use (odds ratio [OR]: 4.06, 95% confidence interval [CI]: 1.64–10.07), epidural hematoma (OR: 3.98, 95% CI: 1.70–9.33), and Glasgow Coma Scale score 3–8 (OR: 3.78, 95% CI: 1.53–9.35) as predictors of early PTS. The AUROC curve was 0.77 (95% CI: 0.66–0.87).

Conclusions The significant predictors for early PTS were chronic alcohol use, epidural hematoma, and severe TBI. Our nomogram was considered as a reliable source for prediction.

Thirty Years of National Institute on Disability, Independent Living, and Rehabilitation Research Traumatic Brain Injury Model Systems Center Research-An Update

The Traumatic Brain Injury Model Systems Center (TBIMSC) program was established by the National Institute on Disability, Independent Living, and Rehabilitation Research in 1987, with the goal of conducting research to improve the care and outcomes for individuals with moderate-to-severe traumatic brain injury (TBI). This article provides an update on TBIMSC research program activities since 2010 when a similar article was published. It includes (1) discussion of TBIMSC program management and infrastructure; (2) detail on the management, data quality, access, use, and knowledge translation of the TBIMSC National Database, with more than 16 000 participants with follow-up out to 25 years postinjury to date; (3) an overview of the TBIMSC site-specific studies and collaborative module research; (4) highlights of several collaborative initiatives between the TBIMSCs and other federal, advocacy, and research stakeholders; (5) an overview of the vast knowledge translation occurring through the TBIMSC program; and (6) discussion of issues that impact on the data collection methods for and contents of the TBIMSC National Database. On the occasion of the 30th anniversary of the TBIMSC program, this article highlights many of the accomplishments of this well-established, multicenter TBI research consortium.

Pharmacological management of post-traumatic seizures in adults: current practice patterns in the UK and the Republic of Ireland

Background

Patient selection for seizure prophylaxis after traumatic brain injury (TBI) and duration of anti-epileptic drug treatment for patients with early post-traumatic seizures (PTS), remain plagued with uncertainty. In early 2017, a collaborative group of neurosurgeons, neurologists, neurointensive care and rehabilitation medicine physicians was formed in the UK with the aim of assessing variability in current practice and gauging the degree of uncertainty to inform the design of future studies. Here we present the results of a survey of clinicians managing patients with TBI in the UK and Ireland.

Materials and methods

An online survey was developed and piloted. Following approval by the Academic Committee of the Society of British Neurological Surgeons, it was distributed via appropriate electronic mailing lists.

Results

One hundred and seventeen respondents answered the questionnaire, predominantly neurosurgeons (76%) from 30 (of 32) trauma-receiving hospitals in the UK and Ireland. Fifty-three percent of respondents do not routinely use seizure prophylaxis, but 38% prescribe prophylaxis for one week. Sixty percent feel there is uncertainty regarding the use of seizure prophylaxis, and 71% would participate in further research to address this question. Sixty-two percent of respondents use levetiracetam for treatment of seizures during the acute phase, and 42% continued for a total of 3 months. Overall, 90% were uncertain about the duration of treatment for seizures, and 78% would participate in further research to address this question.

Conclusion

The survey results demonstrate the variation in practice and uncertainty in both described aspects of management of patients who have suffered a TBI. The majority of respondents would want to participate in future research to help try and address this critical issue, and this shows the importance and relevance of these two clinical questions.

Electronic supplementary material

The online version of this article (10.1007/s00701-018-3683-9) contains supplementary material, which is available to authorized users.

Variability with Astroglial Glutamate Transport Genetics Is Associated with Increased Risk for Post-Traumatic Seizures

Excitotoxicity contributes to epileptogenesis after severe traumatic brain injury (sTBI). Demographic and clinical risk factors for post-traumatic seizures (PTS) have been identified, but genetic risk remains largely unknown. Thus, we investigated whether genetic variation in astroglial glutamate transporter genes is associated with accelerated epileptogenesis and PTS risk after sTBI. Adults (n = 267) 18-75 years old were assessed over a three-year period post-TBI. Single nucleotide polymorphisms (SNPs) throughout the SLC1A2 and SLC1A3 genes were assayed. Kaplan-Meier estimates and log-rank statistics were used to compare seizure frequencies by genotype. Multivariate Cox proportional hazards regression was used to estimate hazard ratios (HRs) for genotypes significant in Kaplan-Meier analyses. Thirty-nine tagging SNPs were examined (SLC1A2: n = 21, SLC1A3: n = 18). PTS developed in 57 (21.4%) individuals. Of those with PTS, n = 20 (35.7%) had an immediate/early seizure within the first seven days, and n = 36 (64.3%) had a late seizure occurring between eight days and three years post-TBI. When adjusting for multiple comparisons, rs4869682 genotypes (SLC1A3, GG vs. T-carriers) were associated with time to first seizure (p = 0.003). Median time until first seizure was 20.4 days for individuals with a GG genotype and 44.8 days for T-carriers. After adjusting for covariates, rs4869682 GG-homozygotes had a 2.05 times increased PTS risk versus T-carriers (aHR = 2.08, 95% confidence interval: 1.20, 3.62, p = 0.009). Variation within SLC1A3 is associated with accelerated epileptogenesis and clinical PTS development after sTBI. Future studies should validate these findings and examine how genetic variation at rs4869682 may be a target for PTS prevention and treatment.

TBI Rehabilomics Research: Conceptualizing a humoral triad for designing effective rehabilitation interventions

Most areas of medicine use biomarkers in some capacity to aid in understanding how personal biology informs clinical care. This article draws upon the Rehabilomics research model as a translational framework for programs of precision rehabilitation and intervention research focused on linking personal biology to treatment response using biopsychosocial constructs that broadly represent function and that can be applied to many clinical populations with disability. The summary applies the Rehabilomics research framework to the population with traumatic brain injury (TBI) and emphasizes a broad vision for biomarker inclusion, beyond typical brain-derived biomarkers, to capture and/or reflect important neurological and non-neurological pathology associated with TBI as a chronic condition. Humoral signaling molecules are explored as important signaling and regulatory drivers of these chronic conditions and their impact on function. Importantly, secondary injury cascades involved in the humoral triad are influenced by the systemic response to TBI and the development of non-neurological organ dysfunction (NNOD). Biomarkers have been successfully leveraged in other medical fields to inform pre-randomization patient selection for clinical trials, however, this practice largely has not been utilized in TBI research. As such, the applicability of the Rehabilomics research model to contemporary clinical trials and comparative effectiveness research designs for neurological and rehabilitation populations is emphasized. Potential points of intervention to modify inflammation, hormonal, or neurotrophic support through rehabilitation interventions are discussed. This article is part of the Special Issue entitled "Novel Treatments for Traumatic Brain Injury".

Mortality after traumatic brain injury and the effect of posttraumatic epilepsy

Objective

To assess the effect of posttraumatic epilepsy (PTE) on mortality and causes of death after traumatic brain injury (TBI).

Methods

Medical reports were collected retrospectively of patients who sustained TBI between 1996 and 2013. After defining patients with PTE and picking up 2 non-PTE matched TBI controls for every patient with PTE, the database included 714 patients. Demographic data, cause and mechanism of injury, nature of injury (focal injury, intracranial bleeding), time from accident to first seizure, remission rates, neurosurgical operations undertaken, and mortality data were collected.

Results

Of the 714 patients, 555 (77.7%) were men and 159 (22.3%) were women. There was an obvious increase in long-term mortality in patients with PTE compared to control TBI patients. This increase became evident after about 1 year from the injury, when approximately 95% of both non-PTE and PTE patients were alive; after that, the difference in mortality increased. The difference remained significant at least up to 15 years from the injury, when around 65% of non-PTE patients with TBI were alive compared to only 45% of patients with PTE. In patients with PTE, the mortality was 1.75 times higher (p = 0.0001). There was no significant difference in causes of death.

Conclusion

This study shows that long-term mortality is higher in patients with PTE than other patients with TBI, although the reasons for this difference remain unclear.

Craniectomy and Craniotomy in Traumatic Brain Injury: A Propensity-Matched Analysis of Long-Term Functional and Quality of Life Outcomes

OBJECTIVE

To report the comprehensive long-term functional and quality of life outcomes after craniectomy (CE) and craniotomy (CO) in individuals with traumatic brain injury (TBI).

METHODS

Information on all individuals with TBI who had undergone CE or CO were extracted from the TBI Model Systems database from 2002 to 2012. A 1:1 propensity matching with replacement technique was used to balance the baseline characteristics across groups. The matched sample was analyzed for outcomes during hospitalization, acute rehabilitation, and ≤2 years of follow-up.

RESULTS

We identified 1470 individuals who had undergone CE or CO. Individuals undergoing CE compared with CO demonstrated a longer length of stay in the hospital (median, 22 vs. 18 days; P < 0.0001) and acute rehabilitation (median 26 vs. 21 days; P < 0.0001). Individuals with CE had required rehospitalization more often by the 1-year follow-up point (39% vs. 25%; P < 0.0001) for reasons other than cranioplasty, including seizures (12% vs. 8%; P < 0.0001), neurologic events (i.e., hydrocephalus; 9% vs. 4%; P < 0.0001), and infections (10% vs 6%; P < 0.0001). Individuals with CE had significantly greater impairment using the Glasgow Outcome Scale-Extended, required more supervision, and were less likely to be employed at 1 and 2 years after TBI. No difference was observed in the satisfaction with life scale scores at 2 years. The Kaplan-Meier mortality estimates at 1 and 2 years showed no differences between the 2 groups (hazard ratio, 0.57; P = 0.4).

CONCLUSION

In a matched cohort, individuals undergoing CE compared with CO after TBI had a longer length of stay, decreased functional status, and more rehospitalizations. The survival at 2 years and the satisfaction with life scale scores were similar.

Treatment options for posttraumatic epilepsy

PURPOSE OF REVIEW

Posttraumatic seizures (PTS) and posttraumatic epilepsy (PTE) are common and debilitating consequences of traumatic brain injury (TBI). Early PTS result in secondary brain injury by raising intracranial pressure and worsening cerebral edema and metabolic crisis. PTE is a localization-related epilepsy strongly associated with TBI severity, but risk factors for PTE and epileptogenesis are incompletely understood and are active areas of research. Medical management of PTS in adults and children is reviewed. Surgical options for posttraumatic drug-resistant epilepsy are also discussed.

RECENT FINDINGS

Continuous electroencephalography is indicated for children and adults with TBI and coma because of the high incidence of nonconvulsive seizures, periodic discharges, and associated secondary brain injury in this population. Neuroinflammation is a central component of secondary brain injury and appears to play a key role in epileptogenesis. Levetiracetam is increasingly used for seizure prophylaxis in adults and children, but variability remains.

SUMMARY

PTS occur commonly after TBI and are associated with secondary brain injury and worse outcomes in adults and children. Current medical and surgical management options for PTS and PTE are reviewed.

An objective score to identify psychogenic seizures based on age of onset and history

OBJECTIVE

Psychogenic nonepileptic seizure (PNES) is a common diagnosis after evaluation of medication resistant or atypical seizures with video-electroencephalographic monitoring (VEM), but usually follows a long delay after the development of seizures, during which patients are treated for epilepsy. Therefore, more readily available diagnostic tools are needed for earlier identification of patients at risk for PNES. A tool based on patient-reported psychosocial history would be especially beneficial because it could be implemented in the outpatient clinic.

METHODS

Based on the data from 1375 patients with VEM-confirmed diagnoses, we used logistic regression to compare the frequency of specific patient-reported historical events, demographic information, age of onset, and delay from first seizure until VEM in five mutually exclusive groups of patients: epileptic seizures (ES), PNES, physiologic nonepileptic seizure-like events (PSLE), mixed PNES plus ES, and inconclusive monitoring. To determine the diagnostic utility of this information to differentiate PNES only from ES only, we used multivariate piecewise-linear logistic regression trained using retrospective data from chart review and validated based on data from 246 prospective standardized interviews.

RESULTS

The prospective area under the curve of our weighted multivariate piecewise-linear by-sex score was 73%, with the threshold that maximized overall retrospective accuracy resulting in a prospective sensitivity of 74% (95% CI: 70-79%) and prospective specificity of 71% (95% CI: 64-82%). The linear model and piecewise linear without an interaction term for sex had very similar performance statistics. In the multivariate piecewise-linear sex-split predictive model, the significant factors positively associated with ES were history of febrile seizures, current employment or active student status, history of traumatic brain injury (TBI), and longer delay from first seizure until VEM. The significant factors associated with PNES were female sex, older age of onset, mild TBI, and significant stressful events with sexual abuse, in particular, increasing the likelihood of PNES. Delays longer than 20years, age of onset after 31years for men, and age of onset after 40years for women had no additional effect on the likelihood of PNES.

DISCUSSION

Our promising results suggest that an objective score has the potential to serve as an early outpatient screening tool to identify patients with greater likelihood of PNES when considered in combination with other factors. In addition, our analysis suggests that sexual abuse, more than other psychological stressors including physical abuse, is more associated with PNES. There was a trend of increasing frequency of PNES for women during childbearing years and plateauing outside those years that was not observed in men.

Post-traumatic epilepsy associations with mental health outcomes in the first two years after moderate to severe TBI: A TBI Model Systems analysis

PURPOSE

Research suggests that there are reciprocal relationships between mental health (MH) disorders and epilepsy risk. However, MH relationships to post-traumatic epilepsy (PTE) have not been explored. Thus, the objective of this study was to assess associations between PTE and frequency of depression and/or anxiety in a cohort of individuals with moderate-to-severe TBI who received acute inpatient rehabilitation.

METHODS

Multivariate regression models were developed using a recent (2010-2012) cohort (n=867 unique participants) from the TBI Model Systems (TBIMS) National Database, a time frame during which self-reported seizures, depression [Patient Health Questionnaire (PHQ)-9], and anxiety [Generalized Anxiety Disorder (GAD-7)] follow-up measures were concurrently collected at year-1 and year-2 after injury.

RESULTS

PTE did not significantly contribute to depression status in either the year-1 or year-2 cohort, nor did it contribute significantly to anxiety status in the year-1 cohort, after controlling for other known depression and anxiety predictors. However, those with PTE in year-2 had 3.34 times the odds (p=.002) of having clinically significant anxiety, even after accounting for other relevant predictors. In this model, participants who self-identified as Black were also more likely to report clinical symptoms of anxiety than those who identified as White. PTE was the only significant predictor of comorbid depression and anxiety at year-2 (Odds Ratio 2.71; p=0.049).

CONCLUSIONS

Our data suggest that PTE is associated with MH outcomes 2years after TBI, findings whose significance may reflect reciprocal, biological, psychological, and/or experiential factors contributing to and resulting from both PTE and MH status post-TBI. Future work should consider temporal and reciprocal relationships between PTE and MH as well as if/how treatment of each condition influences biosusceptibility to the other condition.

Incidence and risk factors of posttraumatic seizures following traumatic brain injury: A Traumatic Brain Injury Model Systems Study

OBJECTIVE

Determine incidence of posttraumatic seizure (PTS) following traumatic brain injury (TBI) among individuals with moderate-to-severe TBI requiring rehabilitation and surviving at least 5 years.

METHODS

Using the prospective TBI Model Systems National Database, we calculated PTS incidence during acute hospitalization, and at years 1, 2, and 5 postinjury in a continuously followed cohort enrolled from 1989 to 2000 (n = 795). Incidence rates were stratified by risk factors, and adjusted relative risk (RR) was calculated. Late PTS associations with immediate (<24 h), early (24 h-7 day), or late seizures (>7 day) versus no seizure prior to discharge from acute hospitalization was also examined.

RESULTS

PTS incidence during acute hospitalization was highest immediately (<24 h) post-TBI (8.9%). New onset PTS incidence was greatest between discharge from inpatient rehabilitation and year 1 (9.2%). Late PTS cumulative incidence from injury to year 1 was 11.9%, and reached 20.5% by year 5. Immediate/early PTS RR (2.04) was increased for those undergoing surgical evacuation procedures. Late PTS RR was significantly greater for individuals who self-identified as a race other than black/white (year 1 RR = 2.22), and for black individuals (year 5 RR = 3.02) versus white individuals. Late PTS was greater for individuals with subarachnoid hemorrhage (year 1 RR = 2.06) and individuals age 23-32 (year 5 RR = 2.43) and 33-44 (year 5 RR = 3.02). Late PTS RR years 1 and 5 was significantly higher for those undergoing surgical evacuation procedures (RR: 3.05 and 2.72, respectively).

SIGNIFICANCE

In this prospective, longitudinal, observational study, PTS incidence was similar to that in studies published previously. Individuals with immediate/late seizures during acute hospitalization have increased late PTS risk. Race, intracranial pathologies, and neurosurgical procedures also influenced PTS RR. Further studies are needed to examine the impact of seizure prophylaxis in high-risk subgroups and to delineate contributors to race/age associations on long-term seizure outcomes.