Evaluation of First Seizure and Newly Diagnosed Epilepsy

Clinical prediction models for treatment outcomes in newly diagnosed epilepsy: A systematic review

Up to 35% of individuals diagnosed with epilepsy continue to have seizures despite treatment, commonly referred to as drug-resistant epilepsy. Uncontrolled seizures can directly, or indirectly, negatively impact an individual's quality of life. To inform clinical management and life decisions, it is important to be able to predict the likelihood of seizure control. Those likely to achieve seizure control will be able to return sooner to their usual work and leisure activities and require less follow-up, whereas those with a poor prognosis will need more frequent clinical attendance and earlier consideration of epilepsy surgery. This is a systematic review aimed at identifying demographic, clinical, physiological (e.g., electroencephalographic), and imaging (e.g., magnetic resonance imaging) factors that may be predictive of treatment outcomes in patients with newly diagnosed epilepsy (NDE). MEDLINE and Embase were searched for prediction models of treatment outcomes in patients with NDE. Study characteristics were extracted and subjected to assessment of risk of bias (and applicability concerns) using the PROBAST (Prediction Model Risk of Bias Assessment Tool) tool. Baseline variables associated with treatment outcomes are reported as prognostic factors. After screening, 48 models were identified in 32 studies, which generally scored low for concerns of applicability, but universally scored high for susceptibility to bias. Outcomes reported fit broadly into four categories: drug resistance, short-term treatment response, seizure remission, and mortality. Prognostic factors were also heterogenous, but the predictors that were commonly significantly associated with outcomes were those related to seizure characteristics/types, epilepsy history, and age at onset. Antiseizure medication response was often included as a baseline variable, potentially obscuring other factor relationships at baseline. Currently, outcome prediction models for NDE demonstrate a high risk of bias. Model development could be improved with a stronger adherence to recommended TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) practices. Furthermore, we outline actionable changes to common practices that are intended to improve the overall quality of prediction model development in NDE.

Accuracy of patient-reported spell duration: A comparative study

Clinicians rely heavily on patient histories to make medical diagnoses, most of which are inherently subjective and prone to inaccuracies. The aim of this study is to compare the subjective versus objective duration of spells through a retrospective chart review of patients admitted to the epilepsy monitoring unit at our tertiary care medical center. One hundred patients were analyzed. Differences in the accuracy of subjective estimations versus objective duration were compared by age, sex, focal versus generalized, location (frontal versus non-frontal), and spell type (focal aware versus impaired awareness and epileptic versus non-epileptic). Our data show that patients are poor subjective estimators, with 73% of patients overestimating the duration of their spells. We did not find differences in estimated duration by age, sex, seizure location or spell type. A notable exception was patients with generalized convulsive seizures, who accurately reported spell duration to within 17 s. This is likely because these seizures are stereotypical, and patients/family time them. Moreover, patients with non-epileptic spells were worse estimators of their spell duration than those with epileptic spells. In addition, although the prefrontal lobe plays a role in time estimation, we did not find that patients with frontal lobe seizures were worse estimators than those with non-frontal seizures, but invasive monitoring can more precisely localize seizures within areas of the frontal lobe responsible for time estimation. Our data emphasize the importance of not relying solely on patient-reported time estimation in diagnosing and developing treatment plans and instead instructing patients to time their spells.

Seizures and epilepsy associated with central nervous system tuberculosis

Central nervous system (CNS) tuberculosis is a life-threatening condition that usually presents with seizures, particularly in children and HIV-infected patients. Tuberculous meningitis (TBM) and tuberculomas are the two forms of CNS tuberculosis that can present with seizures. Seizures usually resolve after successful treatment of the underlying infection. However, the success of the treatment is usually based on an early diagnosis. Delay in the treatment of CNS tuberculosis increases the risk of its associated complications, such as stroke. This would lead to the development of epilepsy. Early seizures may be related to meningeal irritation and cerebral edema, whereas late seizures are often associated with structural brain lesions that generally require more advanced and prolonged treatment. Risk factors associated with the development of epilepsy include young age, refractory seizures, tuberculoma, cortical involvement, epileptiform discharges, and residual lesions. Treatment of CNS tuberculosis is based on early initiation of appropriate anti-tuberculous drugs, antiseizure medications, and correction of associated predisposing factors. Finally, further research into the mechanisms of seizures and the development of epilepsy in CNS tuberculosis could help improve management of these conditions.