Prophylactic Antiepileptics and Seizure Incidence Following Subarachnoid Hemorrhage

Panczykowski, David M.; Pease, Matthew; Yin, Zhinan; Weiner, Gregory M.; Ares, William J.; Crago, Elizabeth; Jankowitz, Brian; Ducruet, Andrew F.

doi:10.1161/strokeaha.116.013766

Cited by 40 publications

(31 citation statements)

References 26 publications

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“…These factors affect both electrophysiology and the likelihood of seizures. Previous prospective studies have found mixed results regarding the efficacy of antiseizure drug(ASD) prophylaxi . The mixed results of these studies suggest that ASD prophylaxis likely has a modest, if any, effect on both the suppression of cortical irritability and seizure risk.…”

Section: Discussionmentioning

confidence: 99%

Comparison of machine learning models for seizure prediction in hospitalized patients

Struck

Rodriguez‐Ruiz

Osman

et al. 2019

Ann Clin Transl Neurol

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Objective To compare machine learning methods for predicting inpatient seizures risk and determine the feasibility of 1‐h screening EEG to identify low‐risk patients (<5% seizures risk in 48 h). Methods The Critical Care EEG Monitoring Research Consortium (CCEMRC) multicenter database contains 7716 continuous EEGs (cEEG). Neural networks (NN), elastic net logistic regression (EN), and sparse linear integer model (RiskSLIM) were trained to predict seizures. RiskSLIM was used previously to generate 2HELPS2B model of seizure predictions. Data were divided into training (60% for model fitting) and evaluation (40% for model evaluation) cohorts. Performance was measured using area under the receiver operating curve (AUC), mean risk calibration (CAL), and negative predictive value (NPV). A secondary analysis was performed using Monte Carlo simulation (MCS) to normalize all EEG recordings to 48 h and use only the first hour of EEG as a “screening EEG” to generate predictions. Results RiskSLIM recreated the 2HELPS2B model. All models had comparable AUC: evaluation cohort (NN: 0.85, EN: 0.84, 2HELPS2B: 0.83) and MCS (NN: 0.82, EN; 0.82, 2HELPS2B: 0.81) and NPV (absence of seizures in the group that the models predicted to be low risk): evaluation cohort (NN: 97%, EN: 97%, 2HELPS2B: 97%) and MCS (NN: 97%, EN: 99%, 2HELPS2B: 97%). 2HELPS2B model was able to identify the largest proportion of low‐risk patients. Interpretation For seizure risk stratification of hospitalized patients, the RiskSLIM generated 2HELPS2B model compares favorably to the complex NN and EN generated models. 2HELPS2B is able to accurately and quickly identify low‐risk patients with only a 1‐h screening EEG.

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Section: Discussionmentioning

confidence: 99%

Comparison of machine learning models for seizure prediction in hospitalized patients

Struck

Rodriguez‐Ruiz

Osman

et al. 2019

Ann Clin Transl Neurol

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“…Diagnosis will require a high index of suspicion and performance of an EEG. Routine seizure prophylaxis with AEDs remains controversial as there is a lack of demonstrable benefit [16] [17].…”

Section: Discussionmentioning

confidence: 99%

Extended Antiepileptic Drug Prophylaxis and Late Onset Seizures in Aneurysmal Subarachnoid Hemorrhage

Low¹,

Goh²,

Teo³

2019

OJMN

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Background: The indication and optimal duration of antiepileptic drug (AED) prophylaxis after aneurysmal subarachnoid hemorrhage (SAH) remains controversial. Our institution practices routine seizure prophylaxis for variable durations at the discretion of the neurosurgeon and neuro-intensivist. Given the propensity of late onset seizures to progress to chronic epilepsy, we sought to investigate the efficacy of extended AED prophylaxis in reducing the risk of late seizures. Methods: This retrospective study analyzed 36 patients who were admitted to our neurosurgical intensive care unit (NICU) over a 2-year period (1st November 2015 to 31st October 2017). All hospital admissions records, electronic medication records as well as outpatient visits up to 1 year were reviewed. Late onset seizures were defined as seizures occurring more than 7 days post-intervention (or presentation if no intervention was performed) up to 1 year of follow-up. Results: Majority of the patients received Levetiracetam (94%) as seizure prophylaxis and late onset seizures occurred in 6 (17%) of the patients. Those patients who received a greater proportion of in-patient stay with AED prophylaxis had a statistically significant lower risk of developing late seizures (OR = 0.964, 95%, p = 0.02). Although the value tended towards benefit (OR = 0.382) for AED > 21 days in-hospital, the result was not statistically significant (p = 0.307). Conclusion: An extended duration of AED prophylaxis, in particular Levetiracetam, may confer some benefit in reducing risk of developing late seizures. However, the optimal duration of therapy is yet to be determined and further large multi-centered randomized studies are necessary.

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“…Despite recent efforts to introduce a guideline for seizure prophylaxis in SAH patients, a consensus regarding a uniform protocol for all of these patients has not been achieved. Several authors have questioned the benefits of seizure prophylaxis for all patients and many others believe that they can only prevent late seizures in patients with certain risk factors (3,25). Different seizure prophylaxis regimens are used in neuro-vascular units, primarily based on experience with certain medication and the dosage and duration of prophylaxis are determined according to patients' drug history, past medical history of central nervous system lesions, the occurrence of seizures, drug interactions, and side effect profile.…”

Section: Discussionmentioning

confidence: 99%

Long-Versus Short-Term Seizure Prophylaxis After Craniotomy for Clipping in Aneurysmal Subarachnoid Hemorrhage; A Retrospective Cohort Study

et al. 2019

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Background: Seizures are quite common following subarachnoid hemorrhage (SAH) and due to increased mortality and morbidity in this setting, thus seizure prophylaxis is introduced as a common neurosurgical practice. Investigations are still ongoing to figure out the most efficient seizure prophylaxis guideline. Objectives: To compare the efficacy of two seizures prophylaxis protocols that have been practiced in a tertiary neurovascular center in Southern Iran through a retrospective cohort analysis Methods: A total of 426 patients who were operated due to aneurysmal SAH between September 2007 and March 2016 were included in this retrospective cohort study. From September 2007 to March 2011 the common practice was prophylaxis with phenytoin for 3 -6 months, which was switched to a shorter 1-month course since March 2011. Seizure control was evaluated in telephoned patients and outpatient records. Results: Out of 426 subjects eligible for this study, 165 (38.7%) took the 1-month (short-term) regimen and 261 (61.3%) took the 3 -6 months (long-term) regimen. Results revealed that achievement of seizure control was similar for both groups in those without perioperative seizures (P = 0.4); however, with perioperative seizures, the short-term protocol had inferior results for seizure control and higher odds (almost 109-fold) for developing post-operative seizures. Conclusions: Although short-term 1-month seizure prophylaxis with phenytoin provides adequate seizure control for most individuals after SAH, perioperative seizures necessitates a longer course of 3 -6 month seizure prophylaxis.

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Prophylactic Antiepileptics and Seizure Incidence Following Subarachnoid Hemorrhage

Cited by 40 publications

References 26 publications

Comparison of machine learning models for seizure prediction in hospitalized patients

Comparison of machine learning models for seizure prediction in hospitalized patients

Extended Antiepileptic Drug Prophylaxis and Late Onset Seizures in Aneurysmal Subarachnoid Hemorrhage

Long-Versus Short-Term Seizure Prophylaxis After Craniotomy for Clipping in Aneurysmal Subarachnoid Hemorrhage; A Retrospective Cohort Study

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