BACKGROUND: Levetiracetam (LEV) and valproic acid (VPA) are two anti-epileptic drugs (AEDs) routinely used for post-traumatic seizure (PTS) prophylaxis at our institution. In our practice, VPA is used for its beneficial effects on behavioral agitation and headaches, but it is also associated with abnormal liver function tests (LFTs). Both medications may be associated with thrombocytopenia. There is less literature comparing the adverse effect profiles and discontinuation rates of LEV and VPA in the context of PTS prophylaxis. We conducted a quality improvement (QI) analysis to determine the safety of LEV and VPA for traumatic brain injury (TBI) patients at our institution. In particular, our QI analysis involved calculating the rates of discontinuation or change of drug regimen due to the adverse effects.
METHODS: Our QI analysis focused on patients treated for TBI at our institution during a six-year period. We recorded the AED used and if the AED was discontinued or switched due to thrombocytopenia, behavioral agitation, headaches, or elevated LFTs (including elevated aspartate aminotransferase or alanine aminotransferase values). We also recorded the incidence of early PTS, defined as seizures within seven days of the TBI.
RESULTS: Our QI analysis included patients with a mean age of approximately 49 years with nearly 75% males. The mean Glasgow Coma Scale (GCS) score was 12.88, with 73.11% of patients having a mild GCS. The three leading injury mechanisms were fall, assault, and motor vehicle collision. The three leading types of TBI were traumatic subarachnoid hemorrhage, subdural hematoma, and cerebral contusion. Among patients with no prior history of seizures, we found an early PTS incidence of 7.28%. For patients administered LEV and VPA, 0.11% (1/898) and 3.85% (4/104) had the medication discontinued or changed because of thrombocytopenia (p < 0.001), respectively. For patients on LEV, 4.01% (36/898) and 1.78% (16/898) had the medication discontinued or changed because of behavioral agitation and headaches, respectively. For patients on VPA, 2.88% (3/104) had the medication discontinued or changed because of hepatotoxicity. In total, 5.90% versus 6.73% (p > 0.5) of patients on LEV and VPA, respectively, had their medication regimens changed due to the adverse effects.
CONCLUSIONS: The incidence of early PTS in our patients is within the range of what has been reported in the literature. The rate of discontinuation of LEV and VPA on account of adverse events is low in the context of PTS prophylaxis. Both medications had similar overall rates of discontinuation. VPA was discontinued more frequently than LEV due to thrombocytopenia, but discontinuation was not common in either case. LEV is associated with behavioral agitation and headaches, which makes VPA a desirable alternative for patients suffering from these symptoms.

BACKGROUND: This study aimed to re-establish a Population Pharmacokinetic (PPK) model of oral phenytoin to further optimize the individualized medication regimen based on our previous research.
METHODS: Patients with intracranial malignant tumor requiring craniotomy were prospectively enrolled according to the inclusion criteria. Genotypes of CYP2C9*1 or *3 and CYP2C19*1, *2 or *3 were determined by real time PCR (TaqMan probe) method. Serum concentrations of phenytoin on the 4th and 7th day after oral administration were determined using fluorescence polarization immunoassay. The PPK parameters were estimated using Nonlinear Mixed Effects Models (NONMEM) and internal validation was performed using bootstraps. The predictive performance of the final model was evaluated by Normalized Predictive Distribution Errors (NPDEs) and diagnostic goodness- of-fit plots.
RESULTS: A total of 390 serum samples were collected from 170 patients in PPK model building group. The population typical values for Vm, Km and the apparent volume of distribution (V) in the final model were 17.5 mg/h, 6.41 mg/L and 54.8 L, respectively. Internal validation by bootstraps showed that the final model was stable and reliable. NPDEs with a normal distribution and a scatterplot with symmetrical distribution showed that the final model had good predictive capability. Individualized dose regimens of additional 40 patients in the external validation group were designed by the present final PPK model. The percentages of patients with serum concentrations within the therapeutic range were 61.53% (24/39) on the 4th day and 94.87% (37/39) on the 7th day, which were higher than the 39.33% (59/150) and 52.10% (87/167) of above 170 patients (P < 0.0001).
CONCLUSIONS: The present PPK final model for oral phenytoin may be used to further optimize phenytoin individualized dose regimen to prevent early seizure in patients after brain injury if patient characteristics meet those of the population studied.

Traumatic brain injury (TBI) is the leading cause of death and disability in children, and can lead to long lasting functional impairment. Many factors influence outcome, but imaging studies examining effects of individual variables are limited by sample size. Roughly 20-40% of hospitalized TBI patients experience seizures, but not all of these patients go on to develop a recurrent seizure disorder. Here we examined differences in structural network connectivity in pediatric patients who had sustained a moderate-severe TBI (msTBI). We compared those who experienced early post-traumatic seizures to those who did not; we found network differences months after seizure activity stopped. We also examined correlations between network measures and a common measure of injury severity, the Glasgow Coma Scale (GCS). The global GCS score did not have a detectable relationship to brain integrity, but sub-scores of the GCS (eyes, motor, verbal) were more closely related to imaging measures.