BackgroundThe U.S. Food and Drug Administration (FDA) recently linked antiepileptic drug (AED) exposure to suicide-related behaviors based on meta-analysis of randomized clinical trials. We examined the relationship between suicide-related behaviors and different AEDs in older veterans receiving new AED monotherapy from the Veterans Health Administration (VA), controlling for potential confounders.MethodsVA and Medicare databases were used to identify veterans 66 years and older, who received a) care from the VA between 1999 and 2004, and b) an incident AED (monotherapy) prescription. Previously validated ICD-9-CM codes were used to identify suicidal ideation or behavior (suicide-related behaviors cases), epilepsy, and other conditions previously associated with suicide-related behaviors. Each case was matched to controls based on prior history of suicide-related behaviors, year of AED prescription, and epilepsy status.ResultsThe strongest predictor of suicide-related behaviors (N = 64; Controls N = 768) based on conditional logistic regression analysis was affective disorder (depression, anxiety, or post-traumatic stress disorder (PTSD); Odds Ratio 4.42, 95% CI 2.30 to 8.49) diagnosed before AED treatment. Increased suicide-related behaviors were not associated with individual AEDs, including the most commonly prescribed AED in the US - phenytoin.ConclusionOur extensive diagnostic and treatment data demonstrated that the strongest predictor of suicide-related behaviors for older patients newly treated with AED monotherapy was a previous diagnosis of affective disorder. Additional, research using a larger sample is needed to clearly determine the risk of suicide-related behaviors among less commonly used AEDs.

SUMMARYPurpose: There is a growing movement to assess the quality of care provided to patients in the US, but few studies have examined initial care for epilepsy patients. We examined the relationships among patient race, setting of initial diagnosis, and initial treatment for older veterans newly diagnosed with epilepsy. Methods: We used Department of Veterans Affairs (VA) inpatient, outpatient, pharmacy and Medicare data (1999)(2000)(2001)(2002)(2003)(2004) to identify patients 66 years and older with new-onset epilepsy. High quality care was defined as avoiding a suboptimal agent (phenytoin, phenobarbital, primidone) as defined by experts. Predictors included demographic and clinical characteristics, and the context of the initial seizure diagnosis including the setting (e.g. emergency, neurology, hospital, primary care). We used mixed-effects multivariable logistic regression modeling to identify predictors of initial seizure diagnosis in a neurology setting, and receipt of a suboptimal AED. Results: Of 9,682 patients, 27% were initially diagnosed in neurology and 70% received a suboptimal AED. Blacks and Hispanics were less likely to be diagnosed in neurology clinics (black OR = 0.7 95% CI 0.6-0.8; Hispanic OR = 0.6 95% CI 0.5-0.9). Diagnosis in a non-neurology setting increased the likelihood of receiving a suboptimal agent (e.g. Emergency Department OR = 2.3 95% CI 2.0-2.7). After controlling for neurology diagnosis, black race was independently associated with an increased risk of receiving a suboptimal agent. Discussion: We demonstrated that differences in quality of care exist for both clinical setting of initial diagnosis and race. We discussed possible causes and implications of these findings.

Objectives Identify clinically-meaningful potential drug-drug interactions with antiepileptic drugs (AED-PDI), the AEDs and co-administered drugs commonly associated with AED-PDI, and characteristics of patients with increased likelihood of AED-PDI exposure. Design Five-year retrospective cohort study of veterans with new-onset epilepsy. Setting National VA and Medicare databases. Participants Veterans age 66 years and older with a new diagnosis of epilepsy between October 1, 1999-September 30, 2004 (N=9,682). Measurements We restricted AED-PDI to clinically-meaningful potential drug interactions identified by prior literature review. AED-PDI were identified using participants' date of initial AED prescription and overlapping concomitant medications. Logistic regression analysis identified factors associated with AED-PDI including demographic characteristics, chronic disease states and diagnostic setting. Results AED-PDI exposure was found in 45.5% (4,406/9,682); phenytoin, a drug with many potential drug interactions, was the most commonly prescribed AED. Cardiovascular drugs, lipid-lowering medications and psychotropic agents were the most commonly co-administered AED-PDI medications. Individuals at higher likelihood of AED-PDI exposure had 1) hypertension (OR=1.46, 99% CI 1.24-1.82), 2) hypercholesterolemia (OR=1.40, 99% CI 1.24-1.57) and 3) were diagnosed in emergency or primary care vs. Neurology settings (emergency OR: 1.30 99% CI=1.08-1.58; primary care OR: 1.29 99% CI 1.12-1.49). Conclusion Exposure to AED-PDI was substantial, but less common in epilepsy patients diagnosed in a neurology setting. Because potential outcomes associated with AED-PDI include stroke and myocardial infarction in a population already at elevated risk, clinicians should closely monitor blood pressure, coagulation, and lipid measures to minimize adverse effects of AED-PDI. Interventions to reduce AED-PDI may improve patient outcomes.