Comparing the efficacy of anti-seizure medications using matched cohorts on a large insurance claims database.

Epilepsy is a severe chronic neurological disease affecting 60 million people worldwide. Primary treatment is with anti-seizure medicines (ASMs), but many patients continue to experience seizures. We used retrospective insurance claims data on 280,587 patients with uncontrolled epilepsy (UE), defined as status epilepticus, need for a rescue medicine, or admission or emergency visit for an epilepsy code. We conducted a computational risk ratio analysis between pairs of ASMs using a causal inference method, in order to match 1034 clinical factors and simulate randomization. Data was extracted from the MarketScan insurance claims Research Database records from 2011 to 2015. The cohort consisted of individuals over 18 years old with a diagnosis of epilepsy who took one of eight ASMs and had more than a year of history prior to the filling of the drug prescription. Seven ASM exposures were analyzed: topiramate, phenytoin, levetiracetam, gabapentin, lamotrigine, valproate, and carbamazepine or oxcarbazepine (treated as the same exposure). We calculated the risk ratio of UE between pairs of ASM after controlling for bias with inverse propensity weighting applied to 1034 factors, such as demographics, confounding illnesses, non-epileptic conditions treated by ASMs, etc. All ASMs exhibited a significant reduction in the prevalence of UE, but three drugs showed pair-wise differences compared to other ASMs. Topiramate consistently was associated with a lower risk of UE, with a mean risk ratio range of 0.68-0.93 (average 0.82, CI: 0.56-1.08). Phenytoin and levetiracetam were consistently associated with a higher risk of UE with mean risk ratio ranges of 1.11 to 1.47 (average 1.13, CI 0.98-1.65) and 1.15 to 1.43 (average 1.2, CI 0.72-1.69), respectively. Large-scale retrospective insurance claims data - combined with causal inference analysis - provides an opportunity to compare the effect of treatments in real-world data in populations 1,000-fold larger than those in typical randomized trials. Our causal analysis identified the clinically unexpected finding of topiramate as being associated with a lower risk of UE; and phenytoin and levetiracetam as associated with a higher risk of UE (compared to other studied drugs, not to baseline). However, we note that our data set for this study only used insurance claims events, which does not comprise actual seizure frequencies, nor a clear picture of side effects. Our results do not advocate for any change in practice but demonstrate that conclusions from large databases may differ from and supplement those of randomized trials and clinical practice and therefore may guide further investigation.

Smartphone-based audiometric test for screening hearing loss in the elderly.

Hearing loss is widespread among the elderly. One of the main obstacles to rehabilitation is identifying individuals with potentially correctable hearing loss. Smartphone-based hearing tests can be administered at home, thus greatly facilitating access to screening. This study evaluates the use of a smartphone application as a screening tool for hearing loss in individuals aged ≥ 65 years. Twenty-six subjects aged 84.4 ± 6.73 years (mean ± SD) were recruited. Pure-tone audiometry was administered by both a smartphone application (uHear for iPhone, v1.0 Unitron, Canada) and a standard portable audiometer by trained personnel. Participants also completed a questionnaire on their hearing. Pure-tone thresholds were compared between the two testing modalities and correlated with the questionnaire results. The cutoff point for failing screening tests was a pure tone average of 40 dB for the frequencies 250-6,000 Hz. The smartphone application's pure tone thresholds were higher (poorer hearing) than the audiometric thresholds, with a significant difference in all frequencies but 2,000 Hz. The application and the audiometric values were in agreement for 24 subjects (92 %). The application had a sensitivity of 100 % and specificity of 60 % for screening compared with the audiometer. The questionnaire was significantly less accurate, having assigned a passing score to three participants who failed both the application and audiometric tests. While a smartphone application may not be able to accurately determine the level of hearing impairment, it is useful as a highly accessible portable audiometer substitute for screening for hearing loss in elderly populations.