Automated identification and quality measurement for pediatric convulsive status epilepticus.

OBJECTIVE: Treatment delays for refractory convulsive status epilepticus (RCSE) are associated with worse outcomes. In the United States, treatment for pediatric RCSE is slower than guidelines recommend. To address this gap, the American Academy of Neurology and Child Neurology Society (AAN/CNS) developed a quality measure: the percentage of RCSE patients that receive third-line treatment within 60 minutes. We aimed to develop computable phenotypes for convulsive status epilepticus (CSE) and RCSE to automate calculation of the quality measure. METHODS: From an observational cohort of children presenting to the emergency department for seizures or epilepsy, we identified presentations of RCSE and its precursors: CSE and benzodiazepine-resistant status epilepticus (BRSE). These served as a gold standard for computable phenotype development. Using multivariate analyses, we constructed and evaluated statistical models for case identification. We then evaluated adherence to the AAN/CNS RCSE quality measure. RESULTS: From 664 charts, we identified 56 patients with CSE, 36 with BRSE, and 18 with RCSE. Four predictors were used: International Classification of Diseases (ICD) codes, and receiving first-, second-, or third-line agents shortly after presentation to the emergency department (ED). Combinations of these predictors identified CSE with 84% sensitivity and 81% positive predictive value (PPV), BRSE with 67% sensitivity and 89% PPV, and RCSE with 94% sensitivity and 85% PPV. Median (interquartile range [IQR]) time to treatment for first-line agent was 13 (5-27) minutes for CSE, second-line for BRSE was 24 (9.5-43.5) minutes, and third-line for RCSE was 52 (27-87) minutes. Sixty percent of RCSE patients received a third-line agent within 60 minutes of ED arrival. SIGNIFICANCE: RCSE and its precursors can be identified automatically with high fidelity allowing automated calculation of time to treatment and the RCSE quality measure. This has the potential to facilitate quality improvement work and improve care for RCSE.

Astrocyte-specific regulation of hMeCP2 expression in Drosophila.

Alterations in the expression of Methyl-CpG-binding protein 2 (MeCP2) either by mutations or gene duplication leads to a wide spectrum of neurodevelopmental disorders including Rett Syndrome and MeCP2 duplication disorder. Common features of Rett Syndrome (RTT), MeCP2 duplication disorder, and neuropsychiatric disorders indicate that even moderate changes in MeCP2 protein levels result in functional and structural cell abnormalities. In this study, we investigated two areas of MeCP2 pathophysiology using Drosophila as a model system: the effects of MeCP2 glial gain-of-function activity on circuits controlling sleep behavior, and the cell-type specific regulation of MeCP2 expression. In this study, we first examined the effects of elevated MeCP2 levels on microcircuits by expressing human MeCP2 (hMeCP2) in astrocytes and distinct subsets of amine neurons including dopamine and octopamine (OA) neurons. Depending on the cell-type, hMeCP2 expression reduced sleep levels, altered daytime/nighttime sleep patterns, and generated sleep maintenance deficits. Second, we identified a 498 base pair region of the MeCP2e2 isoform that is targeted for regulation in distinct subsets of astrocytes. Levels of the full-length hMeCP2e2 and mutant RTT R106W protein decreased in astrocytes in a temporally and spatially regulated manner. In contrast, expression of the deletion Δ166 hMeCP2 protein was not altered in the entire astrocyte population. qPCR experiments revealed a reduction in full-length hMeCP2e2 transcript levels suggesting transgenic hMeCP2 expression is regulated at the transcriptional level. Given the phenotypic complexities that are caused by alterations in MeCP2 levels, our results provide insight into distinct cellular mechanisms that control MeCP2 expression and link microcircuit abnormalities with defined behavioral deficits.