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Purpose: The 2017 epilepsy and seizure diagnosis framework emphasizes epilepsy syndromes and the etiology-based approach. We developed a propositional artificial intelligence (AI) system based on the above concepts to support physicians in the diagnosis of epilepsy., Methods: We analyzed and built ontology knowledge for the classification of seizure patterns, epilepsy, epilepsy syndrome, and etiologies. Protégé ontology tool was applied in this study. In order to enable the system to be close to the inferential thinking of clinical experts, we classified and constructed knowledge of other epilepsy-related knowledge, including comorbidities, epilepsy imitators, epilepsy descriptors, characteristic electroencephalography (EEG) findings, treatments, etc. We used the Ontology Web Language with Description Logic (OWL-DL) and Semantic Web Rule Language (SWRL) to design rules for expressing the relationship between these ontologies., Results: Dravet syndrome was taken as an illustration for epilepsy syndromes implementation. We designed an interface for the physician to enter the various characteristics of the patients. Clinical data of an 18-year-old boy with epilepsy was applied to the AI system. Through SWRL and reasoning engine Drool's execution, we successfully demonstrate the process of differential diagnosis., Conclusion: We developed a propositional AI system by using the OWL-DL/SWRL approach to deal with the complexity of current epilepsy diagnosis. The experience of this system, centered on the clinical epilepsy syndromes, paves a path to construct an AI system for further complicated epilepsy diagnosis., Competing Interests: Declaration of competing interest The author has no conflicts of interest., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Purpose: The aim of this study was to evaluate the prevalence of prescription and use of antiepileptic drugs (AEDs) for the treatment of epilepsy and other indications in a nationwide population using a prescription database., Materials and Methods: AED prescription data were collected from the National Health Insurance Research Database (NHIRD) in Taiwan for a 5-year period (2003-2007). Patients prescribed AEDs at least two times from 2003 to 2007 were selected for the study from a random sample that included approximately 600,000 people., Results: The prevalence of AED use (per 1000 inhabitants) increased from 12.6 in 2003 to 13.8 in 2007. The prevalence of newer AED use increased progressively from 1.0 in 2003 to 3.8 in 2007, but the prevalence of older AED use decreased during this time (11.6-10). Carbamazepine and valproic acid were the most common AEDs used. Among the newer generation of AEDs, gabapentin was the most frequently used. Newer AEDs were used primarily to treat pain disorders. The primary class of drugs used to treat epileptic disorders was older AEDs., Conclusion: An increase in the use of AEDs was observed over a 5-year period in data collected from NHIRD. This might implicate the use of newer compounds at clinical practice not only increased in the treatment of epilepsy, but also in the conditions other than epilepsy especially pain disorders., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Objective: The objective of this study was to analyze and evaluate antiepileptic drug (AED) utilization among adults in Taiwan., Methods: A random sample of 167,377 patients from the National Health Insurance (NHI) reference database was used. Prescription records were retrieved for all patients prescribed AEDs during 2004. The prescribed daily dose/defined daily dose (PDD/DDD) ratio was used to assess the adequacy of AED dosing., Results: Seventy-one percent (n=518) of patients used only one AED, while 29% (n=212) used more than two AEDs in 2004. For monotherapy, the most frequent regimens included carbamazepine (41.9%), followed by phenytoin (27.3%) and valproic acid (17.8%). For polytherapy, the most commonly used combination was valproic acid and carbamazepine. For adults, the mean PDD/DDD ratio for each AED used for either monotherapy or polytherapy was less than 1.00. Additionally, adult patients treated with more than one AED during 2004 in Taiwan took each drug in higher dose than patients using the same AED in monotherapy., Conclusion: In Taiwan antiepileptic drug therapies appear to be still dominated by the first generation drugs. The mean dosages of most antiepileptic drugs were lower than that of WHO suggested.

Objective: To determine the prevalence of treated epilepsy in the Taiwan in 2004 using prescription data from the National Health Insurance (NHI) research database and to compare this rate with estimates from other prevalence studies., Methods: A cohort was extracted from a group of antiepileptic drug (AED) users who met two inclusion criteria: (1) use of AED more than once and International Classification of Disease (ICD) codes indicating epilepsy or (2) use of AEDs except clonazepam for more than 90 days without ICD codes of epilepsy., Results: In total, 559 AED users were included. The estimated crude prevalence of AED use was 0.42% of the adult population (0.4% for women and 0.45% for men), and 72% of the cohort (n=400) used only one AED., Conclusion: Our estimate of prevalence of treated epilepsy through the NHI system has much larger coverage of population with more credible registration system, and appears to be closer to the truth than two previous small-scaled community-based studies in Taiwan.

Background Studies investigating reasons for the admission and the associated lengths of stay (LOSs) among cerebral palsy (CP) patients are limited. This study determined common reasons for acute hospitalizations and the LOSs among children, adolescents, and young adults with CP. Methods We performed a secondary analysis of data. CP patients aged 4–32.9 years were identified by CP registry in the catastrophic illness patient registry of the 2010 Taiwan National Health Insurance Research Database. Data of admission claims from 2010 to 2011 were analyzed. Reasons for admissions were identified according to International Classification of Diseases codes. Common reasons, frequencies of admissions for each reason, and LOSs were reported. Results Pneumonia, other respiratory problems, and epilepsy were the top three reasons for admissions in all groups. Other common reasons in all groups were sepsis, other respiratory infections, and gastrointestinal problems. The reasons specific to children included orthopedic issues; ear, nose, and throat problems; and urinary tract infections (UTIs). In youths, scoliosis, and contractures, were unique reasons. In young adults, UTIs, blood problems, and mental illness, were special reasons. Most admission reasons appeared to prolong LOS, and the LOS exhibited an increasing trend as age increased. Conclusion The results implied that patients with CP are more susceptible to most disease invasions. Our results also suggest that the current care system in Taiwan is unsuitable for patients with CP. These results can be used as guidance for planning effective multidisciplinary assessments in the future. [ABSTRACT FROM AUTHOR]

The objective of the study was to explore the influences of seasonality, meteorological conditions, and air pollution exposure on the number of patients who visit the hospital due to seizures. Outpatient and inpatient data from the National Health Insurance Database of Taiwan from 2009 to 2013, meteorological data from the Meteorological Bureau, and air pollution exposure data from the Taiwan Air Quality Monitoring Stations were collected and integrated into daily time series data. The following data processing and analysis results are based on the mean of the 7 days' lag data of the 18 meteorological condition/air pollution exploratory factors to identify the critical meteorological conditions and air pollution exposure factors by executing univariate analysis. The average hospital visits for seizure per day by month were used as an index of observation. The effect of seasonality has also been examined. The average visits per day by month had a significant association with 10 variables. Overall, the number of visits due to these factors has been estimated to be 71.529 (13.7%). The most obvious factors affecting the estimated number of visits include ambient temperature, CH 4 , and NO. Six air pollutants, namely CH 4 , NO, CO, NO 2 , PM2.5, and NMHC had a significantly positive correlation with hospital visits due to seizures. Moreover, the average daily number of hospital visits was significantly high in January and February (winter season in Taiwan) than in other months (R2 = 0.422). The prediction model obtained in this study indicates the necessity of rigorous monitoring and early warning of these air pollutants and climate changes by governments. Additionally, the study provided a firm basis for establishing prediction models to be used by other countries or for other diseases. • AMB_TEMP and UBV had decrease risk on hospital-visits for seizures. • PS01, RAINFALL, CH 4 , NO, CO, NO 2 , PM2.5, and NMHC had increase risk. • The overall impact of these factors on the average visits per day by month was 13.7%. • The number of visits in January and February was significantly higher than in other months. [ABSTRACT FROM AUTHOR]