Could the 2017 ILAE and the four-dimensional epilepsy classifications be merged to a new "Integrated Epilepsy Classification"?

Over the last few decades the ILAE classifications for seizures and epilepsies (ILAE-EC) have been updated repeatedly to reflect the substantial progress that has been made in diagnosis and understanding of the etiology of epilepsies and seizures and to correct some of the shortcomings of the terminology used by the original taxonomy from the 1980s. However, these proposals have not been universally accepted or used in routine clinical practice. During the same period, a separate classification known as the "Four-dimensional epilepsy classification" (4D-EC) was developed which includes a seizure classification based exclusively on ictal symptomatology, which has been tested and adapted over the years. The extensive arguments for and against these two classification systems made in the past have mainly focused on the shortcomings of each system, presuming that they are incompatible. As a further more detailed discussion of the differences seemed relatively unproductive, we here review and assess the concordance between these two approaches that has evolved over time, to consider whether a classification incorporating the best aspects of the two approaches is feasible. To facilitate further discussion in this direction we outline a concrete proposal showing how such a compromise could be accomplished, the "Integrated Epilepsy Classification". This consists of five categories derived to different degrees from both of the classification systems: 1) a "Headline" summarizing localization and etiology for the less specialized users, 2) "Seizure type(s)", 3) "Epilepsy type" (focal, generalized or unknown allowing to add the epilepsy syndrome if available), 4) "Etiology", and 5) "Comorbidities & patient preferences"

Histopathological Findings in Brain Tissue Obtained during Epilepsy Surgery

BACKGROUND: Detailed neuropathological information on the structural brain lesions underlying seizures is valuable for understanding drug-resistant focal epilepsy. / METHODS: We report the diagnoses made on the basis of resected brain specimens from 9523 patients who underwent epilepsy surgery for drug-resistant seizures in 36 centers from 12 European countries over 25 years. Histopathological diagnoses were determined through examination of the specimens in local hospitals (41%) or at the German Neuropathology Reference Center for Epilepsy Surgery (59%). / RESULTS: The onset of seizures occurred before 18 years of age in 75.9% of patients overall, and 72.5% of the patients underwent surgery as adults. The mean duration of epilepsy before surgical resection was 20.1 years among adults and 5.3 years among children. The temporal lobe was involved in 71.9% of operations. There were 36 histopathological diagnoses in seven major disease categories. The most common categories were hippocampal sclerosis, found in 36.4% of the patients (88.7% of cases were in adults), tumors (mainly ganglioglioma) in 23.6%, and malformations of cortical development in 19.8% (focal cortical dysplasia was the most common type, 52.7% of cases of which were in children). No histopathological diagnosis could be established for 7.7% of the patients. / CONCLUSIONS: In patients with drug-resistant focal epilepsy requiring surgery, hippocampal sclerosis was the most common histopathological diagnosis among adults, and focal cortical dysplasia was the most common diagnosis among children. Tumors were the second most common lesion in both groups. (Funded by the European Union and others.

Effect of Farm Income and Off-Farm Wage Variability on Off-Farm Labor Supply

This study models the effects of variability in farm income and off-farm wages on farm operators' labor allocation decisions. A simple theoretical model is employed to develop hypotheses, which are then tested empirically. Variability in farm income and off-farm wages is predicted to have a positive and negative effect, respectively, on off-farm hours worked. The empirical results confirm these predictions

BEYOND RISK AVERSION: ECCENTRICITY IN WEIGHTED EXPECTED UTILITY

In recent survey articles Bell and Farquhar and Machina have brought to the attention of decision scientists an alternative to the expected utility model called weighted expected utility. Developed by MacCrimmon, Chew and Fishburn, this is the simplest alternative to expected utility that permits an interpretation and rationalization of Allais' famous paradox. This paper identifies the two crucial parameters of weighted expected utility -- risk aversion and eccentricity -- by studying demand for insurance. The first of these is a measure that generalizes the Arrow-Pratt risk aversion measure of expected utility. The other, which we call a measure of eccentricity, has no counterpart in expected utility theory. Risk aversion is a concept with which decision analysts are quite comfortable, but eccentricity is simultaneously a new concept and one whose predictions are more subtle than those of risk aversion. In essence, eccentricity is a measure of how susceptible the decision maker is to Allais' paradox or how much he differs from expected utility maximization. Together risk aversion and eccentricity completely determine weighted expected utility and provide insight into the behavior of decision makers under uncertainty, behavior that can be quite different from that predicted by expected utility. Explanations are given of the impact of increases in risk aversion.and eccentricity on demand for insurance. Perhaps the most striking difference is that when the decision maker is eccentric, the standard analysis of decision trees by "averaging out and folding back" provides suboptimal decisions and the losses are magnified as the degree of eccentricity grows