18 research outputs found
SAMS - A Systems Architecture for Developing Intelligent Health Information Systems
WOS: 000327459800013PubMed ID: 2419735
Latency of epileptic and psychogenic nonepileptic seizures
Background Due to their semiological similarities, psychogenic nonepileptic seizures (PNESs) can occasionally hardly be differentiated from epileptic seizures (ESs), and long-term video-electroencephalographic monitoring (VEM) is needed for the differential diagnosis
Factors affecting long-term prognosis in adult patients with psychogenic non-epileptic seizures
Background and purpose – Among epileptic patients who are monitored using the video-electroencephalography monitoring
(VEM) technique, in some patients a psychogenic non-epileptic seizure (PNES) can be identified as a definitive diagnosis. The longterm prognosis of these patients is not well known. In this study, we aimed to determine
the factors that affect the prognosis of PNES. Methods – Forty-one PNES patients diagnosed using VEM between 2012 and 2022 were questioned about their PNES frequencies in the last 12 months. According to their semiological characteristics, PNES types were divided into motor and non-motor seizures. The effects of clinical characteristics (e.g. age, gender, marital status, education level and
PNES type) on the prognoses were identified. Results – Twenty-one PNES patients (51.2%) had long-term seizure freedom after VEM. Thirteen of them (31.7%) entered the
seizure-free period immediately after VEM, and the other eight (19.5%) continued suffering from PNES for several years and became seizure free in the last 12 months. In the
poor-prognosis group, female cases showed worse prognoses than male cases. The prognoses of motor and non-motor PNES types did not show significant differences. Conclusion – This study showed that 51.2% of the PNES patients examined had long-term seizure freedom and that female patients had worse prognoses than male patients
Variability of Quality of Life at Small Scales: Addis Ababa, Kirkos Sub-City
Quality of life, Quality of life variability, GIS, Kirkos sub-city, Addis Ababa,