ABSTRACT
Identification of stroke mimics and 'chameleons' among transient neurological deficits (TND) is critical. Diagnostic workup consists of a brain imaging study, for a vascular disease or a brain tumour and EEG, for epileptiform discharges. The precise role of EEG in this diagnostic workup has, however, never been clearly delineated. However, this could be crucial in cases of atypical or incomplete presentation with consequences on disease management and treatment. We analysed the EEG patterns on 95 consecutive patients referred for an EEG within 7 days of a TND with diagnostic uncertainty. Patients were classified at the discharge or the 3-month follow-up visit as: 'ischemic origin', 'migraine aura', 'focal seizure', and 'other'. All patients had a brain imaging study. EEG characteristics were correlated to the TND symptoms, imaging study, and final diagnosis. Sixty four (67%) were of acute onset. Median symptom duration was 45 min. Thirty two % were 'ischemic', 14% 'migraine aura', 19% 'focal seizure', and 36% 'other' cause. EEGs were recorded with a median delay of 1.6 day after symptoms onset. Forty EEGs (42%) were abnormal. Focal slow waves were the most common finding (43%), also in the ischemic group (43%), whether patients had a typical presentation or not. Epileptiform discharges were found in three patients, one with focal seizure and two with migraine aura. Non-specific EEG focal slowing is commonly found in TND, and may last several days. We found no difference in EEG presentation between stroke mimics and stroke chameleons, and between other diagnoses.
Subject(s)
Brain Waves/physiology , Electroencephalography/methods , Nervous System Diseases/physiopathology , Adult , Aged , Aged, 80 and over , Brain/diagnostic imaging , Brain/physiopathology , Female , Follow-Up Studies , Humans , Magnetic Resonance Imaging , Male , Middle Aged , Nervous System Diseases/diagnostic imaging , Nervous System Diseases/etiology , Stroke/complicationsABSTRACT
BACKGROUND: The chronic hemodialysis imposes various limitations on patients that may affect their quality of life. However, Tunisian studies on this matter remain scarce. AIMS: To assess the quality of life among hemodialysis patients and to identify the factors influencing their quality of life. METHODS: We performed a cross-sectional study which included 71 outpatients, during the month of January 2013, in the department of Nephrology at Hedi Chaker Sfax university hospital in Tunisia. We used the specific scale Kidney Disease Quality of Life Short-Form (KDQOL-SF™) to assess the patient's quality of life. This instrument combines the short form 36 health survey questionnaire (SF-36) and a specific module adapted to renal function. Regression analysis was used to adjust for confounding factors. RESULTS: The global average score, according to KDQOL-SF and the SF-36 were respectively 51.6 and 38.2. The QOL was impaired in 90% of the cases. The logistic regression identified six variables to be correlated with impaired QOL. These six factors in descending order of importance were: lack of autonomy, a dialysis rhythm of thrice a week, an age over 60 years, a comorbid diabetes, low social economic level and living in rural areas. CONCLUSION: Our study highlights the high frequency of QOL impairment upon patients on hemodialysis underlining the interest of a systematic effort to assess the quality of life in those patients. It also shows the interest of acting upon modifiable factors correlated with the alteration of the quality of life. In this way, the professional integration of the patients should be favored as well as peritoneal dialysis.
