The effect of sleep disorders on quality of life in patients with epilepsy: A multicenter study from Turkey.

OBJECTIVE: We aimed to investigate sleep disorders in patients with epilepsy (PWE) and to investigate the effects of sleep disorders on quality of life. METHODS: In our multicenter study conducted in Turkey, 1358 PWE were evaluated. The demographic and clinical data of the patients were recorded. The Insomnia Severity Index (ISI), Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), Beck Depression Inventory (BDI), and Quality of Life in Epilepsy Inventory-10 (QOLIE-10) were administered. RESULTS: The mean age of 1358 patients was 35.92 ±â€¯14.11 (range, 18-89) years. Seven hundred fifty-one (55.30 %) were women. Some 12.7 % of the patients had insomnia (ISI > 14), 9.6 % had excessive daytime sleepiness (ESS > 10), 46.5 % had poor sleep quality (PSQI > 5), and 354 patients (26.1 %) had depressive symptoms (BDI > 16). The mean QOLIE-10 score was 22.82 ±â€¯8.14 (10-48). Resistant epilepsy was evaluated as the parameter with the highest risk affecting quality of life Adjusted odds ratio (AOR = 3.714; 95 % confidence interval (CI): [2.440-5.652] < 0.001)). ISI (AOR = 1.184; 95 % CI: [1.128-1.243]; p < 0.001), ESS (AOR = 1.081; 95 % CI: [1.034-1.130]; p < 0.001), PSQI (AOR = 0.928; 95 % CI: [0.867 - 0.994]; p = 0.034), BDI (AOR = 1.106; 95 % CI: [1.084-1.129]; p < 0.001), epilepsy duration (AOR = 1.023; 95 % CI: [1.004-1.041]; p = 0.014), were determined as factors affecting quality of life. SIGNIFICANCE: Sleep disorders are common in PWE and impair their quality of life. Quality of life can be improved by controlling the factors that may cause sleep disorders such as good seizure control, avoiding polypharmacy, and correcting the underlying mood disorders in patients with epilepsy.

Headache in idiopathic/genetic epilepsy: Cluster analysis in a large cohort.

OBJECTIVE: The link between headache and epilepsy is more prominent in patients with idiopathic/genetic epilepsy (I/GE). We aimed to investigate the prevalence of headache and to cluster patients with regard to their headache and epilepsy features. METHODS: Patients aged 6-40 years, with a definite diagnosis of I/GE, were consecutively enrolled. The patients were interviewed using standardized epilepsy and headache questionnaires, and their headache characteristics were investigated by experts in headache. Demographic and clinical variables were analyzed, and patients were clustered according to their epilepsy and headache characteristics using an unsupervised K-means algorithm. RESULTS: Among 809 patients, 508 (62.8%) reported having any type of headache; 87.4% had interictal headache, and 41.2% had migraine. Cluster analysis revealed two distinct groups for both adults and children/adolescents. In adults, subjects having a family history of headache, ≥5 headache attacks, duration of headache ≥ 24 months, headaches lasting ≥1 h, and visual analog scale scores > 5 were grouped in one cluster, and subjects with juvenile myoclonic epilepsy (JME), myoclonic seizures, and generalized tonic-clonic seizures (GTCS) were clustered in this group (Cluster 1). Self-limited epilepsy with centrotemporal spikes and epilepsy with GTCS alone were clustered in Cluster 2 with the opposite characteristics. For children/adolescents, the same features as in adult Cluster 1 were clustered in a separate group, except for the presence of JME syndrome and GTCS alone as a seizure type. Focal seizures were clustered in another group with the opposite characteristics. In the entire group, the model revealed an additional cluster, including patients with the syndrome of GTCS alone (50.51%), with ≥5 attacks, headache lasting >4 h, and throbbing headache; 65.66% of patients had a family history of headache in this third cluster (n = 99). SIGNIFICANCE: Patients with I/GE can be clustered into distinct groups according to headache features along with seizures. Our findings may help in management and planning for future studies.

Compound muscle action potential scan and MScanFit motor unit number estimation during Wallerian degeneration after nerve transections.

BACKGROUND: Compound muscle action potential (CMAP) scan and MScanFit have been used to understand the consequences of denervation and reinnervation. This study aimed to monitor these parameters during Wallerian degeneration (WD) after acute nerve transections (ANT). METHODS: Beginning after urgent surgery, CMAP scans were recorded at 1-2 day intervals in 12 patients with ANT of the ulnar or median nerves, by stimulating the distal stump (DS). Stimulus intensities (SI), steps, returners, and MScanFit were calculated. Studies were grouped according to the examination time after ANT. Results were compared with those of 27 controls. RESULTS: CMAP amplitudes and MScanFit progressively declined, revealing a positive correlation with one another. SIs were higher in WD groups than controls. Steps appeared or disappeared in follow-up scans. The late WD group had higher returner% than the early WD and control groups. CONCLUSIONS: MScanFit can monitor neuromuscular dysfunction during WD. SIs revealed excitability changes in DS.