Predictors of seizure detection and EEG clinical impact in an italian tertiary emergency department.

BACKGROUND AND OBJECTIVES: Epileptic seizures pose challenges in emergency departments (ED), affecting up to 10% of admitted patients. This study aimed to assess emergency electroencephalogram (EmEEG) utilization, identifying factors predicting seizure detection and its influence on clinical decisions. METHODS: A retrospective review of 1135 EmEEGs on 1017 patients at a tertiary teaching hospital between June 2022 and June 2023 was conducted. Data included demographics, medical history, EmEEG indications, neuroimaging findings, and clinical outcomes. Statistical analyses utilized Fisher's exact tests and logistic regression models. RESULTS: EmEEG detected status epilepticus-related seizures in 5.40% of cases, seizures without status epilepticus in 3.05%, and status epilepticus without discrete seizures in 3.74%. Epileptiform abnormalities were noted in 22.12% of EmEEGs. EmEEG influenced initial diagnoses (21.24%), antiseizure medication changes (20.85%), and discharge decisions (39.04%). Predictors for seizures/status epilepticus included previous neurosurgery, seizures in the ED, and cognitive/behavioral impairment (p < 0.001). EmEEG significantly altered initial diagnoses based on witnessed seizures, involuntary movements, epileptiform abnormalities, and 1-2 Hz generalized periodic discharges (p < 0.001). Changes in antiseizure medications correlated with seizure occurrence, neuroimaging results, epileptiform abnormalities, and EEG background slowing (p < 0.001). Factors influencing discharge decisions included previous neurosurgery, consciousness impairment, acute neuroimaging pathology, EEG focal slowing, and EEG background slowing (p < 0.001). DISCUSSION: The study clarifies EmEEG's role in modifying initial diagnoses, treatment approaches, and discharge decisions. The study provides insights into the nuanced impact of EmEEG in different clinical scenarios, offering valuable guidance for clinicians in selecting patients for EmEEG, particularly in conditions of limited EEG availability.

CSF-based liquid biopsy pointing to a diagnosis of diffuse glioma in a patient with supposed neurodegenerative disorder.

INTRODUCTION: The differential diagnosis of brain diseases becomes challenging in cases where imaging is not sufficiently informative, and surgical biopsy is impossible or unacceptable to the patient. METHODS: An elderly patient with progressive short-term memory loss and cognitive impairment presented with a normal brain CT scan, a brain FDG-PET that indicated symmetrical deterioration of the white matter in the frontal lobes, and inconclusive results of a molecular marker analysis of suspected dementia in cerebrospinal fluid (CSF). Brain MRI suggested the diagnosis of lower grade glioma. The patient refused surgical biopsy. In order to investigate whether somatic mutations associated with gliomas existed, we performed a "liquid biopsy" by the targeted sequencing of cell-free DNA (cfDNA) from his CSF. RESULTS: Deep sequencing of the cfDNA from CSF revealed somatic mutations characteristically found in gliomas, including mutations of the TP53 (Arg282Trp), BRAF (Val600Glu), and IDH1 (Arg132His) genes. The patient is currently treated with temozolomide, and his clinical and MRI findings suggest the stabilization of his disease. CONCLUSION: Neurological patients may benefit from liquid biopsy diagnostic work-up as it can reveal therapeutically targetable mutations.

Peripheral brain-derived neurotrophic factor (BDNF) in insomnia: A systematic review and meta-analysis.

The brain-derived neurotrophic factor (BDNF) is associated with emotional and cognitive functioning, and it is considered a transdiagnostic biomarker for mental disorders. Literature on insomnia related BDNF changes yielded contrasting results and it has never been synthetized using meta-analysis. To fill this gap, we conducted a systematic review and meta-analysis of case-control studies examining the levels of peripheric BDNF in individuals with insomnia and healthy controls using the PRISMA guidelines. PubMed, Scopus, Medline, PsycINFO and CINAHL were searched up to Nov 2022. Nine studies met the inclusion criteria and were assessed using the Newcastle-Ottawa Scale. Eight studies reported sufficient data for meta-analysis. Random-effects models showed lower BDNF in subjects with insomnia (n = 446) than in controls (n = 706) (Hedge's g = -0.86, 95% CI: -1.39 to -0.32, p = .002). Leave-one-out sensitivity analysis confirmed that the pooled effect size was robust and not driven by any single study. However, given the small sample size, the cross-sectional nature of the measurement, and the high heterogeneity of included data, the results should be cautiously interpreted. Progress in the study of BDNF in insomnia is clinically relevant to better understand the mechanisms that may explain the relationship between disturbed sleep and mental disorders.