Cerebral venous sinus thrombosis as a complication of heparin-induced thrombocytopenia in myasthenia gravis: A rare and complex case.

Background: Cerebral venous sinus thrombosis (CVST) is an uncommon yet critical complication, especially when arising from heparin-induced thrombocytopenia (HIT). In patients with preexisting conditions such as myasthenia gravis (MG), this correlation adds further complexity to clinical management and outcomes.

Case Presentation: We report a unique case of CVST induced by HIT in a patient with an established diagnosis of MG.

Epilepsy Diagnosis When the Routine Ancillary Tests Are Normal.

In a patient suspected of having epilepsy, routine EEG primarily contributes to the recording of interictal epileptiform discharges (IEDs). Similarly, magnetic resonance imaging (MRI) has become the gold standard imaging technique for identifying epileptogenic structural brain abnormalities. Various EEG and MRI tools to improve epilepsy diagnosis will be presented.

Unlocking new frontiers in epilepsy through AI: From seizure prediction to personalized medicine.

Artificial intelligence (AI) is revolutionizing epilepsy care by advancing seizure detection, enhancing diagnostic precision, and enabling personalized treatment. Machine learning and deep learning technologies improve seizure monitoring, automate EEG analysis, and facilitate tailored therapeutic strategies, addressing the complexities of epilepsy management. However, challenges remain, including issues of model accuracy, interpretability, and applicability across diverse patient populations.

Sleep Disorders and Optic Neuritis Risk in Multiple Sclerosis: A Retrospective Cohort Study.

This retrospective cohort study investigates the relationship between sleep disorders and the risk of developing optic neuritis in patients with multiple sclerosis (MS). Utilizing data from the TriNetX Global Collaborative Network, we analyzed two matched cohorts as follows: MS patients with documented sleep disorders (n = 48,995) and those without (n = 48,995). Propensity score matching ensured balance in baseline characteristics, minimizing confounding factors.

Harnessing artificial intelligence for the diagnosis and treatment of neurological emergencies: a comprehensive review of recent advances and future directions.

Artificial intelligence (AI) is rapidly transforming the landscape of neurology, offering innovative solutions for diagnosing and managing emergent neurological conditions such as stroke, traumatic brain injury, and acute spinal cord injury. This review critically examines the recent advancements in AI applications within the field of neurology, emphasizing both the potential and limitations of these technologies. While AI demonstrates remarkable accuracy and speed in diagnostic imaging, outcome prediction, and personalized treatment plans, its integration into clinical practice remains challenged by ethical concerns, infrastructural limitations, and the "black box" nature of many AI algorithms.