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RATIONALE: Miller-Fisher syndrome (MFS) is a rare subtype of Guillain-Barre syndrome with classic features of ataxia, areflexia, and ophthalmoplegia that can be caused by a preceding infection including COVID-19. We present a current, asymptomatic thrombocytopenic COVID-19 infection as a cause of MFS in a 60-year-old male with a concurrent chronic immune neuropathy. PATIENT CONCERNS: A 60-year-old male presenting with acute symptoms of MFS including ataxia, areflexia, and ophthalmoplegia on a chronic immune neuropathy for at least 1 year and concurrent asymptomatic COVID-19 positive infection. DIAGNOSIS: MFS suspected secondary to a current thrombocytopenic COVID-19 infection. INTERVENTIONS: Five days of intravenous immune globulin with continued monthly intravenous immune globulin as an outpatient, follow-up long-term in a neuromuscular clinic, electromyography as an outpatient, and continued physical therapy. OUTCOMES: The patient significantly improved after initial treatment. LESSONS: The full effect of COVID-19 on the various Guillain-Barre syndrome subtypes is unknown, although it clearly can be a cause of the various variants including being caused by a current, asymptomatic infection.
Asunto(s)
COVID-19 , Inmunoglobulinas Intravenosas , Síndrome de Miller Fisher , Humanos , Síndrome de Miller Fisher/diagnóstico , Síndrome de Miller Fisher/inmunología , Masculino , COVID-19/complicaciones , COVID-19/inmunología , Persona de Mediana Edad , Inmunoglobulinas Intravenosas/uso terapéutico , SARS-CoV-2 , TrombocitopeniaRESUMEN
We present a case of infratentorial variant posterior reversible encephalopathy syndrome (PRES), which is a very rare presentation of PRES. Atypical PRES is more common than the typical parieto-occipital PRES. We present a 43-year-old male who presented with acute change in mentation, left gaze deviation, and paraparesis with initial blood pressures of 230/120 with anasarca. In the present admission, his CT showed diffuse infratentorial hypodensity. Computed tomography angiography (CTA) was negative for large vessel occlusion. MRI of the brain without contrast showed fluid-attenuated inversion recovery (FLAIR) change diffusely in the brainstem but also extended to the cerebellum and occipital lobe, along with diffusion restriction seen in different regions, including the brainstem and cortex. The patient improved clinically with the improvement of blood pressure and follow-up imaging in five weeks showed improvement of imaging findings. This presentation helps understand the approach to patients presenting with brainstem edema in the acute phase.
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Background: Adverse effects of antiseizure medications (ASMs) remain one of the major causes of non-adherence. Cosmetic side effects (CSEs) are among the most commonly reported side effects of ASMs. In this context, alopecia is one of the CSEs that has a high intolerance rate leading to poor therapeutical compliance. Methods: We performed a literature review concerning alopecia as a secondary effect of ASMs. Results: There are 1656 individuals reported with ASM-induced alopecia. Valproate (983), lamotrigine (355), and carbamazepine (225) have been extensively reported. Other ASMs associated with alopecia were cenobamate (18), levetiracetam (14), topiramate (13), lacosamide (7), vigabatrin (6), phenobarbital (5), gabapentin (5), phenytoin (4), pregabalin (4), eslicarbazepine (3), brivaracetam (2), clobazam (2), perampanel (2), trimethadione (2), rufinamide (2), zonisamide (2), primidone (1), and tiagabine (1). There were no reports of oxcarbazepine and felbamate with drug-induced alopecia. Hair loss seen with ASMs was diffuse and non-scarring. Telogen effluvium was the most common cause of alopecia. A characteristic feature was the reversibility of alopecia after ASM dose adjustment. Conclusions: Alopecia should be considered one important adverse effect of ASMs. Patients reporting hair loss with ASM therapy should be further investigated, and specialist consultation is recommended.
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Teleneurology has provided access to neurological expertise and state-of-the-art stroke care where previously they have been inaccessible. The use of Artificial Intelligence with machine learning to assist telestroke care can be revolutionary. This includes more rapid and more reliable diagnosis through imaging analysis as well as prediction of hospital course and 3-month prognosis. Intelligent Electronic Medical Records can search free text and provide decision assistance by analyzing patient charts. Speech recognition has advanced enough to be reliable and highly convenient. Smart contextually aware communication and alert programs can enhance efficiency of patient flow and improve outcomes. Automated data collection and analysis can make quality improvement and research projects quicker and much less burdensome. Despite current challenges, these synergistic technologies hold immense promise in enhancing the clinician experience, helping to reduce physician burnout while improving patient health outcomes at a lower cost. This brief overview discusses the multifaceted potential of AI use in telestroke.
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In recent years, transcranial magnetic stimulation has become an area of interest in the field of neurosciences due to its ability to non-invasively induce sufficient electric current to depolarize superficial axons and networks in the cortex and can be used to explore brain functioning. Evidence shows that transcranial magnetic stimulation could be used as a diagnostic and therapeutic tool for various neurological and psychiatric illnesses. The aim of this review is to introduce the basics of this technology to the readers and to bring together an overview of some of its clinical applications investigated thus far.