COVID-19: A Chronological Review of the Neurological Repercussions - What do We Know by May, 2020?
Mei, P. A.; Loeb, L.
Show abstract
IntroductionDespite the new SARS-CoV-2 (COVID-19) be the seventh of the coronavirus family viruses known to cause human disease, little is known about potential symptoms and syndromes secondary to the compromise of the central and peripheral nervous systems. We reviewed neurological manifestations due to the new coronavirus, thus far published in the literature, as well as guidelines issued by sub-specialties in Neurology, to tackle the disease. Methodswe searched medical databases, such as PubMed, PubMed Central, LILACS and Google scholar for papers (case reports, short letters, case series, etc) describing neurological symptoms in patients with confirmed or suspect COVID-19 diagnosis and also searched webpages of associations and organizations that deal with neurological disorders. Resultswe describe briefly each article considered for this review. Forty-one papers were found associating neurological conditions and COVID-19. Cases are divided by disease groups and, within each disease group, results are listed in chronological order or publication date. We also discuss briefly recommendations for neurological patients, according to disease group. ConclusionAlthough there is evidence of neurological manifestations with previous coronaviruses, COVID-19 is assuring a volume of published papers not seen before for other coronavirus infections. Most neurological cases are not life-threatening, but 10 to 20% of cases will require hospitalization and are in risk for sequelae and death. Although a lot of data coming from these papers is amassing, researchers must bear in mind that many papers currently published are not yet peer-reviewed, and thus are prone to further corrections.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Neurological Disorders associated with COVID-19 Hospital Admissions : Experience of a Single Tertiary Healthcare Centre 93%
- Optical coherence tomography assessment of axonal and neuronal damage of the retina in patients with familial and sporadic multiple sclerosis 92%
- Eye movement evaluation in Multiple Sclerosis and Parkinson's Disease using a Standardized Oculomotor and Neuro-ophthalmic Disorder Assessment (SONDA) 90%
Similar papers in this journal
- Ocular vestibular evoked myogenic potential (VEMP) reveals subcortical HTLV-1-associated neurological disease 94%
- Clinical Laboratory Parameters Associated with Severe or Critical Novel Coronavirus Disease 2019 (COVID-19): A Systematic Review and Meta-analysis 93%
- Clinical characteristics of Coronavirus Disease 2019 (COVID-19) patients in Kuwait 92%
Similar papers in this journal
- Cerebrospinal fluid in COVID-19 neurological complications: no cytokine storm or neuroinflammation 89%
- A Prospective Study of Long-Term Outcomes Among Hospitalized COVID-19 Patients with and without Neurological Complications 89%
- Artificial Intelligence and Machine Learning in Aneurysmal Subarachnoid Hemorrhage: Future Promises, Perils, and Practicalities 89%
Similar papers in this journal
- Two patients with acute meningo-encephalitis concomitant to SARS-CoV-2 infection 91%
- Ocular motor biomarkers in Niemann-Pick disease type C: A prospective cross-sectional multicontinental study in 72 patients 90%
- Surgical interventions in idiopathic intracranial hypertension - a comprehensive multi-center study of outcome and the role of treatment indication 90%
Similar papers in this journal
- The COVID-19 pandemic impact on continuity of care provision on rare brain diseases and on Ataxia, Dystonia and PKU. A scoping review protocol 93%
- NATURAL HISTORY OF LAFORA DISEASE A Prognostic Systematic Review and Individual Participant Data Meta-Analysis 90%
- Utilization of CoRDS Registry to Monitor Quality of Life in Patients with VCP Multisystem Proteinopathy 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.