Neurological manifestations and implications of COVID-19 pandemic
Bibliographic record
Abstract
The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China and rapidly spread worldwide, with a vast majority of confirmed cases presenting with respiratory symptoms. Potential neurological manifestations and their pathophysiological mechanisms have not been thoroughly established. In this narrative review, we sought to present the neurological manifestations associated with coronavirus disease 2019 (COVID-19). Case reports, case series, editorials, reviews, case-control and cohort studies were evaluated, and relevant information was abstracted. Various reports of neurological manifestations of previous coronavirus epidemics provide a roadmap regarding potential neurological complications of COVID-19, due to many shared characteristics between these viruses and SARS-CoV-2. Studies from the current pandemic are accumulating and report COVID-19 patients presenting with dizziness, headache, myalgias, hypogeusia and hyposmia, but also with more serious manifestations including polyneuropathy, myositis, cerebrovascular diseases, encephalitis and encephalopathy. However, discrimination between causal relationship and incidental comorbidity is often difficult. Severe COVID-19 shares common risk factors with cerebrovascular diseases, and it is currently unclear whether the infection per se represents an independent stroke risk factor. Regardless of any direct or indirect neurological manifestations, the COVID-19 pandemic has a huge impact on the management of neurological patients, whether infected or not. In particular, the majority of stroke services worldwide have been negatively influenced in terms of care delivery and fear to access healthcare services. The effect on healthcare quality in the field of other neurological diseases is additionally evaluated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".