The effect of SARS-CoV-2 on the nervous system: a review of neurological impacts caused by human coronaviruses
Bibliographic record
Abstract
The COVID-19 pandemic has affected millions of people worldwide. While coronaviruses typically have low rates of neurotropic effects, the massive transmission of SARS-CoV-2 suggests that a substantial population will suffer from potential SARS-CoV-2-related neurological disorders. The rapid and recent emergence of SARS-CoV-2 means little research exists on its potential neurological effects. Here we analyze the effects of similar viruses to provide insight into the potential effects of SARS-CoV-2 on the nervous system and beyond. Seven coronavirus strains (HCoV-OC43, HCoV-HKU1, HCoV-229E, HCoV-NL63, SARS-CoV, MERS-CoV, SARS-CoV-2) can infect humans. Many of these strains cause neurological effects, such as headaches, dizziness, strokes, seizures, and critical illness polyneuropathy/myopathy. Certain studies have also linked coronaviruses with multiple sclerosis and extensive central nervous system injuries. Reviewing these studies provides insight into the anticipated effects for patients with SARS-CoV-2. This review will first describe the effects of other coronaviruses that have caused severe disease (SARS-CoV, MERS-CoV) on the nervous system, as well as their proposed origins, non-neurological effects, and neurological infection mechanisms. It will then discuss what is known about SARS-CoV-2 in these areas with reference to the aforementioned viruses, with the goal of providing a holistic picture of SARS-CoV-2.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".