A systematic review of neurological manifestations of SARS‐CoV‐2 infection: the devil is hidden in the details
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: We systematically reviewed available evidence for reports of neurological signs and symptoms in patients with COVID-19 to identify cases with severe acute respiratory syndrome coronavirus (SARS-CoV)-2 infection or immune-mediated reaction in the nervous system. METHODS: We followed PRISMA guidelines and used the MEDLINE, EMBASE, Google Scholar, MedRxiv and ChinaXiv databases to search for articles on COVID-19 and nervous system involvement that were published from 1 January to 24 April 2020. Data on design, sample size, neurological assessment and related work-up were extracted. Biases were assessed with the Newcastle-Ottawa scale. RESULTS: We analysed 27 publications on potential neuroinvasive or parainfectious neurological complications of COVID-19. The reports focused on smell and taste (n = 5) and evaluation of neurological symptoms and signs in cohorts (n = 5). There were cases of Guillain-Barré syndrome/Miller-Fisher syndrome/cranial neuropathy (seven cases), meningitis/encephalitis (nine cases) and various other conditions (five cases). The number of patients with examination of cerebrospinal fluid and, in particular, SARS-CoV-2 polymerase chain reaction was negligible. Two had a positive SARS-CoV-2 polymerase chain reaction examination of cerebrospinal fluid specimen. Study of potential parenchymal involvement with magnetic resonance imaging was rare. Only four reports received a rating of the highest quality standards. CONCLUSIONS: This systematic review failed to establish comprehensive insights into nervous system manifestations of COVID-19 beyond immune-mediated complications in the aftermath of respiratory symptoms. The authors therefore provide guidance for more careful clinical, diagnostic and epidemiological studies to characterize the manifestations and burden of neurological disease caused by SARS-CoV-2 on behalf of the Infectious Disease Panel of the European Academy of Neurology.
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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 | 0.011 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.005 |
| Bibliometrics | 0.020 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".