SARS-CoV-2 and Nervous System - Neurological Manifestations in Patients With COVID-19: A Systematic Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Coronavirus (CoV) is a virus infectious disease with a considerable spectrum of clinical presentations. Symptoms ranged from asymptomatic infection to severe pneumonia that may lead to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and several clinical complications. Neurologic symptoms related to CoV have been described recently in the literature. The relationship between SARS-CoV-2 and the central nervous system (CNS) is still not clear. This review aimed to reveal the current knowledge regarding CNS manifestation in SARS-CoV-2. A systematic literature review was carried out to identify the particularities of coronavirus disease 2019 (COVID-19) in patients with CNS involvement, using the PubMed database between January 1, 2020 and April 30, 2020. Conference papers, reviews, published letters, editorials, studies in pregnant women and children, and studies only reporting on a specific factor were excluded. An initial search included as many as 83 articles. Out of the 83 screened articles, 32 were selected for full-text review. Sixteen studies were excluded because they did not analyze nervous system involvement in SARS-CoV-2 infection. Thus, 16 papers were included in this review. There were three retrospective studies and 13 case reports/series of cases. Data from the current literature reveal that patients who suffer from a severe illness have more CNS involvement, neurological symptoms (i.e., dizziness, headache) and an association with strokes. The severe patients had higher D-dimer and C-reactive protein levels than non-severe patients and presented multiple organ involvement, such as serious liver, kidney and muscle damage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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 it