Neurologic Compromise in COVID-19: A Literature 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 disease 2019 (COVID-19) disease caused by a new coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been associated with many neurological symptoms. The purpose of this article is to describe the neurological manifestations so far reported and their probable pathogenesis. We conducted a literature review on EMBASE, MEDLINE and SCIELO databases using the terms "COVID-19", "COVID", "neurological", "neurologic", "manifestations", "implications", "Guillain-Barre syndrome", "encephalopathy". A total of 33 articles including clinical series, retrospective studies, and case reports were selected and thoroughly reviewed to describe neurological manifestations of COVID-19. There are several neurological manifestations of SARS-CoV-2 infection with different clinical presentations, severity, and prevalence. The most critical ones, such as cerebrovascular disease, encephalopathy, and Guillain-Barre syndrome, were less common and usually associated with previous medical history, known risk factors for cerebrovascular disease or advanced age. The main hypotheses for the spread of the virus are through the hematogenous route or the cribriform plate of the ethmoid bone or a disseminated severe immune response by a cytokine storm. The presence of neurological disturbances associated with laboratory tests alterations is an important clue for the physicians to promptly recognize neurological manifestations of SARS-CoV-2.
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 | 0.008 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.015 |
| 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