Updates on the neurological manifestations of SARS-CoV-2 infection
Bibliographic record
Abstract
PURPOSE OF REVIEW: Since its emergence in 2020, the COVID-19 pandemic has created a global surge of survivors experiencing neurologic effects from SARS-CoV-2 infection. This review aims to provide an updated synthesis of the acute and chronic neurological manifestations of COVID-19, and to outline the current therapeutic strategies for these conditions. RECENT FINDINGS: Epidemiological studies have shown that COVID-19 patients with neurological symptoms during acute infection tend to have poorer hospital and functional outcomes. While the risk of adverse neurologic symptoms including cognitive dysfunction, headache, autonomic dysfunction, and chronic fatigue are thought to be greatest following infection with the original SARS-CoV-2 strain and its alpha variant, they remain prevalent after infection with subsequent less virulent strains as well. Some recent work has also found a link between SARS-CoV-2 and structural brain changes. However, ongoing trials show promising results for pharmacologic and nonpharmacologic treatments targeting the postacute neurological sequelae of COVID-19. SUMMARY: Lingering neurological manifestations after COVID-19 still pose considerable individual, healthcare system, and socioeconomic repercussions. Both preventive and multimodal treatment approaches are necessary to address these conditions. Further research is required to assess the lasting impacts of SARS-CoV-2 on the nervous system, particularly its potential contribution to the development of neurodegenerative diseases.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".