Evidence map›Paper›PMID 37255742›Full record

ReviewNeuroscience insights2023

Mechanisms of SARS-CoV-2-induced Encephalopathy and Encephalitis in COVID-19 Cases.

Aaron Vengalil, Damir Nizamutdinov, Matthew Su, Jason H Huang

Open access · goldAbstract readReview
In one paragraph

Review in Neuroscience insights, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.4field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Aaron VengalilNeurosurgery, Texas A&M University, College of Medicine, Temple, TX, USA.
Damir NizamutdinovNeurosurgery, Texas A&M University, College of Medicine, Temple, TX, USA.ORCID https://orcid.org/0000-0001-6020-6869
Matthew SuDepartment of BioSciences, Rice University, Houston, TX, USA.
Jason H HuangNeurosurgery, Texas A&M University, College of Medicine, Temple, TX, USA.
Temple College · USRice University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The SARS-CoV-2 virus caused an unprecedented pandemic around the globe, infecting 36.5 million people and causing the death of over 1 million in the United States of America alone. COVID-19 patients demonstrated respiratory symptoms, cardiovascular complications, and neurologic symptoms, which in most severe cases included encephalopathy and encephalitis. Hypoxia and the uncontrolled proliferation of cytokines are commonly recognized to cause encephalopathy, while the retrograde trans-synaptic spread of the virus is thought to cause encephalitis in SARS-CoV-2-induced pathogenesis. Although recent research revealed some mechanisms explaining the development of neurologic symptoms, it still remains unclear whether interactions between these mechanisms exist. This review focuses on the discussion and analysis of previously reported hypotheses of SARS-CoV-2-induced encephalopathy and encephalitis and looks into possible overlaps between the pathogenesis of both neurological outcomes of the disease. Promising therapeutic approaches to prevent and treat SARS-CoV-2-induced neurological complications are also covered. More studies are needed to further investigate the dominant mechanism of pathogenesis for developing more effective preventative measures in COVID-19 cases with the neurologic presentation.

Indexed as

brain damageCOVID-19encephalitisencephalopathymechanismsneurologic complicationsSARS-CoV-2

Identifiers

PMID37255742
PMCPMC10225804
OpenAlexW4378575652

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.