Cited by 224Long-Term Effects of COVID-19Infectious Encephalopathies and EncephalitisCOVID-19 Clinical Research Studies

Encephalopathy in patients with COVID‐19: A review

Garg, Ravindra Kumar, Paliwal, Vimal Kumar, Gupta, Ankit·2021·Journal of Medical Virology

Abstract

Encephalopathy and encephalitis are major and devastating severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) virus‐associated central nervous system complications. Hypoxic/metabolic changes produced by intense inflammatory response against the virus triggers cytokine storm and subsequently acute respiratory distress syndrome and multiple organ failure. Hypoxic/metabolic changes result in encephalopathy. The presence of comorbidities predisposes to hypoxic/metabolic changes responsible for encephalopathy. Altered consciousness, ranging from mild confusion, delirium, to deep coma, is hallmark clinical features. Cortical and subcortical T2/FLAIR signal changes are common neuroimaging abnormalities. In a few isolated case reports of SARS‐CoV‐2 encephalitis, the virus has been demonstrated in cerebrospinal fluid. The presence of anosmia and ageusia can help in differentiation from other encephalopathies. We analyzed published reports on coronavirus disease 2019‐associated encephalopathy. Encephalopathy is common in older patients, the majority are more than 50 years of age. The patients having encephalopathy/encephalitis are either severely or critically ill. Many patients were already on mechanical ventilation. Lung abnormalities are noted in almost all of the patients, presenting with encephalopathy. Encephalopathy is always preceded by commoner clinical features, like, fever, cough, dyspnoea, and headache. In majority, patients are already in the intensive care unit, when encephalopathy develops.

Integrity signals

Registry

Crossref · 10.1002/jmv.26207

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

The citation lists haven’t been fetched yet

References 87 · Cited by 224

Authors
Garg, R. K., Paliwal, V. K., & Gupta, A.
Affiliations
  • King George's Medical University (IN)
  • Sanjay Gandhi Post Graduate Institute of Medical Sciences (IN)
Corresponding author
Garg, Ravindra Kumar
Venue
Journal of Medical Virology
Publisher
Wiley
Published
2020-07-11
Volume
93
Issue
1
Pages
206-222
ISSN
  • 0146-6615 (ISSN-L)
  • 1096-9071
OpenAlex
W3036301913
Cited by
224
References
87
Citations by year
2026: 5 · 2025: 7 · 2024: 23 · 2023: 41 · 2022: 54 · 2021: 72 · 2020: 22
FWCI
5.32
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Medical Virology (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Neurology › Long-Term Effects of COVID-19
  • Health Sciences › Medicine › Infectious Diseases › Infectious Encephalopathies and Encephalitis
  • Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
Keywords
COVID-19 pandemic, SARS-CoV-2, encephalopathy, encephalitis, central nervous system complications, hypoxia, metabolic encephalopathy, cytokine storm, acute respiratory distress syndrome, multiple organ failure, altered states of consciousness, delirium, coma, anosmia, ageusia, cerebrospinal fluid viral detection, neuroimaging abnormalities, mechanical ventilation, intensive care unit, comorbidities
MeSH terms
COVID-19, Age Factors, Ageusia, Brain Diseases, Critical Care, Headache, Humans, Critical Illness

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review