Evidence map›Paper›PMID 33177829›Full record

ReviewTherapeutics and clinical risk management2020

N-Acetylcysteine to Combat COVID-19: An Evidence Review.

Zhongcheng Shi, Carlos A Puyo

Open access · goldAbstract readReview
In one paragraph

Review in Therapeutics and clinical risk management, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 6% 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

67 citing papers in PubMed, 1 synthesis or guideline pooled it, 128 citations in OpenAlex.

  1. Pooled it
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  15. The use of combination therapy for the improvement of colistin activity against bacterial biofilm.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2024
    Review
  16. Article
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  19. Glucose metabolism disorder: a potential accomplice of SARS-CoV-2.International journal of obesity (2005) · 2023
    Review
  20. Review

7 more citing papers are in PubMed but not listed here.

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

2 authors at 1 institution in 1 country.

Zhongcheng ShiDepartment of Pathology and Immunology, Baylor College of Medicine, Houston, TX, USA.ORCID 0000-0001-9267-4536
Carlos A PuyoDepartment of Anesthesia and Critical Care, Holy Family Hospital, Steward Health Care, Methuen, MA, USA.ORCID 0000-0002-2481-0513
Baylor College of Medicine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The novel coronavirus disease (COVID-19) is caused by a virus (SARS-Cov-2) and is known for inducing multisystem organ dysfunction associated with significant morbidity and mortality. Current therapeutic strategies for COVID-19 have failed to effectively reduce mortality rate, especially for elderly patients. A newly developed vaccine against SARS-Cov-2 has been reported to induce the production of neutralizing antibodies in young volunteers. However, the vaccine has shown limited benefit in the elderly, suggesting an age-dependent immune response. As a result, exploring new applications of existing medications could potentially provide valuable treatments for COVID-19. N-acetylcysteine (NAC) has been used in clinical practice to treat critically ill septic patients, and more recently for COVID-19 patients. NAC has antioxidant, anti-inflammatory and immune-modulating characteristics that may prove beneficial in the treatment and prevention of SARS-Cov-2. This review offers a thorough analysis of NAC and discusses its potential use for treatment of COVID-19.

Indexed as

COVID-19N-acetylcysteineSARS-Cov-2

Identifiers

PMID33177829
PMCPMC7649937
OpenAlexW3095048012

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.