Evidence map›Paper›PMID 32490731›Full record

ReviewEmerging microbes & infections2020

Targeting SARS-CoV-2 receptors as a means for reducing infectivity and improving antiviral and immune response: an algorithm-based method for overcoming resistance to antiviral agents.

Ram Gelman, Areej Bayatra, Asa Kessler, Asaf Schwartz, Yaron Ilan

Open access · goldAbstract readReview
In one paragraph

Review in Emerging microbes & infections, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed
1.4field-weighted citation impact, top 10% 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

53 citing papers in PubMed, 77 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Ram GelmanDepartment of Medicine, Hebrew University-Hadassah Medical Center, Jerusalem, Israel.
Areej BayatraDepartment of Medicine, Hebrew University-Hadassah Medical Center, Jerusalem, Israel.
Asa KesslerDepartment of Medicine, Hebrew University-Hadassah Medical Center, Jerusalem, Israel.
Asaf SchwartzDepartment of Medicine, Hebrew University-Hadassah Medical Center, Jerusalem, Israel.
Yaron IlanDepartment of Medicine, Hebrew University-Hadassah Medical Center, Jerusalem, Israel.ORCID https://orcid.org/0000-0003-0802-1220
Hadassah Medical Center · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ongoing severe acute respiratory syndrome pandemic caused by the novel coronavirus 2 (SARS-CoV-2) is associated with high morbidity and mortality rates, and it has created a pressing global need for effective antiviral therapies against it. COVID-19 disease pathogenesis is characterized by an initial virus-mediated phase, followed by inappropriate hyperactivation of the immune system leading to organ damage. Targeting of the SARS-CoV-2 viral receptors is being explored as a therapeutic option for these patients. In this paper, we summarize several potential receptors associated with the infectivity of SARS-CoV-2 and discuss their association with the immune-mediated inflammatory response. The potential for the development of resistance towards antiviral drugs is also presented. An algorithm-based platform to improve the efficacy of and overcome resistance to viral receptor blockers through the introduction of personalized variability is described. This method is designed to ensure sustained antiviral effectiveness when using SARS-CoV-2 receptor blockers.

Indexed as

Drug Resistance, ViralAlgorithmsAnimalsAntiviral AgentsBetacoronavirusCoronavirus InfectionsCOVID-19HumansPandemicsPneumonia, ViralReceptors, VirusSARS-CoV-2Antiviral AgentsReceptors, VirusACECoronavirusDPP4receptorsSARS-COV-2treatmentviral resistance

Identifiers

PMID32490731
PMCPMC7473106
OpenAlexW3031203304

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.