Evidence map›Paper›PMID 38443725›Full record

ArticleThe AAPS journal2024

A Short Update on the Use of Monoclonal Antibodies in COVID-19.

Antonio Vitiello, Michela Sabbatucci, Annarita Ponzo, Antonio Salzano, Andrea Zovi

Abstract read
PubMed Publisher
In one paragraph

Article in The AAPS journal, 2024. 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
1.6field-weighted citation impact, top 19% 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, 4 citations in OpenAlex.

  1. Article
  2. Molecular mechanisms of SARS-CoV-2 entry: implications for biomedical strategies.Microbiology and molecular biology reviews : MMBR · 2025
    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

5 authors at 3 institutions in 1 country.

Antonio VitielloDirectorate General for Health Prevention, Italian Ministry of Health, Rome, Italy.ORCID 0000-0003-2623-166X
Michela SabbatucciDepartment Infectious Diseases, Italian National Institute of Health, Viale Regina Elena 299, 00161, Rome, Italy.
Annarita PonzoBiology Department L. Spallanzani, University of Pavia, Pavia, Italy.
Antonio SalzanoDirectorate General for Health Prevention, Italian Ministry of Health, Rome, Italy.
Andrea ZoviItalian Ministry of Health, Rome, Italy. zovi.andrea@gmail.com.
Ministero della Salute · ITIstituto Superiore di Sanità · ITUniversity of Pavia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Monoclonal antibodies in the prophylaxis and treatment of COVID-19 have been crucial in reducing severe infections when vaccines were unavailable. However, as the virus and its variants have changed over time, the effectiveness of monoclonal antibodies has been questioned. This technical note highlights the need to assess the antiviral activity of these antibodies against new variants and adapt treatment strategies accordingly. On the one hand, in vitro studies have suggested reduced susceptibility of the latest variants to monoclonal antibodies, whereas clinical data still show benefits in reducing severe illness and mortality, indicating that laboratory results do not always mirror real-world outcomes. As a result, although resistance to monoclonal antibodies can develop over time, they could still have an important role in COVID-19 treatment, especially when used in combination, and ongoing research aims to identify effective antibodies against new variants.

Indexed as

Antibodies, MonoclonalCOVID-19COVID-19 Drug TreatmentHumansResearch DesignAntibodies, Monoclonalclinical dataCOVID-19monoclonal antibodiesresistancevariants

Identifiers

PMID38443725
OpenAlexW4392450562

What OpenQuestion holds

Textmetadata
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.