Evidence map›Paper›PMID 36973781›Full record

ArticleVirology journal2023

Simple prediction of COVID-19 convalescent plasma units with high levels of neutralization antibodies.

Katerina Jazbec, Mojca Jež, Klemen Žiberna, Polonca Mali, Živa Ramšak, Urška Rahne Potokar, Zdravko Kvrzić, Maja Černilec, Melita Gracar, Marjana Šprohar and 3 more

Open access · goldFull text read
In one paragraph

Article in Virology journal, 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
1.6field-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, 8 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Retrospective Analysis of Coronavirus SARS-CoV-2 Antibody Levels in COVID-19 Convalescent Plasma From Blood Donors.The Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2024
    Article
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

13 authors at 2 institutions in 1 country.

Katerina JazbecBlood Transfusion Centre of Slovenia, Šlajmerjeva 6, Ljubljana, 1000, Slovenia. katerina.jazbec@ztm.si.
Mojca JežBlood Transfusion Centre of Slovenia, Šlajmerjeva 6, Ljubljana, 1000, Slovenia.
Klemen ŽibernaBlood Transfusion Centre of Slovenia, Šlajmerjeva 6, Ljubljana, 1000, Slovenia.
Polonca MaliBlood Transfusion Centre of Slovenia, Šlajmerjeva 6, Ljubljana, 1000, Slovenia.
Živa RamšakNIB-National Institute of Biology, Ljubljana, Slovenia.
Urška Rahne PotokarBlood Transfusion Centre of Slovenia, Šlajmerjeva 6, Ljubljana, 1000, Slovenia.
Zdravko KvrzićBlood Transfusion Centre of Slovenia, Šlajmerjeva 6, Ljubljana, 1000, Slovenia.
Maja ČernilecBlood Transfusion Centre of Slovenia, Šlajmerjeva 6, Ljubljana, 1000, Slovenia.
Melita GracarBlood Transfusion Centre of Slovenia, Šlajmerjeva 6, Ljubljana, 1000, Slovenia.
Marjana ŠproharBlood Transfusion Centre of Slovenia, Šlajmerjeva 6, Ljubljana, 1000, Slovenia.
Petra JovanovičBlood Transfusion Centre of Slovenia, Šlajmerjeva 6, Ljubljana, 1000, Slovenia.
Sonja VuletićBlood Transfusion Centre of Slovenia, Šlajmerjeva 6, Ljubljana, 1000, Slovenia.
Primož RožmanBlood Transfusion Centre of Slovenia, Šlajmerjeva 6, Ljubljana, 1000, Slovenia.
Blood Transfusion Centre of Slovenia · SINational Institute of Biology · SI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHyperimmune convalescent COVID-19 plasma (CCP) containing anti-SARS-CoV-2 neutralizing antibodies (NAbs) was proposed as a therapeutic option for patients early in the new coronavirus disease pandemic. The efficacy of this therapy depends on the quantity of neutralizing antibodies (NAbs) in the CCP units, with titers ≥ 1:160 being recommended. The standard neutralizing tests (NTs) used for determining appropriate CCP donors are technically demanding and expensive and take several days. We explored whether they could be replaced by high-throughput serology tests and a set of available clinical data.

methodsOur study included 1302 CCP donors after PCR-confirmed COVID-19 infection. To predict donors with high NAb titers, we built four (4) multiple logistic regression models evaluating the relationships of demographic data, COVID-19 symptoms, results of various serological testing, the period between disease and donation, and COVID-19 vaccination status.

resultsThe analysis of the four models showed that the chemiluminescent microparticle assay (CMIA) for the quantitative determination of IgG Abs to the RBD of the S1 subunit of the SARS-CoV-2 spike protein was enough to predict the CCP units with a high NAb titer. CCP donors with respective results > 850 BAU/ml SARS-CoV-2 IgG had a high probability of attaining sufficient NAb titers. Including additional variables such as donor demographics, clinical symptoms, or time of donation into a particular predictive model did not significantly increase its sensitivity and specificity.

conclusionA simple quantitative serological determination of anti-SARS-CoV-2 antibodies alone is satisfactory for recruiting CCP donors with high titer NAbs.

Indexed as

COVID-19Antibodies, NeutralizingAntibodies, ViralCOVID-19 SerotherapyCOVID-19 VaccinesHumansImmunization, PassiveImmunoglobulin GSARS-CoV-2Spike Glycoprotein, CoronavirusAntibodies, NeutralizingAntibodies, ViralCOVID-19 VaccinesImmunoglobulin GSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2Antibody titerAnti-SARS-CoV-2 antibodiesCOVID-19 convalescent plasmaHyperimmune plasma donorsNeutralization assay

Identifiers

PMID36973781
PMCPMC10042109
OpenAlexW4361001380

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read61
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.