Evidence map›Paper›PMID 36124254›Full record

ArticleSensors and actuators. B, Chemical2022

Plasma-induced nanoparticle aggregation for stratifying COVID-19 patients according to disease severity.

Giulia Santopolo, Antonio Clemente, Marta González-Freire, Steven M Russell, Andreu Vaquer, Enrique Barón, María Aranda, Antonia Socias, Alberto Del Castillo, Marcio Borges and 1 more

Open access · greenAbstract read
In one paragraph

Article in Sensors and actuators. B, Chemical, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 43% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Coronavirus Anatomy and Its Analytical Approaches for Targeting COVID-19.Advances in experimental medicine and biology · 2024
    Review
  3. 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

11 authors at 3 institutions in 1 country.

Giulia SantopoloMultidisciplinary Sepsis Group, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma, Spain.
Antonio ClementeMultidisciplinary Sepsis Group, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma, Spain.
Marta González-FreireTranslational Research In Aging and Longevity (TRIAL) group, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma, Spain.
Steven M RussellMultidisciplinary Sepsis Group, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma, Spain.
Andreu VaquerMultidisciplinary Sepsis Group, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma, Spain.
Enrique BarónMultidisciplinary Sepsis Group, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma, Spain.
María ArandaMultidisciplinary Sepsis Group, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma, Spain.
Antonia SociasMultidisciplinary Sepsis Group, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma, Spain.
Alberto Del CastilloMultidisciplinary Sepsis Group, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma, Spain.
Marcio BorgesMultidisciplinary Sepsis Group, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma, Spain.
Roberto de la RicaMultidisciplinary Sepsis Group, Health Research Institute of the Balearic Islands (IdISBa), 07120 Palma, Spain.
Health Research Institute of the Balearic Islands · ESHospital Son Llatzer · ESCentro de Investigación Biomédica en Red · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stratifying patients according to disease severity has been a major hurdle during the COVID-19 pandemic. This usually requires evaluating the levels of several biomarkers, which may be cumbersome when rapid decisions are required. In this manuscript we show that a single nanoparticle aggregation test can be used to distinguish patients that require intensive care from those that have already been discharged from the intensive care unit (ICU). It consists of diluting a platelet-free plasma sample and then adding gold nanoparticles. The nanoparticles aggregate to a larger extent when the samples are obtained from a patient in the ICU. This changes the color of the colloidal suspension, which can be evaluated by measuring the pixel intensity of a photograph. Although the exact factor or combination of factors behind the different aggregation behavior is unknown, control experiments demonstrate that the presence of proteins in the samples is crucial for the test to work. Principal component analysis demonstrates that the test result is highly correlated to biomarkers of prognosis and inflammation that are commonly used to evaluate the severity of COVID-19 patients. The results shown here pave the way to develop nanoparticle aggregation assays that classify COVID-19 patients according to disease severity, which could be useful to de-escalate care safely and make a better use of hospital resources.

Indexed as

Alb, albuminAST, aspartate aminotransferaseALT, alanine aminotransferaseC1.75, protein concentration 1.75 × 10-4 g·dL-1ColorimetricCPImin, protein concentration at PIminCreat, creatinineCRP, C-reactive proteinD-D, D-dimerFerr, ferritinGGT, gamma-glutamyl transferaseGlu, glucoseGoldHb, hemoglobinICU, intensive care unitINR, international normalized ratio (prothrombin time)LDH, lactate dehydrogenaseLSPR, localized surface plasmon resonanceMCV, mean corpuscular volumeMono, monocytesMPV, mean platelet volumeNIR, near-infraredNLR, neutrophil-to-lymphocyte ratioNTA, nanoparticle tracking analysisPDW, platelet distribution widthPI1.75, pixel intensity at C1.75PIdil, pixel intensity at plasma dilution 1:31250PImin, minimum value of pixel intensityPI, pixel intensityPlasmonicPLR, platelet-to-lymphocyte ratioRBC, red blood cellsRDW, red cell distribution widthSARS-CoV-2SepsisTG, triglyceridesTotProt, total protein concentrationWBC, white blood cells

Identifiers

PMID36124254
PMCPMC9476366
OpenAlexW4295950614

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.