Evidence map›Paper›PMID 35857467›Full record

ArticleScience advances2022

A handheld intelligent single-molecule binary bioelectronic system for fast and reliable immunometric point-of-care testing.

Eleonora Macchia, Zsolt M Kovács-Vajna, Daniela Loconsole, Lucia Sarcina, Massimiliano Redolfi, Maria Chironna, Fabrizio Torricelli, Luisa Torsi

Open access · goldAbstract read
In one paragraph

Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
5.0field-weighted citation impact, top 3% 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

18 citing papers in PubMed, 60 citations in OpenAlex.

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  10. Innovative solutions for disease management.Bioelectronic medicine · 2023
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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

8 authors at 3 institutions in 2 countries.

Eleonora MacchiaDipartimento di Farmacia-Scienze del Farmaco, Universit. degli Studi di Bari "Aldo Moro," 70125 Bari, Italy.ORCID 0000-0002-1534-7336
Zsolt M Kovács-VajnaDipartimento di Ingegneria dell'Informazione, Università degli Studi di Brescia, 25123 Brescia, Italy.
Daniela LoconsoleDipartimento di Scienze Biomediche e Oncologia Umana, Università degli Studi di Bari "Aldo Moro," 70125 Bari, Italy.
Lucia SarcinaDipartimento di Chimica, Università degli Studi di Bari "Aldo Moro," 70125 Bari, Italy.ORCID 0000-0001-7797-029X
Massimiliano RedolfiIntersail Engineering, Via Pianette, 25064 Gussago, Brescia, Italy.ORCID 0000-0003-0314-1741
Maria ChironnaDipartimento di Scienze Biomediche e Oncologia Umana, Università degli Studi di Bari "Aldo Moro," 70125 Bari, Italy.ORCID 0000-0002-1043-1256
Fabrizio TorricelliDipartimento di Ingegneria dell'Informazione, Università degli Studi di Brescia, 25123 Brescia, Italy.ORCID 0000-0002-7932-0677
Luisa TorsiDipartimento di Chimica, Università degli Studi di Bari "Aldo Moro," 70125 Bari, Italy.ORCID 0000-0002-0798-0780
University of Bari Aldo Moro · ITUniversity of Brescia · ITÅbo Akademi University · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular tests are highly reliable and sensitive but lack portability and are not simple to use; conversely, easy-to-use antigenic tests still lack high performance. BioScreen combines single-molecule sensitivity and outstanding reliability with ultraportability and simplicity of use. This digital platform is capable of artificial intelligence-based binary classification at the limit of identification of a single marker/virus in 0.1 ml. The diagnostic sensitivity, specificity, and accuracy reach 99.2% as validated through 240 assays, including a pilot clinical trial. The versatile immunometric system can detect the SARS-CoV-2 virus, spike S1, and immunoglobulin G antigen proteins in saliva, blood serum, and swab. BioScreen has a small footprint comprising a disposable cartridge and a handheld electronic reader connected to a smart device. The sample handling is minimal, and the assay time to result is 21 min. Reliable and sensitive self-testing with an ultraportable and easy-to-use diagnostic system operated directly by a patient holds the potential to revolutionize point-of-care testing and early diagnosis.

Indexed as

COVID-19SARS-CoV-2Artificial IntelligenceHumansPoint-of-Care TestingReproducibility of ResultsSensitivity and Specificity

Identifiers

PMID35857467
PMCPMC9258948
OpenAlexW4286245995

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.