Evidence mapPaperPMID 42587639Full record

ReviewDiagnostics (Basel, Switzerland)2026

SARS-CoV-2 Point-of-Care Testing Modalities: Integrating Molecular, Immunological, Biosensor, and AI Approaches.

Helal F Hetta, Rehab Ahmed, Abdul Haseeb, Salwa Qasim Bukhari, Zinab Alatawi, Ahmad J Mahrous, Mahmoud E Elrggal, Mohammad Al Masri, Ahmed A Kotb

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Helal F HettaDivision of Microbiology, Immunology and Biotechnology, Department of Natural Products and Alternative Medicine, Faculty of Pharmacy, University of Tabuk, Tabuk 71491, Saudi Arabia.ORCID 0000-0001-8541-7304
Rehab AhmedDivision of Microbiology, Immunology and Biotechnology, Department of Natural Products and Alternative Medicine, Faculty of Pharmacy, University of Tabuk, Tabuk 71491, Saudi Arabia.
Abdul HaseebDepartment of Pharmacy Practice, Faculty of Pharmacy, University of Tabuk, Tabuk 71491, Saudi Arabia.
Salwa Qasim BukhariDepartment of Diagnostic Radiology, Faculty of Medicine, University of Tabuk, Tabuk 71491, Saudi Arabia.ORCID 0000-0002-8025-5454
Zinab AlatawiDepartment of Family and Community Medicine, Faculty of Medicine, University of Tabuk, Tabuk 47512, Saudi Arabia.ORCID 0000-0002-8963-8398
Ahmad J MahrousDepartment of Pharmaceutical Practices, College of Pharmacy, Umm Al-Qura University, Makkah 21955, Saudi Arabia.ORCID 0000-0002-7140-741X
Mahmoud E ElrggalCollege of Medicine, Al Qunfudah Umm Al-Qura University, Al Qunfudhah 28821, Saudi Arabia.
Mohammad Al MasriFaculty of Allied Medical Sciences, Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman 19111, Jordan.
Ahmed A KotbDepartment of Microbiology and Immunology, Faculty of Pharmacy, Assiut University, Assiut 71515, Egypt.ORCID 0009-0007-3368-3994

Funding

Umm al-Qura University 26UQU4320605GSSR03
6 · The paper itself

Abstract

The coronavirus disease 2019 (COVID-19) pandemic highlighted the critical need for rapid, accessible, and accurate diagnostic tools to support timely clinical decision-making, outbreak control, and public health surveillance. Point-of-care testing (POCT) has emerged as an essential component of decentralized healthcare by enabling diagnostic testing outside conventional laboratory settings. This review was based on a structured literature search of PubMed, Scopus, and Web of Science databases covering studies published between January 2020 and January 2026. The review evaluates current advances in COVID-19 POCT technologies, including molecular assays, antigen-based tests, antibody-based assays, biosensor platforms, and artificial intelligence (AI)-assisted diagnostic approaches. Molecular POCT methods, including rapid reverse transcription polymerase chain reaction (RT-PCR), loop-mediated isothermal amplification (LAMP), and CRISPR-based technologies, provide high analytical sensitivity and specificity and are increasingly suitable for decentralized diagnostic applications. Antigen-based assays offer rapid and cost-effective screening solutions, although diagnostic performance may vary depending on viral load, symptom onset, and circulating variants. Antibody-based POCT remains valuable for seroprevalence studies, retrospective diagnosis, and immune-response monitoring rather than acute infection detection. Emerging biosensor technologies and AI-enabled diagnostic systems demonstrate promising analytical capabilities and operational advantages; however, many remain at the prototype or early-validation stage and require further clinical evaluation before widespread implementation. The findings indicate that no single POCT modality is optimal for all clinical scenarios. Instead, molecular, antigen, antibody, biosensor, and AI-assisted approaches provide complementary strengths that support different diagnostic and public health objectives. Continued advances in assay design, digital connectivity, multiplex testing, and variant-resilient detection strategies are expected to further enhance the role of POCT in COVID-19 management and future infectious disease preparedness.

Indexed as

antigen testingartificial intelligencebiosensorsCOVID-19CRISPRinfectious disease surveillanceLAMPmolecular diagnosticspoint-of-care testingSARS-CoV-2

Identifiers

PMID42587639
PMCPMC13464939

What Socratic 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 Socratic graph.