Evidence map›Paper›PMID 36919087›Full record

ReviewHeliyon2023

Smartphone-based corona virus detection using saliva: A mini-review.

Hamide Ehtesabi, Elham Afzalpour

Open access · goldAbstract readReview
In one paragraph

Review in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 36% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. 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

2 authors at 1 institution in 1 country.

Hamide EhtesabiFaculty of Life Sciences and Biotechnology, Shahid Beheshti University, Tehran, Iran.
Elham AfzalpourFaculty of Life Sciences and Biotechnology, Shahid Beheshti University, Tehran, Iran.
Shahid Beheshti University · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the ongoing worldwide epidemic, SARS-CoV-2 has infected millions of individuals and taken the lives of numerous victims. It is clear that early detection of infected individuals, especially asymptomatic carriers, is possible with the development of innovative analytical tools for rapid identification of COVID-19 present in nasopharyngeal swabs, serum, and saliva. The saliva, as a diagnostic sample, can be easily collected by the patient with almost no discomfort and needs specialized healthcare personnel to manage, which reduces the risks for the operator. Moreover, smartphone-based sensing systems are one of the most attractive techniques that can speed up the detection time of COVID-19 agents without the need for professional staff and clinical centers. In this review, recent advances in precise salivary-based SARS-CoV-2 diagnosis using smartphones via viral RNA detection, antibody identification, and viral antigen identification were summarized. Finally, the conclusion and future perspective of this field are described in brief.

Indexed as

COVID-19DiagnosisHealthcarePhoneSARS-CoV-2SensorViral

Identifiers

PMID36919087
PMCPMC9991337
OpenAlexW4323349236

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.