Evidence map›Paper›PMID 34518727›Full record

ArticleInternational journal of energy research2021

Application of microfluidic paper-based analytical device (μPAD) to detect COVID-19 in energy deprived countries.

Mosfera A Chowdury, Farrukh Khalid

Abstract read
In one paragraph

Article in International journal of energy research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
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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

2 authors.

Mosfera A ChowdurySystem Integration Team Nicoya Lifesciences Inc. Kitchener Ontario Canada.
Farrukh KhalidDepartment of Mechanical Engineering Istinye University Istanbul Turkey.ORCID https://orcid.org/0000-0003-4600-3496

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronavirus disease (COVID-19) has spread all across the world. Low- and medium-income countries are more affected economically and socially compared to developed countries due to the lack of a rapid, robust, and affordable testing infrastructure. Furthermore, the high cost of real-time polymerase chain reaction (PCR) system, sophisticated user-handling procedure, and high expense of the conventional clinical tests are the root causes of the less accessibility of the testing systems to the users. In this study, a COVID-19 Point-of-Care (POC) ecosystem model is proposed for the low- and medium-income countries (or energy deprived countries) that will facilitate the technological development with locally available fabrication components. In addition, the nontechnological development phases have also been discussed, which encompasses the collaboration among academia, local as well as government bodies, and entrepreneurial ventures. In addition, a hypothetical design of a microfluidic paper-based analytical (μPADs) POC platform is proposed to detect COVID-19 analyte using unprocessed patient-derived saliva, which is a miniaturized form-factor of conventional real-time polymerase chain reaction (PCR) technique. The device contains four major reaction zones, which are sample zone, buffer zone, loop-mediated isothermal amplification (LAMP) Master Mix zone, Ethylenediamine tetraacetic acid (EDTA) zone, and sensor zone. To obtain quicker test results and easier operation, a handheld image acquisition technique is introduced in this study. It is hypothesized that in a remote setting, the proposed design could be used as an initial guideline to develop a POC COVID-19 testing system, which may be simple, easy-to-use, and cost-effective.

Indexed as

COVIDmicrofluidicPoint‐of‐Care

Identifiers

PMID34518727
PMCPMC8427062

What OpenQuestion holds

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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.