Evidence map›Paper›PMID 37990045›Full record

ArticleScientific reports2023

Optimization of extraction-free protocols for SARS-CoV-2 detection using a commercial rRT-PCR assay.

Minhee Kang, Eunjung Jeong, Ji-Yeon Kim, Sun Ae Yun, Mi-Ae Jang, Ja-Hyun Jang, Tae Yeul Kim, Hee Jae Huh, Nam Yong Lee

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 22% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Minhee Kang *Smart Healthcare Research Institute, Biomedical Engineering Research Center, Samsung Medical Center, Seoul, South Korea.
Eunjung Jeong *Smart Healthcare Research Institute, Biomedical Engineering Research Center, Samsung Medical Center, Seoul, South Korea.
Ji-Yeon KimSamsung Biomedical Research Institute, Center for Clinical Medicine, Samsung Medical Center, Seoul, South Korea.
Sun Ae YunSamsung Biomedical Research Institute, Center for Clinical Medicine, Samsung Medical Center, Seoul, South Korea.
Mi-Ae JangDepartment of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
Ja-Hyun JangDepartment of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
Tae Yeul KimDepartment of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea. voltaire0925@gmail.com.
Hee Jae HuhDepartment of Medical Device Management and Research, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, South Korea. pmhhj77@gmail.com.
Nam Yong LeeDepartment of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
Samsung Medical Center · KRSungkyunkwan University · KR

Funding

Future Medicine 2030 Project of the Samsung Medical Center SMX1230761Korea Medical Device Development Fund grant funded by the Korea government (the Ministry of Science and ICT, the Ministry of Trade, Industry and Energy, the Ministry of Health & Wel-fare, Republic of Korea, the Ministry of Food and Drug Safety RS-2020-KD000004National Research Foundation of Korea (NRF) grant funded by the Korean Government (MSIT) 2022M3H4A4097528
6 · The paper itself

Abstract

In the ongoing global fight against coronavirus disease 2019 (COVID-19), the sample preparation process for real-time reverse transcription polymerase chain reaction (rRT-PCR) faces challenges due to time-consuming steps, labor-intensive procedures, contamination risks, resource demands, and environmental implications. However, optimized strategies for sample preparation have been poorly investigated, and the combination of RNase inhibitors and Proteinase K has been rarely considered. Hence, we investigated combinations of several extraction-free protocols incorporating heat treatment, sample dilution, and Proteinase K and RNase inhibitors, and validated the effectiveness using 120 SARS-CoV-2 positive and 62 negative clinical samples. Combining sample dilution and heat treatment with Proteinase K and RNase inhibitors addition exhibited the highest sensitivity (84.26%) with a mean increase in cycle threshold (Ct) value of + 3.8. Meanwhile, combined sample dilution and heat treatment exhibited a sensitivity of 79.63%, accounting for a 38% increase compared to heat treatment alone. Our findings highlight that the incorporation of Proteinase K and RNase inhibitors with sample dilution and heat treatment contributed only marginally to the improvement without yielding statistically significant differences. Sample dilution significantly impacts SARS-CoV-2 detection, and sample conditions play a crucial role in the efficiency of extraction-free methods. Our findings may provide insights for streamlining diagnostic testing, enhancing its accessibility, cost-effectiveness, and sustainability.

Indexed as

COVID-19SARS-CoV-2Clinical Laboratory TechniquesCOVID-19 TestingEndopeptidase KHumansReverse Transcriptase Polymerase Chain ReactionRibonucleasesRNA, ViralSensitivity and SpecificityEndopeptidase KRibonucleasesRNA, Viral

Identifiers

PMID37990045
PMCPMC10663557
OpenAlexW4388857528

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.