Evidence map›Paper›PMID 33413116›Full record

ArticleBMC infectious diseases2021

Direct detection of Corynebacterium striatum, Corynebacterium propinquum, and Corynebacterium simulans in sputum samples by high-resolution melt curve analysis.

Shuai Xu, Xiaotong Qiu, Xuexin Hou, Haijian Zhou, Dongke Chen, Xuebing Wang, Lichao Han, Dan Li, Lina Sun, Xingzhao Ji and 4 more

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.0field-weighted citation impact, top 16% 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

8 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Clinical Characteristics and Risk Factors ofThe Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2025
    Article
  5. Review
  6. The first case of urosepsis caused byFuture microbiology · 2024
    Article
  7. Rising prevalence and drug resistance ofFrontiers in cellular and infection microbiology · 2024
    Review
  8. 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

14 authors at 2 institutions in 1 country.

Shuai XuState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Xiaotong QiuState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Xuexin HouState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Haijian ZhouState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Dongke ChenDepartment, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.
Xuebing WangState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Lichao HanState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Dan LiState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Lina SunState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Xingzhao JiState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Minghui LiState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Jingshan ZhangState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Mengtong LiState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Zhenjun LiState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China. lizhenjun@icdc.cn.
National Institute for Communicable Disease Control and Prevention · CNChinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

China Special Grant for the Prevention and Control of Infectious Diseases 2017ZX10303401National Key R&D Program of China 2017YFC1200303National Key R&D Program of China 2019YFC1200705
6 · The paper itself

Abstract

backgroundPulmonary infections caused by non-diphtheriae corynebacteria are increasing. However, rapid identification of Corynebacterium species poses a challenge due to the low genetic variation within the genus.

methodsThree reference strains and 99 clinical isolates were used in this study. A qPCR followed by high-resolution melting (HRM) targeting ssrA was performed to simultaneously identify C. striatum, C. propinquum and C. simulans. To further evaluate this assay's performance, 88 clinical sputum samples were tested by HRM and the detection results were compared with those of the traditional culture method and multiple cross-displacement amplification (MCDA) assay.

resultsThe melting curve produced by a pair of universal primers generated species-specific HRM curve profiles and could distinguish the three target species from other related bacteria. The limit of detection of HRM assay for DNA from the three purified Corynebacterium species was 100 fg. Compared with the culture method, HRM detected 22 additional positive specimens, representing a 23.9% relative increase in detection rate. The HRM assay had 98.4% (95% confidence interval [CI], 90.5-99.9%) sensitivity and 100% (95% CI, 82.8-100%) specificity. Additionally, 95.5% concordance between HRM and MCDA (κ = 0.89 [95% CI, 0.79-0.99]) was noted.

conclusionsThe HRM assay was a simple, rapid, sensitive, and specific diagnostic tool for detecting C. striatum, C. propinquum, and C. simulans, with the potential to contribute to early diagnosis, epidemiological surveillance, and rapid response to outbreak.

Indexed as

Bacterial ProteinsCorynebacteriumCorynebacterium InfectionsDNA PrimersGenotyping TechniquesHumansLimit of DetectionReal-Time Polymerase Chain ReactionSputumBacterial ProteinsDNA PrimersBacterial identificationCorynebacterium speciesDiagnosticsHigh-resolution melt curve analysis

Identifiers

PMID33413116
PMCPMC7788810
OpenAlexW3118298462

What OpenQuestion holds

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LicenceCC BY
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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.