Evidence map›Paper›PMID 25836606›Full record

ArticleChinese medical journal2015

Rapid detection and identification of infectious pathogens based on high-throughput sequencing.

Pei-Xiang Ni, Xin Ding, Yin-Xin Zhang, Xue Yao, Rui-Xue Sun, Peng Wang, Yan-Ping Gong, Jia-Li Zhou, Dong-Fang Li, Hong-Long Wu and 3 more

Abstract read
In one paragraph

Article in Chinese medical journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. The diagnostic value of metagenomic next-generation sequencing for identifyingFrontiers in cellular and infection microbiology · 2022
    Article
  6. Review
  7. Review
  8. Article
  9. 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

13 authors.

Pei-Xiang Ni
Xin Ding
Yin-Xin Zhang
Xue Yao
Rui-Xue Sun
Peng Wang
Yan-Ping Gong
Jia-Li Zhou
Dong-Fang Li
Hong-Long Wu
Xin Yi
Ling Yang
Yun LongDepartment of Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe dilemma of pathogens identification in patients with unidentified clinical symptoms such as fever of unknown origin exists, which not only poses a challenge to both the diagnostic and therapeutic process by itself, but also to expert physicians.

methodsIn this report, we have attempted to increase the awareness of unidentified pathogens by developing a method to investigate hitherto unidentified infectious pathogens based on unbiased high-throughput sequencing.

resultsOur observations show that this method supplements current diagnostic technology that predominantly relies on information derived five cases from the intensive care unit. This methodological approach detects viruses and corrects the incidence of false positive detection rates of pathogens in a much shorter period. Through our method is followed by polymerase chain reaction validation, we could identify infection with Epstein-Barr virus, and in another case, we could identify infection with Streptococcus viridians based on the culture, which was false positive.

conclusionsThis technology is a promising approach to revolutionize rapid diagnosis of infectious pathogens and to guide therapy that might result in the improvement of personalized medicine.

Indexed as

FemaleHerpesvirus 4, HumanHigh-Throughput Nucleotide SequencingHumansMaleViridans Streptococci

Identifiers

PMID25836606
PMCPMC4834002

What OpenQuestion holds

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Registered trials

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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.