Evidence map›Paper›PMID 38216600›Full record

ArticleScientific reports2024

Novel rapid method for identifying and quantifying pathogenic bacteria within four hours of blood collection.

Akio Miyakoshi, Hideki Niimi, Tomohiro Ueno, Masahiro Wakasugi, Yoshitsugu Higashi, Yuki Miyajima, Masashi Mori, Homare Tabata, Hiroshi Minami, Akinori Takaoka and 3 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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
–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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
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.

Akio Miyakoshi *Department of Ophthalmology, Toyama University Hospital, Toyama, Japan.
Hideki Niimi *Clinical Laboratory Center, Toyama University Hospital, 2630 Sugitani, Toyama, 930-0194, Japan. hiniimi@med.u-toyama.ac.jp.
Tomohiro UenoClinical Laboratory Center, Toyama University Hospital, 2630 Sugitani, Toyama, 930-0194, Japan.
Masahiro WakasugiDisaster and Emergency Center, Toyama University Hospital, Toyama, Japan.
Yoshitsugu HigashiDepartment of Clinical Infectious Diseases, Toyama University Hospital, Toyama, Japan.
Yuki MiyajimaDepartment of Clinical Infectious Diseases, Toyama University Hospital, Toyama, Japan.
Masashi MoriResearch Institute for Bioresources and Biotechnology, Ishikawa Prefectural University, Nonoichi, Japan.
Homare TabataLife Science Center, Hokkaido Mitsui Chemicals, Inc., Sunagawa, Japan.
Hiroshi MinamiLife Science Center, Hokkaido Mitsui Chemicals, Inc., Sunagawa, Japan.
Akinori TakaokaInstitute for Genetic Medicine, Hokkaido University, Sapporo, Japan.
Atsushi HayashiDepartment of Ophthalmology, Toyama University Hospital, Toyama, Japan.
Yoshihiro YamamotoDepartment of Clinical Infectious Diseases, Toyama University Hospital, Toyama, Japan.
Isao KitajimaAdministrative Office, University of Toyama, Toyama, Japan.

Funding

Japan Agency for Medical Research and Development JP19im0210217Japan Society for the Promotion of Science 18H02728Japan Society for the Promotion of Science 21H02825
6 · The paper itself

Abstract

Sepsis is life-threatening organ dysfunction and is considered a major cause of health loss. However, since the current biomarkers of sepsis reflect the host's immune response to microorganisms, they would inevitably cause a time-lag. This means that there is still no truly reliable biomarker of sepsis. In the present study, we developed a novel method for identifying and quantifying unknown pathogenic bacteria within four hours of sample collection. The most important point of this study is that the novel method can be used to determine the number of bacteria in a sample as a novel biomarker of infectious diseases. Indeed, based on the number of bacteria, we were able to accurately estimate the severity of microbial infection. Furthermore, using the time-dependent changes in the number of bacteria, we were able to monitor the therapeutic effect accurately. The rapid identification and quantification of bacteria may change our approach to medical care.

Indexed as

BacteriaSepsisBiomarkersHumansBiomarkers

Identifiers

PMID38216600
PMCPMC10786899

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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.