Evidence map›Paper›PMID 37078855›Full record

ArticleMicrobiology spectrum2023

Epidemiological and Genetic Characteristics of Clinical Carbapenem-Resistant

Yonggang Zhao, Dingqiang Chen, Kaichao Chen, Miaomiao Xie, Jiubiao Guo, Edward Wai Chi Chan, Lu Xie, Jingbo Wang, Enqi Chen, Sheng Chen and 2 more

Open access · goldAbstract read
In one paragraph

Article in Microbiology spectrum, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 11% 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Carbapenem-resistant bacteria in the environment.Arhiv za higijenu rada i toksikologiju · 2025
    Review
  8. Article
  9. Article
  10. Antimicrobial agents and chemotherapy · 2024
    Article
  11. Article
  12. Article
  13. Molecular Epidemiology ofAntibiotics (Basel, Switzerland) · 2024
    Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. 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

12 authors at 6 institutions in 3 countries.

Yonggang Zhao *Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby, Denmark.
Dingqiang Chen *Microbiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, People's Republic of China.
Kaichao Chen *Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, People's Republic of China.
Miaomiao XieDepartment of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, People's Republic of China.ORCID 0000-0002-6408-2995
Jiubiao GuoCollege of Pharmacy-Shenzhen Technology University, Shenzhen, People's Republic of China.
Edward Wai Chi ChanDepartment of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, People's Republic of China.
Lu XieResearch Center for Micro-Ecological Agent Engineering and Technology of Guangdong Province, Guangzhou, People's Republic of China.
Jingbo WangCollege of Pharmacy-Shenzhen Technology University, Shenzhen, People's Republic of China.
Enqi ChenCollege of Pharmacy-Shenzhen Technology University, Shenzhen, People's Republic of China.
Sheng ChenDepartment of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, People's Republic of China.ORCID 0000-0003-3526-7808
Weijun ChenBGI-Shenzhen, Shenzhen, People's Republic of China.
Lars JelsbakDepartment of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby, Denmark.ORCID 0000-0002-5759-9769
City University of Hong Kong · HKShenzhen Technology University · CNTechnical University of Denmark · DKBGI Group (China) · CNKey Laboratory of Guangdong Province · CNZhujiang Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Carbapenem-resistant Pseudomonas aeruginosa (CRPA) is a bacterial pathogen that may cause serious drug-resistant infections that are potentially fatal. To investigate the genetic characteristics of these organisms, we tested 416 P. aeruginosa strains recovered from 12 types of clinical samples collected in 29 different hospital wards in 10 hospitals in Guangdong Province, China, from 2017 to 2020. These strains were found to belong to 149 known sequence types (STs) and 72 novel STs, indicating that transmission of these strains involved multiple routes. A high rate of resistance to imipenem (89.4%) and meropenem (79.4%) and a high prevalence of pathogenic serotypes (76.4%) were observed among these strains. Six STs of global high-risk clones (HiRiCs) and a novel HiRiC strains, ST1971, which exhibited extensive drug resistance, were identified. Importantly, ST1971 HiRiC, which was unique in China, also exhibited high virulence, which alarmed the further surveillance on this highly virulent and highly resistant clone. Inactivation of the

Indexed as

Anti-Bacterial AgentsPseudomonas Infectionsbeta-LactamasesCarbapenemsHumansImipenemMeropenemMicrobial Sensitivity TestsPseudomonas aeruginosaAnti-Bacterial Agentsbeta-LactamasesCarbapenemsImipenemMeropenemcarbapenem resistanceefflux-pump-encoding genesmolecular epidemiologyoprDPseudomonas aeruginosa

Identifiers

PMID37078855
PMCPMC10269565
OpenAlexW4366463449

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.