Evidence map›Paper›PMID 36882683›Full record

ArticleBMC microbiology2023

Clonal transmission of polymyxin B-resistant hypervirulent Klebsiella pneumoniae isolates coharboring bla

Mengli Tang, Jun Li, Zhaojun Liu, Fengjun Xia, Changhang Min, Yongmei Hu, Haichen Wang, Mingxiang Zou

Open access · goldAbstract read
In one paragraph

Article in BMC microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Epidemiological and characteristic differences of hypervirulent and classicalFrontiers in cellular and infection microbiology · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Microbiology spectrum · 2024
    Article
  13. Article
  14. HypervirulentInfection and drug resistance · 2023
    Review
  15. Characterisation of a Novel Hybrid IncFIIInfection and drug resistance · 2023
    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

8 authors at 1 institution in 1 country.

Mengli Tang *Department of Clinical Laboratory, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu district, Changsha, Hunan, China.
Jun Li *Department of Clinical Laboratory, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu district, Changsha, Hunan, China.
Zhaojun LiuDepartment of Clinical Laboratory, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu district, Changsha, Hunan, China.
Fengjun XiaDepartment of Clinical Laboratory, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu district, Changsha, Hunan, China.
Changhang MinDepartment of Clinical Laboratory, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu district, Changsha, Hunan, China.
Yongmei HuDepartment of Clinical Laboratory, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu district, Changsha, Hunan, China.
Haichen WangDepartment of Clinical Laboratory, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu district, Changsha, Hunan, China.
Mingxiang ZouDepartment of Clinical Laboratory, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu district, Changsha, Hunan, China. zoumingxiang@csu.edu.cn.
Central South University · CN

Funding

Fundamental Research Funds for the Central Universities of Central South University under Grant 2021zzts1043National Natural Science Foundation of China 81702068Natural Science Foundation of Hunan Province under Grant 2020JJ4886Natural Science Foundation of Hunan Province under Grant 2022JJ70084Science Foundation of Hunan Health Commission in Hunan Province under Grant 202111000066
6 · The paper itself

Abstract

backgroundThe prevalence of multidrug-resistant hypervirulent K. pneumoniae (MDR-hvKP) has gradually increased. It poses a severe threat to human health. However, polymyxin-resistant hvKP is rare. Here, we collected eight polymyxin B-resistant K. pneumoniae isolates from a Chinese teaching hospital as a suspected outbreak.

resultsThe minimum inhibitory concentrations (MICs) were determined by the broth microdilution method. HvKP was identified by detecting virulence-related genes and using a Galleria mellonella infection model. Their resistance to serum, growth, biofilm formation, and plasmid conjugation were analyzed in this study. Molecular characteristics were analyzed using whole-genome sequencing (WGS) and mutations of chromosome-mediated two-component systems pmrAB and phoPQ, and the negative phoPQ regulator mgrB to cause polymyxin B (PB) resistance were screened. All isolates were resistant to polymyxin B and sensitive to tigecycline; four were resistant to ceftazidime/avibactam. Except for KP16 (a newly discovered ST5254), all were of the K64 capsular serotype and belonged to ST11. Four strains co-harbored bla

conclusionsPolymyxin-resistant hvKP has become an essential new superbug prevalent in China, posing a serious challenge to public health. Its epidemic transmission characteristics and mechanisms of resistance and virulence deserve attention.

Indexed as

Drug Resistance, Multiple, BacterialKlebsiella InfectionsKlebsiella pneumoniaePolymyxin Bbeta-LactamasesChinaDisease OutbreaksHumansTertiary Care Centersbeta-lactamase NDM-1beta-LactamasesPolymyxin BClonal transmissionHypervirulenceKlebsiella pneumoniaePolymyxin BST11-K64Whole-genome sequencing

Identifiers

PMID36882683
PMCPMC9990273
OpenAlexW4323361229

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.