ArticleBMC microbiology2023
Molecular characteristics of carbapenem-resistant gram-negative bacilli in pediatric patients in China.
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 3 papers.
What it found
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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.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Comparative evaluation of tigecycline susceptibility testing methods for carbapenem-resistant Klebsiella pneumoniae and Acinetobacter baumannii.Annals of clinical microbiology and antimicrobials · 2026Article
- Article
- ESKAPE in China: epidemiology and characteristics of antibiotic resistance.Emerging microbes & infections · 2024Review
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCarbapenem-resistant gram-negative bacilli (CR-GNB) have been increasingly reported in China. However, dynamic monitoring data on molecular epidemiology of CR-GNB are limited in pediatric patients.
results300 CR-GNB isolates (200 Carbapenem-resistant K. pneumoniae (CRKP), 50 carbapenem-resistant A.baumannii (CRAB) and 50 carbapenem-resistant P. aeruginosa (CRPA)) were investigated. The predominant carbapenemase gene was bla
conclusionCRKP showed different molecular phenotypes in neonates and non-neonates and was changing dynamically and high-risk clone of ST11 KPC-KP should be paid more attention. Most CRKP and CRAB strains shared the same CCs, suggesting that intrahospital transmission may occur, and large-scale screening and more effective measures are urgently needed.
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Registered trials
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.