Evidence map›Paper›PMID 42802859›Full record

ArticleInfection and drug resistance2026

Extensively Drug-Resistant ST16

Yao Li, Haijun Li, Xiaohong Xu, Jilei Ma, Hongmei Wang, Shijun Sun, Wanhai Wang

Abstract read
In one paragraph

Article in Infection and drug resistance, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Yao Li *Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People's Republic of China.ORCID 0000-0002-8185-2138
Haijun Li *Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
Xiaohong XuSchool of Basic Medical Sciences, Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
Jilei MaDepartment of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
Hongmei WangDepartment of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
Shijun SunDepartment of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
Wanhai WangDepartment of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Carbapenem-resistant Methods: A CRKP isolate, designated KPY1, was recovered from the bloodstream of an intensive care unit patient. Antimicrobial susceptibility testing was performed to determine the resistance phenotype. Whole-genome sequencing was conducted using a hybrid Illumina-Nanopore approach. Genome assembly, antimicrobial resistance gene detection, plasmid replicon typing, comparative plasmid analysis, and genetic environment analysis of carbapenemase genes were performed using established bioinformatic tools. Results: KPY1 belonged to sequence type 16 and exhibited an extensively drug-resistant phenotype, including resistance to carbapenems, β-lactam/β-lactamase inhibitor combinations, ceftazidime-avibactam, and colistin. Genomic analysis revealed the coexistence of three carbapenemase genes: Conclusion: This study describes a rare and clinically challenging ST16 CRKP bloodstream isolate co-harboring class A, B, and D carbapenemases. The chromosomal integration of

Indexed as

antimicrobial resistancecarbapenem resistanceIS26plasmidwhole-genome sequencing

Identifiers

PMID42802859
PMCPMC13616171

What OpenQuestion holds

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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.