Evidence map›Paper›PMID 39302440›Full record

ReviewArchives of microbiology2024

Phenotypic and genotypic perspectives on detection methods for bacterial antimicrobial resistance in a One Health context: research progress and prospects.

Bingbing Yang, Xiaoqi Xin, Xiaoqing Cao, Lubanga Nasifu, Zhenlin Nie, Bangshun He

Abstract readReview
PubMed Publisher
In one paragraph

Review in Archives of microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Predicting Antibiotic Resistance inInternational journal of molecular sciences · 2025
    Pooled it
  2. Article
  3. Article
  4. Uncovering antimicrobial resistance structures inFrontiers in veterinary science · 2026
    Article
  5. Article
  6. 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

6 authors.

Bingbing YangDepartment of Laboratory Medicine, Nanjing First Hospital, China Pharmaceutical University, Nanjing, 210006, China.
Xiaoqi XinDepartment of Laboratory Medicine, Nanjing First Hospital, China Pharmaceutical University, Nanjing, 210006, China.
Xiaoqing CaoDepartment of Laboratory Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, China.
Lubanga NasifuDepartment of Laboratory Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, China.
Zhenlin NieDepartment of Laboratory Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, China. zhenlinnie@126.com.ORCID http://orcid.org/0000-0002-2175-1140
Bangshun HeDepartment of Laboratory Medicine, Nanjing First Hospital, China Pharmaceutical University, Nanjing, 210006, China. bhe@njmu.edu.cn.ORCID http://orcid.org/0000-0002-4731-0167

Funding

Jiangsu Provincial Medical Key Discipline Cultivation Unit JSDW202239the research project of Jiangsu Health Development Research Center JSHD2022045
6 · The paper itself

Abstract

The widespread spread of bacterial antimicrobial resistance (AMR) and multidrug-resistant bacteria poses a significant threat to global public health. Traditional methods for detecting bacterial AMR are simple, reproducible, and intuitive, requiring long time incubation and high labor intensity. To quickly identify and detect bacterial AMR is urgent for clinical treatment to reduce mortality rate, and many new methods and technologies were required to be developed. This review summarizes the current phenotypic and genotypic detection methods for bacterial AMR. Phenotypic detection methods mainly include antimicrobial susceptibility tests, while genotypic detection methods have higher sensitivity and specificity and can detect known or even unknown drug resistance genes. However, most of the current tests are either genotypic or phenotypic and rarely combined. Combining the advantages of phenotypic and genotypic methods, combined with the joint application of multiple rapid detection methods may be the trend for future AMR testing. Driven by rapid diagnostic technology, big data analysis, and artificial intelligence, detection methods of bacterial AMR are expected to constantly develop and innovate. Adopting rational detection methods and scientific data analysis can better address the challenges of bacterial AMR and ensure human health and social well-being.

Indexed as

Anti-Bacterial AgentsBacteriaDrug Resistance, BacterialGenotypeMicrobial Sensitivity TestsOne HealthPhenotypeBacterial InfectionsDrug Resistance, Multiple, BacterialHumansAnti-Bacterial AgentsAntimicrobial resistanceGenotypic detection methodsPhenotypic detection methodsResistance testing

Identifiers

What OpenQuestion holds

Textmetadata
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.