Evidence map›Paper›PMID 39135637›Full record

ArticleFrontiers in cellular and infection microbiology2024

Standardization of an antimicrobial resistance surveillance network through data management.

Hyunji Kim, Jeong Su Park, Dokyun Kim, Hee Jung Kim, Jeong Hwan Shin, Young Ah Kim, Young Uh, Soo Hyun Kim, Jong Hee Shin, Seok Hoon Jeong and 1 more

Abstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

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

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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

11 authors.

Hyunji Kim *Department of Laboratory Medicine, Seoul National University Bundang Hospital and Seoul National University College of Medicine, Seoul, Republic of Korea.
Jeong Su Park *Department of Laboratory Medicine, Seoul National University Bundang Hospital and Seoul National University College of Medicine, Seoul, Republic of Korea.
Dokyun KimDepartment of Laboratory Medicine and Research Institute of Bacterial Resistance, Yonsei University College of Medicine, Seoul, Republic of Korea.
Hee Jung KimDepartment of Laboratory Medicine and Research Institute of Bacterial Resistance, Yonsei University College of Medicine, Seoul, Republic of Korea.
Jeong Hwan ShinDepartment of Laboratory Medicine and Paik Institute for Clinical Research, Inje University College of Medicine, Busan, Republic of Korea.
Young Ah KimDepartment of Laboratory Medicine, National Health Insurance Service Ilsan Hospital, Goyang, Republic of Korea.
Young UhDepartment of Laboratory Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea.
Soo Hyun KimDepartment of Laboratory Medicine, Chonnam National University Medical School, Gwangju, Republic of Korea.
Jong Hee ShinDepartment of Laboratory Medicine, Chonnam National University Medical School, Gwangju, Republic of Korea.
Seok Hoon JeongDepartment of Laboratory Medicine and Research Institute of Bacterial Resistance, Yonsei University College of Medicine, Seoul, Republic of Korea.
Kyoung Un ParkDepartment of Laboratory Medicine, Seoul National University Bundang Hospital and Seoul National University College of Medicine, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The rapid spread of COVID-19 worldwide within 2 months demonstrated the vulnerability of the world's population to infectious diseases. In 2015, the Global Antimicrobial Resistance and Use Surveillance System (GLASS) was launched to combat antimicrobial resistance (AMR). However, there has been no comprehensive assessment of the decade-long global battle against AMR based on GLASS data. Methods: South Korea established Kor-GLASS (Korean-GLASS) to proactively monitor data quality and enable international collaborations. A unique feature of Kor-GLASS is the quality control center (QCC), which uses network hubs and ensures standardized, high-quality data through interlaboratory proficiency testing (IPT) and external quality assessment (EQA). In addition, the QCC multifaceted endeavors for integrated data quality management. Results: Since 2020, high-quality AMR data have indicated fluctuating antibiotic resistance rates in South Korea. This trend does not align with the decrease in antibiotic usage seen in humans but coincides with non-human antibiotic sales, indicating a need for greater monitoring of non-human antibiotic resistance. Comprehensive and robust management taking account of the intricate interplay among humans, animals, and the environment is essential. Kor-GLASS has been expanded into a "One Health" multiagency collaborative initiative. Discussion: Although a standardized solution is not suitable for all countries, it must align with the local context and international standards. A centralized top-down management structure such as that of the QCC is essential to ensure continuous data quality coordination. Sustained efforts and surveillance systems are crucial for monitoring and managing AMR and safeguarding human health.

Indexed as

COVID-19Anti-Bacterial AgentsData ManagementDrug Resistance, BacterialDrug Resistance, MicrobialEpidemiological MonitoringHumansQuality ControlRepublic of KoreaSARS-CoV-2Anti-Bacterial Agentsantimicrobial resistanceEQAIPTKor-GLASSquality control center

Identifiers

PMID39135637
PMCPMC11317371

What OpenQuestion holds

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LicenceCC BY
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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.