ArticleFrontiers in cellular and infection microbiology2024
Standardization of an antimicrobial resistance surveillance network through data management.
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.
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.
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.
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Insights into Haemophilus macrolide resistance: A comprehensive systematic review and meta-analysis.PLoS neglected tropical diseases · 2025Pooled it
- ESKAPE Pathogens in a Hungarian Emergency Department: A 5-Year Retrospective Observational Study of Prevalence and Resistance Patterns Utilizing the AWaRe Framework.Antibiotics (Basel, Switzerland) · 2026Article
- Antimicrobial Resistance as a Global Public Health Challenge: Epidemiological Burden, Bioethical Dimensions and Emerging Therapeutic Strategies.Infectious disease reports · 2026Review
- Artificial intelligence for antimicrobial resistance: advancing reproducibility, interpretability, and clinical deployment.Briefings in bioinformatics · 2026Review
- Application of Long-Read Whole-Genome Sequencing to Clarify Genotypic-Phenotypic Discrepancies in Methicillin-ResistantDiagnostics (Basel, Switzerland) · 2026Article
- The dual role of azoles: lifesaving antifungals and drivers of resistance - a One Health perspective.Nature communications · 2026Review
- Performance of a quality control center supporting national antimicrobial resistance surveillance.British journal of biomedical science · 2026Article
- Antimicrobial peptides in the era of resistance: integrating AI-driven design, host-microbe interactions, and nanotechnological delivery.Frontiers in microbiology · 2026Review
- A Decade of Achievements and Future Directions in Global Antimicrobial Resistance Surveillance System in Korea (Kor-GLASS).Public health weekly report · 2026Article
- Molecular Epidemiology of Extended-spectrum β-Lactamase-producingAnnals of laboratory medicine · 2026Article
- Preventive Immunology for Livestock and Zoonotic Infectious Diseases in the One Health Era: From Mechanistic Insights to Innovative Interventions.Veterinary sciences · 2025Review
- Comparative Performance Evaluation of Continuous Monitoring Blood Culture Systems Using Simulated Septic Specimen.Diagnostics (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
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
Identifiers
What OpenQuestion holds
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.