ArticlePloS one2020
Comparison of de-duplication methods used by WHO Global Antimicrobial Resistance Surveillance System (GLASS) and Japan Nosocomial Infections Surveillance (JANIS) in the surveillance of antimicrobial resistance.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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
14 citing papers in PubMed.
- Emergence of antimicrobial resistance in New Caledonia: 20-year trends from laboratory-based surveillance (2005-2024).The Lancet regional health. Western Pacific · 2026Article
- Drug-Resistant Infections in Burn Patients: A One-Year Analysis of Microbiological Trends and Predictive Risk Factors in a Romanian Tertiary Care Centre.Antibiotics (Basel, Switzerland) · 2026Article
- Mapping antimicrobial resistance and healthcare-associated infections indicators for actionable benchmarking: a cross-network overview in a data-driven era.Antimicrobial resistance and infection control · 2025Review
- Ecological and public health dimensions of ESBL-producingVeterinary world · 2025Review
- Staphylococcus aureus Tetracycline Resistance and Co-resistance in a Doxycycline Postexposure Prophylaxis-Eligible Population.The Journal of infectious diseases · 2025Article
- Implications of deduplication on the detection rates of multidrug-resistant organism (MDRO) in various specimens: insights from the hospital infection surveillance program.Antimicrobial resistance and infection control · 2024Article
- Distribution, Trends, and Antimicrobial Susceptibility ofOpen forum infectious diseases · 2023Article
- Distribution, trends, and antifungal susceptibility of Candida species causing candidemia in Japan, 2010-2019: A retrospective observational study based on national surveillance data.Medical mycology · 2022Observational
- The rising dominance of microbiology: what to expect in the next 15 years?Microbial biotechnology · 2022Article
- Impact of the COVID-19 pandemic on the surveillance of antimicrobial resistance.The Journal of hospital infection · 2021Article
- Quality Assessment of an Antimicrobial Resistance Surveillance System in a Province of Nepal.Tropical medicine and infectious disease · 2021Article
- Smaller Copper Oxide Nanoparticles have More Biological Effects Versus Breast Cancer and Nosocomial Infections Bacteria.Asian Pacific journal of cancer prevention : APJCP · 2021Article
- Antibiotic Susceptibility and Molecular Characterization of UropathogenicTropical medicine and infectious disease · 2020Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
A major issue in the surveillance of antimicrobial resistance (AMR) is "de-duplication" or removal of repeated isolates, for which there exist multiple methods. The World Health Organization (WHO) Global Antimicrobial Resistance Surveillance System (GLASS) requires de-duplication by selecting only the first isolate of a given bacterial species per patient per surveillance period per specimen type per age group, gender, and infection origin stratification. However, no study on the comparative application of this method has been reported. The objective of this study was to evaluate differences in data tabulation between the WHO GLASS and the Japan Nosocomial Infections Surveillance (JANIS) system, which counts both patients and isolates after removing repeated isolates of the same bacterial species isolated from a patient within 30 days, regardless of specimen type, but distinguishing isolates with change of antimicrobial resistance phenotype. All bacterial data, consisting of approximately 8 million samples from 1795 Japanese hospitals in 2017 were exported from the JANIS database, and were tabulated using either the de-duplication algorithm of GLASS, or JANIS. We compared the tabulated results of the total number of patients whose blood and urine cultures were taken and of the percentage of resistant isolates of Escherichia coli for each priority antibiotic. The number of patients per specimen type tabulated by the JANIS method was always smaller than that of GLASS. There was a small (< 3%) difference in the percentage of resistance of E. coli for any antibiotic between the two methods in both out- and inpatient settings and blood and urine isolates. The two tabulation methods did not show considerable differences in terms of the tabulated percentages of resistance for E. coli. We further discuss how the use of GLASS tabulations to create a public software and website that could help to facilitate the understanding of and treatment against AMR.
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.