ReviewNature reviews. Microbiology2026
Genome sequencing for prevention of health-care-associated bacterial infections.
Review in Nature reviews. Microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Comprehensive Phenotypic Characterization of ClinicalInternational journal of molecular sciences · 2026Article
- [Advances in integrated antimicrobial resistance diagnostics: quantitative, qualitative and AI-driven approaches].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2026Review
- Leveraging real-time genomic surveillance to combat infectious diseases and antimicrobial resistance in cancer patients.Frontiers in public health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Health-care-associated infections (HAIs) are a global threat. Microbial whole-genome sequencing (WGS) can strengthen HAI prevention strategies by enabling high-resolution detection and tracking of pathogen transmission and predicting clinically relevant phenotypic traits, such as antibiotic resistance and virulence. Although WGS continues to serve as a vital adjunct in outbreak responses, its role has evolved to include prospective pathogen surveillance and epidemiological monitoring. In this Review, we provide an overview of the epidemiology and microbiology of HAIs and highlight actionable insights gained by inclusion of WGS in HAI investigation and surveillance, with an emphasis on high-priority antibiotic-resistant bacterial pathogens. We explore the value of incorporating plasmid analysis into investigations and emphasize the importance of integrating genomic data with clinical and epidemiological metadata to support accurate transmission inferences. Critical methodological decisions are examined, including strategies for sample selection and the determination of an appropriate single nucleotide variant threshold to identify patients linked by transmission. The need for capacity building in low-and-middle-income countries, which bear a disproportionate burden of HAIs, is discussed. Together, these considerations underscore the transformative potential of WGS to inform targeted, data-driven interventions and advance global efforts to reduce the burden of HAIs.
Indexed as
Identifiers
41214237What 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.