| 1. |
- Chng, Kern Rei, et al.
(författare)
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Cartography of opportunistic pathogens and antibiotic resistance genes in a tertiary hospital environment
- 2020
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Ingår i: Nature Medicine. - : Springer Science and Business Media LLC. - 1078-8956 .- 1546-170X. ; 26, s. 941-951
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Tidskriftsartikel (refereegranskat)abstract
- Although disinfection is key to infection control, the colonization patterns and resistomes of hospital-environment microbes remain underexplored. We report the first extensive genomic characterization of microbiomes, pathogens and antibiotic resistance cassettes in a tertiary-care hospital, from repeated sampling (up to 1.5 years apart) of 179 sites associated with 45 beds. Deep shotgun metagenomics unveiled distinct ecological niches of microbes and antibiotic resistance genes characterized by biofilm-forming and human-microbiome-influenced environments with corresponding patterns of spatiotemporal divergence. Quasi-metagenomics with nanopore sequencing provided thousands of high-contiguity genomes, phage and plasmid sequences (>60% novel), enabling characterization of resistome and mobilome diversity and dynamic architectures in hospital environments. Phylogenetics identified multidrug-resistant strains as being widely distributed and stably colonizing across sites. Comparisons with clinical isolates indicated that such microbes can persist in hospitals for extended periods (>8 years), to opportunistically infect patients. These findings highlight the importance of characterizing antibiotic resistance reservoirs in hospitals and establish the feasibility of systematic surveys to target resources for preventing infections. Spatiotemporal characterization of microbial diversity and antibiotic resistance in a tertiary-care hospital reveals broad distribution and persistence of antibiotic-resistant organisms that could cause opportunistic infections in a healthcare setting.
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| 2. |
- Danko, David, et al.
(författare)
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A global metagenomic map of urban microbiomes and antimicrobial resistance
- 2021
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Ingår i: Cell. - : Elsevier BV. - 0092-8674 .- 1097-4172. ; 184:13, s. 3376-3393
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Tidskriftsartikel (refereegranskat)abstract
- We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.
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| 3. |
- Ho, Peh Joo, et al.
(författare)
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Comparison of self-reported and register-based hospital medical data on comorbidities in women
- 2019
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Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 9:1
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Tidskriftsartikel (refereegranskat)abstract
- Breast cancer patients commonly present with comorbidities which are known to influence treatment decisions and survival. We aim to examine agreement between self-reported and register-based medical records (National Patient Register [NPR]). Ascertainment of nine conditions, using individually-linked data from 64,961 women enrolled in the Swedish KARolinska MAmmography Project for Risk Prediction of Breast Cancer (KARMA) study. Agreement was assessed using observed proportion of agreement (overall agreement), expected proportion of agreement, and Cohen's Kappa statistic. Two-stage logistic regression models taking into account chance agreement were used to identify potential predictors of overall agreement. High levels of overall agreement (i.e. ≥86.6%) were observed for all conditions. Substantial agreement (Cohen's Kappa) was observed for myocardial infarction (0.74), diabetes (0.71) and stroke (0.64) between self-reported and NPR data. Moderate agreement was observed for preeclampsia (0.51) and hypertension (0.46). Fair agreement was observed for heart failure (0.40) and polycystic ovaries or ovarian cysts (0.27). For hyperlipidemia (0.14) and angina (0.10), slight agreement was observed. In most subgroups we observed negative specific agreement of >90%. There is no clear reference data source for ascertainment of conditions. Negative specific agreement between NPR and self-reported data is consistently high across all conditions.
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