Application of combined genomic and transfer analyses to identify factors mediating regional spread of antibiotic resistant bacterial lineages
Bibliographic record
Abstract
ABSTRACT Background Patients entering nursing facilities (NFs) are frequently colonized with antibiotic resistant organisms (AROs). To understand the determinants of ARO colonization on NF admission we applied whole-genome sequencing to track the spread of four ARO species across regional NFs and evaluated patient-level characteristics and transfer acute-care hospitals (ACHs) as risk factors for colonization. Methods 584 patients from six NFs were surveyed for methicillin-resistant Staphylococcus aureus ( MRSA), vancomycin-resistant Enterococcus faecalis / faecium (VREfc/VREfm) and ciprofloxacin-resistant Escherichia coli (CipREc) colonization. Genomic analysis was performed to quantify ARO spread between NFs and compared to patient-transfer networks. The association between admission colonization and patient-level variables and recent ACH exposures was examined using multivariable regression models. Results The majority of ARO isolates across study sites belonged to major healthcare-associated lineages: MRSA (ST5;N=89/117); VREfc (ST6;N=68/75); CipREc (ST131; N=58/64), and VREfm (clade A; N=129/129). While the genomic similarity of strains between NF pairs was associated with overlap in their feeder ACHs (Spearman’s rho=0.44-0.75, p<0.05 for MRSA, VREfc and CipREc), limited phylogenetic clustering by either ACH or NF supported regional endemicity. Significant predictors for ARO colonization on NF admission included lower functional status (adjusted odds ratio [aOR]>1 for all four AROs) and recent exposure to glycopeptides (aOR>2 for VREfm, VREfc and MRSA) or 3 rd /4 th -generation cephalosporins (aOR>2 for MRSA and VREfm). Transfer from specific ACHs was an independent risk factor for only one ARO/ACH pair (VREfm/ACH19, aOR=2.48[1.06-5.83]). Conclusion In this region, healthcare-associated ARO lineages are endemic among connected NFs and ACHs, making patient characteristics more informative of NF admission colonization risk than exposure to specific ACHs. Summary Using a combination of whole-genome sequencing, patient transfer and clinical data, we discerned the dissemination of four high-priority antibiotic-resistant organisms (ARO) in the regional healthcare network, and epidemiolocal drivers underlying the high ARO importation rate into regional nursing facilities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".