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Record W4388164771 · doi:10.1016/s2666-7568(23)00188-5

Association of patient clinical and gut microbiota features with vancomycin-resistant enterococci environmental contamination in nursing homes: a retrospective observational study

2023· article· en· W4388164771 on OpenAlexfundaboutno aff
Joyce Wang, Betsy Foxman, Krishna Rao, Marco Cassone, Kristen E. Gibson, Lona Mody, Evan S. Snitkin

Bibliographic record

VenueThe Lancet Healthy Longevity · 2023
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsnot available
FundersNational Institute on AgingCanadian Institutes of Health ResearchUniversity of MichiganCenters for Disease Control and PreventionMichigan Institute for Clinical and Health ResearchNational Institutes of Health
KeywordsMedicineObservational studyContaminationRetrospective cohort studyEnvironmental healthInternal medicineEcologyBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Preventing transmission is crucial for reducing infections with multidrug-resistant organisms (MDROs) in nursing homes. To identify resident characteristics associated with MDRO spread, we investigated associations between patient characteristics and contamination of their proximate room surfaces with vancomycin-resistant enterococci (VRE). METHODS: In this retrospective observational study, we used demographic and clinical data (including data on comorbidities, physical independence, catheter use within the past 30 days, and antibiotic exposure within the past 30 days) and surveillance cultures of patient body sites and room surfaces at enrolment and during weekly follow-up visits within the first month, and monthly thereafter (up to 6 months), in six US nursing homes collected in a previous clinical trial (September, 2016, to August, 2018). We did 16S rRNA gene sequencing on perirectal surveillance swabs to investigate the association between the gut microbiota and the culture status of participants and their rooms. FINDINGS: We included 245 participants (mean age 72·5 years [SD 13·6]; 111 [45%] were men, 134 [55%] were women, 132 [54%] were non-Hispanic white, and 112 [46%] were African American). We collected 2802 participant samples and 5592 environmental samples. At baseline, VRE colonisation was present in 49 (20%) participants, with environmental surfaces being contaminated in 36 (73%) of these patients. Hand contamination among VRE-colonised participants was more common in those with environmental contamination compared with those without (50 [51%] of 99 vs seven [13%] of 55; p<0·0001). We found a correlation between hand contamination and both groin and perirectal colonisation and contamination of various high-touch room surfaces (Cohen's κ 0·43). We found participant microbiota composition to be associated with antibiotic receipt within the past 30 days (high-risk antibiotics p=0·011 and low-risk antibiotics p=0·0004) and participant VRE colonisation status, but not environmental contamination among VRE-colonised participants (participant only vs uncolonised p=0·071, both participant and environment vs uncolonised p=0·025, and participant only vs participant and environment p=0·29). Multivariable analysis to identify independent factors associated with VRE-colonised participants contaminating their environment identified antibiotic exposure (adjusted odds ratio 2·75 [95% CI 1·22-6·16]) and male sex (2·75 [1·24-6·08]) as being associated with increased risk of environmental contamination, and physical dependence as being associated with a reduced risk of environmental contamination (0·91 [0·83-0·99]). INTERPRETATION: Our data support antibiotic use and interaction with proximal surfaces by physically independent nursing home residents as under-appreciated drivers of environmental contamination among VRE-colonised residents. Integrating resident hand-hygiene education and antimicrobial stewardship will strengthen efforts to reduce MDROs in nursing homes. FUNDING: US Centers for Disease Control and Prevention, National Institute of Health, Canadian Institutes of Health Research, and University of Michigan.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.057
GPT teacher head0.376
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2023
Admission routes2
Has abstractyes

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