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Record W4311746724 · doi:10.1093/ofid/ofac492.1028

1193. Disinfection of the Sink Drains to Reduce a Source of <i>Serratia marcescens</i> During Infection Outbreaks in a Neonatal Intensive Care Unit

2022· article· en· W4311746724 on OpenAlexaff
Thibault Bourdin, Marie-Ève Benoit, Dominique Charron, Émilie Bédard, Michèle Prévost, Caroline Quach, Éric Déziel, Philippe Constant

Bibliographic record

VenueOpen Forum Infectious Diseases · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVibrio bacteria research studies
Canadian institutionsUniversité de MontréalPolytechnique MontréalCentre Hospitalier Universitaire Sainte-JustineInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsSerratia marcescensOutbreakMedicineSink (geography)ShowerMicrobiologyVeterinary medicineBiologyPathology

Abstract

fetched live from OpenAlex

Abstract Background Sink drains are known reservoirs of pathogens and have been associated with multiple nosocomial outbreaks. In this study, the distribution of Serratia marcescens was investigated within the sink environment of a NICU and in colonized or infected newborns. The effect of different types of drain disinfection on bacterial concentration and on the detection of Serratia marcescens in sink drains was also investigated. Methods Sink drains from a NICU were sampled: 20 drains sampled for 6 weeks in the first year and 28 drains sampled for 5 months in the second year. S. marcescens isolated from positive patients were collected. A high-throughput short sequence typing (HiSST) method was developed to identify S. marcescens and compare strains and environmental DNA from sink drains with 56 clinical strains from 5 nosocomial outbreaks. Five interventions were tested: self-disinfecting drains, hot water disinfection, chlorine disinfection, steam disinfection and hot tap water flushing. Bacterial concentration of samples was measured in culture and flow cytometry and the HiSST method was used to identify S. marcescens. Results During the first and second sampling campaigns, 40% and 60% of sink drain samples were positive for S. marcescens with a moderate genotype diversity (1 to 11 different STs). The genotype profile of the 56 clinical strains was heterogeneous (26 STs). Four distinct STs were retrieved in 8 sinks after detection in patients whereas 1 ST was detected in a sink before detection in patient. Some environmental and clinical strains were found in drains for up to a year after the first sampling campaign. Each tested drain intervention reduced culturable bacteria (4-8 log) and viable bacteria (2-3 log), except for chlorine. The self-disinfecting drains, hot water and steam disinfection were able to remove temporarily S. marcescens from the drains. Conclusion The high genotypic diversity of the clinical strains suggests diffuse sources of S. marcescens within the NICU likely to cause nosocomial infection outbreaks. The self-disinfecting drains, hot water and steam disinfection seem to be the best methods to reduce bacterial concentration in drains and eliminate S. marcescens in the short term, thus limiting the risk of pathogens spread from the sink environment to patients. Disclosures All Authors: No reported disclosures.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.010
GPT teacher head0.278
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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