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Record W2982144243 · doi:10.1093/ofid/ofz360.1087

1224. Factors Associated with Aerosolization of Gammaproteobacteria from Intensive Care Unit (ICU) Sinks in a Randomized Trial of Copper Alloy vs. Standard Chrome Sink Drains

2019· article· en· W2982144243 on OpenAlexaff
Cheryl Volling, Sofia Anceva-Sami, David A. Boyd, Brenda L. Coleman, Mark Downing, Susy Hota, Alainna Jamal, Jennie Johnstone, Kevin Katz, Jerome A. Leis, Angel Li, Vinaya Mahesh, Chris McLeod, Matthew Muller, Michael R. Mulvey, Sarah Nayani, Aimee Paterson, Mare Pejkovska, Daniel Ricciuto, Asfia Sultana, Tamara Vikulova, Zoë Zhong, Allison McGeer

Bibliographic record

VenueOpen Forum Infectious Diseases · 2019
Typearticle
Languageen
FieldMedicine
TopicHealthcare and Environmental Waste Management
Canadian institutionsLakeridge HealthSt. Michael's HospitalHealth Sciences CentreUniversity of TorontoUniversity Health NetworkSt Joseph's Health CentrePublic Health Agency of CanadaSunnybrook Health Science CentreNorth York General HospitalSinai Health System
Fundersnot available
KeywordsGammaproteobacteriaMedicineSink (geography)Intensive care unitInternal medicineBiologyBacteria

Abstract

fetched live from OpenAlex

Abstract Background Hospital wastewater environments are recognized as reservoirs for multi-drug-resistant bacteria, and sink drains in ICUs have been implicated in numerous outbreaks. The mechanism of pathogen transmission to patients, and the best approach to risk mitigation remains unclear. We tested a new copper alloy sink drain for its effect on detection of gammaproteobacteria in sink drains and adjacent aerosols. Methods We randomized 90 sinks in 76 ICU rooms/bedspaces in 7 ICUs to new standard chrome or copper alloy drains. We sampled sinks on 4 occasions over 4 months. Drain tailpieces were sampled using cotton swabs of 140 cm2 of the interior surface, inserted into 1mL of Dey-Engley neutralizing broth, and cultured semi-quantitatively for gammaproteobacteria on Mac3CV. 850L samples of air adjacent to sinks were obtained by impaction onto Mac3CV. Faucet swabs were also cultured. Multivariable analysis adjusting for factors associated with growth in air and drains used conditional logistic regression, GEE with an exchangeable correlation matrix, a robust estimate of variance, negative binomial distribution and log link function. Results Gammaproteobacteria were detected in 247/424 (58%) tailpiece swabs, 137/456 (30%) air samples, and 31/456 (7%) faucet swabs. In multivariable analysis, growth was less likely from air adjacent to sinks with copper vs. chrome drains [IRR 0.50 (95% CI 0.35, 0.73), P < 0.0001], with reduced effect size observed when drain growth was included in the model [IRR 0.64 (95% CI 0.43, 0.94)], P = 0.025]. Growth in air was more likely when drain growth was 1–899 cfu/cm2 [IRR 2.38 (95% CI 1.46, 3.88), P = 0.001] or ≥900 cfu/cm2 [IRR 3.55 (95% CI 1.87, 6.86), P < 0.001] vs. no growth. Tailpiece swab growth was more likely if rooms were occupied compared with empty [IRR 1.85 (95% CI 1.25, 2.76), P = 0.002], and less likely from copper drains compared with swabs from chrome drains [IRR 0.51 (95% CI 0.47, 0.75), P ≤ 0.001]. Conclusion Sinks with new copper drains are less likely to have detectable gammaproteobacteria in adjacent air when compared with standard chrome drains, and results suggest this is mediated through reduced bacterial growth in the drains. Ongoing study is needed to determine whether this influences patient risk for hospital-acquired infection. 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 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)0.000
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: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.752

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.018
GPT teacher head0.279
Teacher spread0.261 · 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 designRandomized trial
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
Published2019
Admission routes1
Has abstractyes

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