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The effect of a disinfectant/ coolant irrigant on microbes isolated from dental unit water lines

2002· article· en· W1982515980 on OpenAlexaff
Joel B. Epstein, Jenny Dawson, Ilze A. Buivids, Bea Wong, Nhu D. Le

Bibliographic record

VenueSpecial Care in Dentistry · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLegionella and Acanthamoeba research
Canadian institutionsVancouver Hospital and Health Sciences CentreUniversity of British ColumbiaBC Cancer Agency
FundersU.S. Food and Drug Administration
KeywordsDisinfectantMedicineChlorhexidineChlorhexidine gluconateDentistrySalivaAntisepticColony-forming unitSterile waterPseudomonas aeruginosaSodium hypochloriteMicrobiologyFood scienceBacteriaBiologyInternal medicineChemistry

Abstract

fetched live from OpenAlex

The purpose of this study was to assess water samples from a hospital dental clinic to determine whether a disinfectant/coolant irrigant containing chlorhexidine (Lines, Micrylium Laboratories) affects the presence of microbial organisms in dental unit waterlines. Water samples from three hospital dental operatories were collected at baseline and after overnight treatment with a disinfectant-containing irrigant followed by sterile water irrigation. Saliva of treated patients and sterile water rinse specimens were collected from the waterlines of these operatories for three consecutive days, then weekly for eight weeks after treatment. Specimens were cultured to identify total heterotrophic plate counts as well as presence of Pseudomonas aeruginosa and Candida species. Baseline organism counts varied from 10(3) to 10(5) colony-forming units per milliliter. After treatment, no organisms were detected in waterline discharge. Decontamination of dental unit waterlines is possible using a disinfectant/irrigant followed by sterile water irrigation. The potential for contamination of the lines from patients' saliva may have been reduced due to use of anti-retraction valves and the disinfectant/sterile water irrigation, as conducted in this study.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.008
GPT teacher head0.255
Teacher spread0.248 · 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 designBench or experimental
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

Citations17
Published2002
Admission routes1
Has abstractyes

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