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Record W1982054336 · doi:10.1086/501835

An In-Use Evaluation of an Alcohol-Based Pre-Surgical Hand Disinfectant

2001· article· en· W1982054336 on OpenAlexaff
Elizabeth Bryce, D. Spence, Frederick J. Roberts

Bibliographic record

VenueInfection Control and Hospital Epidemiology · 2001
Typearticle
Languageen
FieldMedicine
TopicInfection Control in Healthcare
Canadian institutionsBC Cancer AgencyVancouver Hospital and Health Sciences Centre
Fundersnot available
KeywordsDisinfectantMedicineChlorhexidineAlcoholHand sanitizerSurgeryAntisepticSignificant differenceDentistryInternal medicineChemistry

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine whether alcohol hand disinfection is an effective alternative to traditional agents for the pre-surgical scrub. DESIGN: A prospective clinical trial of a 70% isopropanol pre-surgical hand disinfectant. SETTING: The operating room suites at two hospital sites in British Columbia. METHODS: Cases were selected to evaluate both short and longer procedures. The hand disinfectant was compared to agents in current use as surgical scrubs (4% chlorhexidine and 7.5% povidone-iodine). Surgical technique and glove use were not modified. Pre- and postoperative fingertip impression and "glove-juice" cultures were used to determine microbial burden, and hands were evaluated for skin integrity. RESULTS: There was no statistical difference between the microbial hand counts following use of the alcohol-based product or the current agents, for cases less than 2 hours' duration. Comparison of longer surgical cases revealed significantly better pre- and postoperative culture results with the alcohol hand rinse, but analysis of matched pairs showed no significant difference in microbial counts. The alcohol hand rinse was equivalent to the operative scrub in terms of skin integrity and user acceptability. CONCLUSION: An alcohol hand rinse was equivalently effective in reducing microbial hand counts as the traditional pre-surgical scrub, both immediately after hand disinfection and at the end of the surgical procedure.

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)0.005
metaresearch head score (Gemma)0.004
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 score0.254
Threshold uncertainty score0.836

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
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 head0.063
GPT teacher head0.407
Teacher spread0.344 · 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

Citations48
Published2001
Admission routes1
Has abstractyes

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