An In-Use Evaluation of an Alcohol-Based Pre-Surgical Hand Disinfectant
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".