Influence of orthopedic reinforced gloves versus double standard gloves on contamination events during small animal orthopedic surgery
Bibliographic record
Abstract
OBJECTIVE: To determine the influence of orthopedic reinforced gloves on contamination events during small animal orthopedic surgery. STUDY DESIGN: Prospective randomized controlled trial SAMPLE POPULATION: Two hundred and thirty-seven pairs of orthopedic gloves (474 gloves) and 203 pairs of double standard gloves (812 gloves) worn during 193 orthopedic procedures. METHODS: Primary and assistant surgeons were randomized to wear either orthopedic reinforced gloves or double gloves. Gloves were leak tested to identify perforations at the end of procedures. Perforations detected intraoperatively or postoperatively were recorded. A contamination event was defined as at least one perforation on either hand for orthopedic reinforced gloves, or a perforation of both the inner and outer glove on the same hand for double gloves. RESULTS: Baseline characteristics between the 2 intervention groups were similar. There was no difference in contamination events between the double-gloved and orthopedic gloved groups (OR = 0.95, 95% CI = 0.49-1.87, P = .89). The same percentage of contamination events (8% glove pairs used) occurred in the double gloved group (17 contamination events) and in the orthopedic gloved group (19 contamination events). The odds of a contamination event increased by 1.02 (95% CI 1.01-1.03, P < .001) with each additional minute of surgery. CONCLUSION: Orthopedic reinforced gloves and double standard gloving were equally effective at preventing contamination events in small animal orthopedic procedures. CLINICAL RELEVANCE: Surgeons reluctant to double glove due to perceptions of decreased dexterity and discomfort may safely opt for wearing orthopedic gloves, which may improve their compliance.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".