Cartilage on the floor: how effective is antibiotic sterilization?
Bibliographic record
Abstract
OBJECTIVE: To determine the incidence of positive cultures from contaminated nasal cartilage and to demonstrate the effectiveness of antibiotic irrigation as a means of sterilization. DESIGN: A prospective study. SETTING: Tertiary referral centre. METHODS: Nasal septal cartilage was harvested during routine endoscopic septoplasties. The harvested cartilage was then dropped on the floor for 60 seconds. The cartilage was then divided into four equal portions, which were then divided into four experimental groups: (1) untreated, (2) normal saline soak for 60 seconds, (3) 40 mg/mL gentamicin solution soak for 60 seconds, and (4) 300 seconds. All specimens were sent for bacterial culture and sensitivity, along with nasal swabs and floor swabs. The incidence of bacterial contamination in the different groups was analyzed using the McNemar hypothesis. MAIN OUTCOME MEASURES: Correlation between bacterial culture results and treatments of contaminated nasal septal cartilages. RESULTS: Thirty-two patients were enrolled in this study. Thirty-one percent of the untreated specimens had bacterial contamination. Thirty-one percent of the saline-soaked specimens had significant bacterial growth. Bacterial growth was not observed in any of the specimens treated with gentamicin irrigation for 60 seconds (absolute reduction of 31%); one specimen (3%) in the 300 seconds gentamicin group had a positive culture. A correlation of 70% was observed in the bacterial growth observed in the swab of the operating room floor and the untreated cartilage. CONCLUSIONS: When no other options are available, this study demonstrates that cartilage dropped on the floor can be decontaminated by washing with gentamicin.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".