Management of contaminated open fractures
Bibliographic record
Abstract
BACKGROUND: Treatment of open fractures demands rapid intervention consisting of intravenous antibiotics, aggressive debridement, fracture immobilization, and soft tissue management including additional debridements and soft tissue coverage. Despite this approach, infection, particularly osteomyelitis, after open fracture continues to be a source of significant morbidity. Recent literature has provided several studies that performed clinical trials in superficial wounds. These investigations compared sterile solutions with tap water for wound decontamination. The results suggest that tap water washouts are cost-effective for these specific wounds. MATERIAL: An established protocol using sterile porcine hind limb tibias, as reported by Bhandari et al., was applied with modification. There were then 15 specimens and 5 controls (no irrigation) for each condition. The conditions were potable water and sterile water. A representative bacterium of gram-positive, Staphylococcus aureus, or gram-negative, Escherichia coli, acted as the contaminant. Sectioned, sterile porcine hind limb tibias were inoculated with 1 mL of a known concentration (1 × 10(10)) of bacterium and incubated. Each specimen was then irrigated, with bulb irrigation at a standardized distance of 15 cm, with 500 mL of irrigation. The specimen, along with 0.5 mL of wash (irrigant collected after it was placed over the specimen), was placed in 5 mL of Brain Heart Infusion broth. All specimens were incubated in this broth at 37°C for 2 hours. At 2 hours, a 100-μL supernatant was plated on blood agar plates and incubated for 24 hours. Colony counts for each specimen and controls were then performed. RESULTS: The number of colony forming units (CFUs) for each type of bacterium was different. The average CFUs from bone samples contaminated with E. coli was 5.18 × 10(8) after irrigation with sterile water and 6.24 × 10(8) after irrigation with tap water. The average CFUs from bone samples contaminated with S. aureus was 18 × 10(6) after irrigation with sterile water and 12 × 10(6) after irrigation with tap water. The average CFUs from the irrigation samples from E. coli contamination treated with sterile water was 1.3 × 10(6) and the CFUs from E. coli contamination treated with tap water was 2.2 × 10(6). The average CFUs from the irrigation samples from S. aureus contamination treated with sterile water was 1.57 × 10(6) and the CFUs from S. aureus contamination treated with tap water was 1.56 × 10(6). CONCLUSION: There was no significant difference between the CFUs for the sterile and potable water (p = 0.201) for each bacterium (p = 0.871).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".