Bibliographic record
Abstract
PURPOSE: Various antibiotics are available to treat soft-tissue infections. However, it is unclear if the empirical antibiotic is always appropriate or the most economical. OBJECTIVE: To determine the percentage of empirically treated wounds susceptible to the antibiotic therapy prescribed, and to determine the percentage of wounds treated with the most economical antibiotic therapy. METHODS: A retrospective chart review was performed on all charts with a diagnosis of 'soft-tissue infection' between January 1, 2005, and June 30, 2005, at St Joseph's Hospital, Hamilton, Ontario. Eligible charts were identified using the medical diagnosis coding system. The following diagnoses (including subheadings) were included: cellulitis, lymphangitis, abscess, carbuncle or furuncle. The following was extracted: patient demographics; soft-tissue diagnosis; name, dose and duration of antibiotics used; culture results; and Gram-stain results. A comparison between the empirical antibiotic prescribed and the microbiology result was made. An assessment was performed on the cost of the initial empirical antibiotic treatment compared with less-expensive effective alternatives. RESULTS: For soft-tissue infections with positive culture growth, empirical antibiotic treatment was appropriate in all abscess cases, 50% of ulcer cases and 83% of cellulitis cases. For cellulitis patients receiving a single empirical antibiotic, it was appropriate in 89% of cases. Only 42% of culture-positive patients were treated with the most economical regimen, multiple antibiotics being the most common fault. CONCLUSIONS: To be most economical, a single empirical antibiotic should be used to treat cellulitis. Culture results should be used to guide any antibiotic changes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".