Trends in oral antibiotic treatment in patients hospitalized with diabetic foot osteomyelitis: A single-centre experience
Bibliographic record
Abstract
Background: The Oral Versus Intravenous Antibiotics for Bone and Joint Infection (OVIVA) trial demonstrated the efficacy of highly bioavailable oral antibiotic therapy for the treatment of osteoarticular infections. However, there continues to be significant variability in practice. This study aimed to assess changes in oral antibiotic use in the treatment of diabetic foot osteomyelitis (DFO) at a large academic hospital. Methods: We conducted a retrospective cohort study of adult patients admitted to Sunnybrook Health Sciences Centre from January 1, 2016, to December 31, 2022, with a diagnosis of DFO. The primary outcome was the proportion of patients who received definitive oral antibiotic treatment during two timeframes (Pre-OVIVA publication: January 1, 2016, through February 28, 2019, and post-OVIVA publication: March 1, 2019, to December 31, 2022). Patients were excluded if they had another indication for long-term intravenous antibiotics, if they did not receive antibiotic treatment for osteomyelitis, or if they underwent amputation without the need for postoperative antibiotics. Results: A total of 145 patients were included in the analysis. (65 patients pre-OVIVA and 80 patients post-OVIVA). The majority of patients had a history of peripheral arterial disease (59%) and gangrene (66%) present on hospital admission. Use of definitive oral antibiotic therapy increased from 10.8% in the pre-OVIVA period to 21.2% in the post-OVIVA period ( p = 0.14). Conclusions: There was a trend toward increased definitive oral antibiotic therapy for DFO, but overall use remained low. Further studies are needed to explore the factors influencing the selection of oral antibiotic therapy in this population.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".