Interventions in the management of infection in the foot in diabetes: a systematic review
Bibliographic record
Abstract
The expert panel on diabetic foot infection (DFI) of the International Working Group on the Diabetic Foot conducted a systematic review seeking all published reports relating to any type of treatment for infection of the foot in persons with diabetes published as of 30 June 2014. This review, conducted with both PubMed and EMBASE, was used to update an earlier one undertaken on 30 June 2010 using the same search string. Eligible publications included those that had outcome measures reported for both a treated and a control population that were managed either at the same time, or as part of a before-and-after case design. We did not include studies that contained only information related to definition or diagnosis, but not treatment, of DFI. The current search identified just seven new articles meeting our criteria that were published since the 33 identified with the previous search, making a total of 40 articles from the world literature. The identified articles included 37 randomised controlled trials (RCTs) and three cohort studies with concurrent controls, and included studies on the use of surgical procedures, topical antiseptics, negative pressure wound therapy and hyperbaric oxygen. Among the studies were 15 RCTs that compared outcomes of treatment with new antibiotic preparations compared with a conventional therapy in the management of skin and soft tissue infection. In addition, 10 RCTs and 1 cohort study compared different treatments for osteomyelitis in the diabetic foot. Results of comparisons of different antibiotic regimens generally demonstrated that newly introduced antibiotic regimens appeared to be as effective as conventional therapy (and also more cost-effective in one study), but one study failed to demonstrate non-inferiority of a new antibiotic compared with that of a standard agent. Overall, the available literature was both limited in both the number of studies and the quality of their design. Thus, our systematic review revealed little evidence upon which to make recommendations for treatment of DFIs. There is a great need for further well-designed trials that will provide robust data upon which to make decisions about the most appropriate treatment of both skin and soft tissue infection and osteomyelitis in diabetic patients.
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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 | 0.010 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".