Guidelines on the diagnosis and treatment of foot infection in persons with diabetes (IWGDF 2019 update)
Bibliographic record
Abstract
The International Working Group on the Diabetic Foot (IWGDF) has published evidence-based guidelines on the prevention and management of diabetic foot disease since 1999. This guideline is on the diagnosis and treatment of foot infection in persons with diabetes and updates the 2015 IWGDF infection guideline. On the basis of patient, intervention, comparison, outcomes (PICOs) developed by the infection committee, in conjunction with internal and external reviewers and consultants, and on systematic reviews the committee conducted on the diagnosis of infection (new) and treatment of infection (updated from 2015), we offer 27 recommendations. These cover various aspects of diagnosing soft tissue and bone infection, including the classification scheme for diagnosing infection and its severity. Of note, we have updated this scheme for the first time since we developed it 15 years ago. We also review the microbiology of diabetic foot infections, including how to collect samples and to process them to identify causative pathogens. Finally, we discuss the approach to treating diabetic foot infections, including selecting appropriate empiric and definitive antimicrobial therapy for soft tissue and for bone infections, when and how to approach surgical treatment, and which adjunctive treatments we think are or are not useful for the infectious aspects of diabetic foot problems. For this version of the guideline, we also updated four tables and one figure from the 2016 guideline. We think that following the principles of diagnosing and treating diabetic foot infections outlined in this guideline can help clinicians to provide better care for these 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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.011 |
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".