Diagnosis of infection in the foot in diabetes: a systematic review
Bibliographic record
Abstract
BACKGROUND: Securing an early accurate diagnosis of diabetic foot infections and assessment of their severity are of paramount importance since these infections can cause great morbidity and potentially mortality and present formidable challenges in surgical and antimicrobial treatment. METHODS: In June 2018, we searched the literature using PuEbMed and EMBASE for published studies on the diagnosis of diabetic foot infection. On the basis of predetermined criteria, we reviewed prospective controlled, as well as noncontrolled, studies in any language, seeking translations for those not in English. We then developed evidence statements on the basis of the included papers. RESULTS: From the 4242 records screened, we selected 35 papers that met our inclusion criteria. The quality of all but one of the evidence statements was low because of the weak methodology of nearly all of the studies. The available data suggest that diagnosing diabetic foot infections on the basis of clinical signs and symptoms and classified according to the International Working Group of the Diabetic Foot scheme correlates with the patient's likelihood of ulcer healing, of lower extremity amputation, and risk of death. Elevated levels of selected serum inflammatory markers are supportive, but not diagnostic, of soft tissue or bone infection. In patients with suspected diabetic foot osteomyelitis, both a positive probe-to-bone test and an elevated erythrocyte sedimentation rate are strongly associated with its presence. Culturing tissue samples of soft tissues or bone, when care is taken to avoid contamination, provides more accurate microbiological information than culturing superficial (swab) samples. Plain X-ray remains the first-line imaging examination when there is suspicion of diabetic foot osteomyelitis, but advanced imaging methods help in cases when either the diagnosis or the localization of infection is uncertain. CONCLUSION: The results of this first reported systematic review on the diagnosis of diabetic foot infections provide some guidance for clinicians, but there is a need for more prospective controlled studies of high quality.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.010 | 0.011 |
| 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) | 0.004 | 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".