A summary of evidence for diabetic foot assessment
Bibliographic record
Abstract
Objective To search, appraise and summarize the best evidence of the diabetic foot assessment and provide a reference for the standardization of the clinical diabetic foot evaluation in China. Methods On the computer, the following websites as well as databases were searched: National Guideline Clearinghouse (NGC) of the USA, Registered Nurses' Association of Ontario (RNAO) , National Institute for Health and Care Excellence (NICE) of UK, the Scottish Intercollegiate Guidelines Network (SIGN) , New England Guidelines Group (NEGG) , International Guidelines Network (IGN) , American Center for Disease Control and Prevention (ACDC) , World Council of Enterostomal therapists (WCET) , Wound Ostomy Continence Nurses Society (WOCN) , the International Working Group on Diabetic Foot (IWGDF) , American Society for Wound Healing, American Diabetes Association (ADA) , American Society for Vascular Surgery (ASVS) , Society of Endocrinology of Chinese Medical Association, Clinical evidence, PubMed, ProQuest, Web of Science, Clinical Key, CINAHL, Best Practice, CNKI, VIP, Wanfang Data, Medlive from January of 2010 to July of 2018 about all evidence-based clinical practice guidelines and systematic reviews on assessment of diabetic foot. Two researchers evaluated the quality of the articles and performed materials extraction, and extracted the evidence from the qualified articles. Results A total of 7 articles were included among which 6 were guidelines and 1 was systemic review. After analyzing them, 9 categories and 32 items of the best evidence contents about diabetic foot assessment were concluded. Conclusions This study summarizes the best evidence for assessment of diabetic foot and provide evidence basis for medical institutions to improve clinical practice of diabetic foot assessment. When applying the evidence into clinical practice, it is necessary to evaluate specific situations, consider patients' values and willingness and select targeted evidence accordingly. Key words: Diabetic foot; Foot ulcer; Assessment; Best evidence; Evidence summary
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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 | 0.014 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.024 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".