Bibliographic record
Abstract
OBJECTIVE: To review underlying causes of diabetic foot ulceration, provide a practical assessment of patients at risk, and outline an evidence-based approach to therapy for diabetic patients with foot ulcers. QUALITY OF EVIDENCE: A MEDLINE search was conducted for the period from 1979 to 1999 for articles relating to diabetic foot ulcers. Most studies found were case series or small controlled trials. MAIN MESSAGE: Foot ulcers in diabetic patients are common and frequently lead to lower limb amputation unless a prompt, rational, multidisciplinary approach to therapy is taken. Factors that affect development and healing of diabetic patients' foot ulcers include the degree of metabolic control, the presence of ischemia or infection, and continuing trauma to feet from excessive plantar pressure or poorly fitting shoes. Appropriate wound care for diabetic patients addresses these issues and provides optimal local ulcer therapy with débridement of necrotic tissue and provision of a moist wound-healing environment. Therapies that have no known therapeutic value, such as foot soaking and topical antiseptics, can actually be harmful and should be avoided. CONCLUSION: Family physicians are often primary medical contacts for patients with diabetes. Patients should be screened regularly for diabetic foot complications, and preventive measures should be initiated for those at risk of ulceration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".