A Perioperative Approach to Increase Limb Salvage When Treating Foot Ulcers in Patients With Diabetes
Bibliographic record
Abstract
Foot ulceration in patients with diabetes increases the risk of lower extremity amputation. Major amputations produce substantial adverse consequences, increase length of hospital stay, diminish quality of life, and increase mortality. In this article, we describe approaches that decrease amputations and improve the quality of life for patients with diabetes and foot ulcers. We highlight the role of the perioperative nurse, who is essential to providing optimal patient care in the perioperative period. Perioperative care of patients with diabetes involves providing optimal surveillance for a break in the skin of the foot, screening for neuropathy, following guidelines for foot ulcer infections, preparing for pathophysiology-based debridement, using adjuvant therapies, and offloading the patient's affected foot. Nurses should understand the disease process and pathophysiology and how to use these approaches in the perioperative setting to assist in curtailing the morbidity and mortality associated with foot ulcers in patients with diabetes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".