Prediction of stump healing in lower limb amputation: a narrative review
Bibliographic record
Abstract
Both types of diabetes, as well as different forms of acquired diabetes, are associated with diabetic peripheral neuropathy. Diabetic foot ulcers (DFU) is the condition most commonly related to somatic peripheral neuropathy, often leading to gangrene and limb amputation. Independent from large-vessel disease, sensory loss may result in DFU development and even amputation. The crucial part of any lower limb amputation is the stump healing process, which represents the central goal of postoperative management. Despite the importance attributed to this process, a standard set of guidelines regarding efficient healing methods is yet to be formulated. Health professionals are faced with the challenge of assessing the different risk factors and deciding which has a greater influence on the stump healing rate. There is currently an insufficient number of studies regarding factors effecting lower limb amputation. The main purpose of this review is to discuss the markers that can be helpful in the prediction of stump healing in patients who have undergone lower limb amputation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".