Evolution of WIfI: Expansion of WIfI Notation After Intervention
Bibliographic record
Abstract
Nearly a decade ago, the Society for Vascular Surgery (SVS)'s wound, ischemia, and foot Infection (WIfI) classification was first developed to help assess overall limb threat. However, managing conditions such as diabetic foot ulcer and chronic limb-threatening ischemia can be complex. For instance, certain investigative findings might initially be pending such as the level of ischemia or extent of infection before the final classification is established. In addition, wounds evolve rapidly, and the current classification does not allow for tracking their progression over time during treatment. Therefore, we propose a supplemental consistent notation for scoring WifI re-assessment during treatment of a threatened limb inspired by the cancer staging before and after neoadjuvant treatment classification system. Thus, we describe the re-scoring system and how to use it. Our suggestion supports a coherent method to longitudinally communicate characteristics of a threatened limb. This has potential to support high quality interdisciplinary, patient-centered care and enhance the use of this classification in research. Further work is required to validate this modification of a common language of risk.
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 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) | 0.000 | 0.000 |
| 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) | 0.001 | 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".