Inlow’s 60-second Diabetic Foot Screen: Update 2022
Bibliographic record
Abstract
Eighty percent of lower extremity amputations related to diabetes-related foot disease can be prevented with the integration of prevention and interdisciplinary care, including screening,foot care and footwear education. In Canada, only half of persons with diabetes receive appropriate foot screening, and this estimate may be higher than the reality. Wounds Canada has updated its diabetic foot screening tool, Inlow’s 60-second Diabetic Foot Screen (2022) to increase its functionality and, ultimately, its usability in clinical practice. The new version was launched at workshops held at the 2022 Diabetes Canada and the Orthotics Prosthetics Canada national conferences. For a person with diabetes, the screening results provide a risk level and identify direct associated educational activities and ongoing screening schedules. For clinicians and healthcare organizations, the use of the diabetic foot screening tool in all care settings creates a common communication avenue between individuals and interdisciplinary teams supporting the individuals’ foot care. The methodology to update Inlow’s 60-second Diabetic Foot Screen, including feedback from a primary care network and working experts, and alignment with the International Working Group on the Diabetic Foot (IWGDF) Prevention Guidelines, are presented in this manuscript.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".