Validated 60-Second General Foot Screen: A Pilot Trial and Guide to Diagnoses and Treatment
Bibliographic record
Abstract
GENERAL PURPOSE: To provide information on a 60-second General Foot Screen to assist in the prevention and/or identification and management of common foot problems. TARGET AUDIENCE: This continuing education activity is intended for physicians, physician assistants, nurse practitioners, and nurses with an interest in skin and wound care. LEARNING OBJECTIVES/OUTCOMES: After participating in this educational activity, the participant should be better able to:1. Use the 60-second General Foot Screen to assist healthcare professionals in the recognition of common foot problems.2. Identify risk factors, causes, and treatment of selected foot problems. ABSTRACT: Foot health is important to overall patient health. Early diagnosis and treatment of diabetes, neuropathy, fungal foot infections, foot deformity, and vascular disease/lower leg edema can improve patient quality of life. One way to achieve this is effective screening. To this end, researchers piloted a validated 10-item screening tool to assess foot health on 120 patients; 74.17% had at least one positive abnormality, demonstrating the critical importance of these early findings. Only 25.83% of individuals had completely low-risk feet. This easy-to-use tool can assist healthcare professionals in the recognition and treatment of common foot problems. The article also outlines the early signs of disease by screening item and provides a guide to treatment to enable effective prevention and quality care.
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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 | 0.000 | 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) | 0.000 | 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".