Diabetic Foot Ulcer Off-loading
Bibliographic record
Abstract
OBJECTIVE: To evaluate the practice of off-loading diabetic foot ulcers (DFUs) using real-world data from a large wound registry to better identify and understand the gap between evidence and practice. DESIGN: Retrospective, deidentified data were extracted from the US Wound Registry based on patient/wound characteristics, procedures performed, and at which clinic the DFU was treated. SETTING: 96 clinics (23 from the United States and Puerto Rico) PATIENTS: : 11,784 patients; 25,114 DFUs MAIN OUTCOME MEASURES: : Healed/not healed, amputated, percent off-loading, percent use of total contact casting (TCC), infection rate MAIN RESULTS: : Off-loading was documented in only 2.2% of 221,192 visits from January 2, 2007, to January 6, 2013. The most common off-loading option was the postoperative shoe (36.8%) and TCC (16.0%). There were significantly more amputations within 1 year for non-TCC-treated DFUs compared with TCC-treated DFUs (5.2% vs 2.2%; P = .001). The proportion of healed wounds was slightly higher for TCC-treated DFUs versus non-TCC-treated DFUs (39.4% vs 37.2%). Infection rates were significantly higher for non-TCC-treated DFUs compared with TCC-treated DFUs (2.6 vs 1.6; P = 2.1 × 10). Only 59 clinics used TCC (61%); 57% of those clinics used traditional TCC, followed by TCC-EZ (36%). Among clinics using any type of TCC, 96.3% of the DFUs that did not receive TCC were "TCC-eligible" ulcers. Among clinics using "traditional" TCC systems, 1.4% of DFUs were treated with TCC, whereas clinics using TCC-EZ provided TCC to 6.2% of DFUs. CONCLUSION: Total contact casting is vastly underutilized in DFU wound care settings, suggesting that there is a gap in practice for adequate off-loading. New, easier-to-apply TCC kits, such as the TCC-EZ, may increase the frequency with which this ideal form of adequate off-loading is utilized.
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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".