<p>Multidisciplinary Management of Diabetic Foot Ulcers in Primary Cares in Quebec: Can We Do Better?</p>
Bibliographic record
Abstract
A growing body of evidence supports the presence of integrated foot care based on multidisciplinary and interdisciplinary teams in the management and prevention of diabetic foot ulcer (DFU) worldwide. This model of care is however rare in the clinical setting in Quebec, Canada. Many best practice gaps are identified as well as probable causal hypothesis are listed in this commentary. We support our opinions with a pilot audit conducted as part of a continuous quality improvement process in managing patients with DFU in our area and on Canadian facts and data. Our pilot study (n = 27 hospitalized patients) included a typical DFU population with neuropathy, peripheral arterial disease and previous amputation. It highlights underachievement of best practice recommendations implementation such as multidisciplinary DFU management and offloading interventions in our establishment. Due the high morbidity and mortality associated with DFU patients, four died during the studied hospitalization episode. Several barriers were encountered in the pilot audit justifying that no robust conclusion can be raised. However, our observations are concerning. Even though data accessibility was limited, our observations are sadly coherent with what is found in the literature. Economic data of what this means for our health system is put forward in the overall discussion. We are preoccupied by the trends outlined by some facts and observations, and this commentary was written with this in mind. In the face of the diabetes crisis that is arising, a plea is made to reassess care pathway for this vulnerable population as we emphasize the importance of teamwork in managing DFU.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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 source (direct Gemma or distilled Codex), 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".