Reduction in Diabetes-Related Major Amputation Rates After Implementation of a Multidisciplinary Model: An Evaluation in Alberta, Canada
Bibliographic record
Abstract
BACKGROUND: Diabetes-related lower limb amputations (LLAs) are a major complication that can be reduced by employing multidisciplinary center frameworks such as the Toe and Flow model (TFM). In this study, we investigate the LLAs reduction efficacy of the TFM compared to the standard of care (SOC) in the Canadian health-care system. METHODS: We retrospectively reviewed the anonymized diabetes-related LLA reports (2007-2017) in Calgary and Edmonton metropolitan health zones in Alberta, Canada. Both zones have the same provincial health-care coverage and similar demographics; however, Calgary operates based on the TFM while Edmonton with the provincial SOC. LLAs were divided into minor and major amputation cohorts and evaluated using the chi-square test, linear regression. A lower major LLAs rate was denoted as a sign for higher efficacy of the system. RESULTS: Although LLAs numbers remained relatively comparable (Calgary: 2238 and Edmonton: 2410), the Calgary zone had both significantly lower major (45%) and higher minor (42%) amputation incidence rates compared to the Edmonton zone. The increasing trend in minor LLAs and decreasing major LLAs in the Calgary zone were negatively and significantly correlated (r = -0.730, p = 0.011), with no significant correlation in the Edmonton zone. CONCLUSIONS: Calgary's decreasing diabetes-related major LLAs and negative correlation in the minor-major LLAs rates compared to its sister zone Edmonton, provides support for the positive impact of the TFM. This investigation includes support for a modernization of the diabetes-related limb preservation practice in Canada by implementing TFMs across the country to combat major LLAs.
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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 | 0.003 | 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 | 0.000 |
| 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".