Diabetes Canada 2018 clinical practice guidelines: Key messages for family physicians caring for patients living with type 2 diabetes.
Bibliographic record
Abstract
OBJECTIVE: To summarize the 2018 Diabetes Canada clinical practice guidelines, focusing on high-priority recommendations for FPs managing people who live with type 2 diabetes. QUALITY OF EVIDENCE: A prioritization process was conducted to focus the efforts of Diabetes Canada's guideline dissemination and implementation efforts. The resulting identified key messages for FPs to consider when managing patients with type 2 diabetes are described. Evidence supporting the guideline recommendations ranges from levels I to IV and grades A to D. MAIN MESSAGE: Three key messages were identified from the 2018 guidelines as priorities for FPs: discussing opportunities to reduce the risk of diabetes complications, discussing opportunities to ensure safety and prevent hypoglycemia, and discussing progress on self-management goals and addressing barriers. A theme cutting across these key messages was the need to tailor discussions to the needs and preferences of each person. These important guideline recommendations are highlighted, along with information about relevant tools for implementing the recommendations in real-world practice. CONCLUSION: High-quality diabetes care involves a series of periodic conversations about self-management and about pharmacologic and nonpharmacologic treatments that fit with each patient's goals (ie, shared decision making). Incorporating these conversations into regular practice provides FPs with opportunities to maximize likely benefits of treatments and decrease the risk of harms, to support patients in initiating and sustaining desired lifestyle changes, and to help patients cope with the burdens of diabetes and comorbid conditions.
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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 | 0.013 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.019 | 0.010 |
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".