Is glycemia control in Canadians with diabetes individualized? A cross-sectional observational study
Bibliographic record
Abstract
OBJECTIVE: Diabetes guidelines recommend individualized glycemic targets: tighter control in younger, healthier patients and consideration of more moderate control in the elderly and those with coexisting illnesses. Our objective was to examine whether glycemic control varied by age and comorbidities in Canadian primary care. RESEARCH DESIGN AND METHODS: Cross-sectional study using data from the electronic medical records of 537 primary care providers across Canada; 30 416 patients with diabetes, aged 40 or above, with at least one encounter and one hemoglobin A1c (HbA1c) measurement between 1 January 2012 and 31 December 2013. The outcome was the most recent HbA1c, categorized into three levels of control: tight (<7.0% or <53 mmol/mol), moderate (7.0%-8.5%, 53 mmol/mol-69.5 mmol/mol) and uncontrolled (>8.5% or >69.5 mmol/mol). We adjusted for several factors associated with glycemic control including treatment intensity. RESULTS: Younger patients (aged 40-49) were more likely to have moderate as opposed to tight control than the older patients (aged 80+) (OR 1.28; 95% CI 1.11 to 1.49, p=0.001). The youngest were also more likely to have uncontrolled as opposed to moderately controlled glycemia (OR 3.39; 95% CI 2.75 to 4.17, p<0.0001). Patients with no or only one comorbidity were more likely to have moderate as opposed to tight control than those with three or more comorbidities (OR 1.66;95% CI 1.46 to 1.90, p<0.0001). CONCLUSIONS: Levels of glycemic control, given age and comorbidities appear to differ from guideline recommendations. Research is needed to understand these discrepancies and develop methods to assist providers in personalizing glycemic targets.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".