Patient-Level Evaluation of Community-Based, Multifactorial Intervention to Prevent Diabetic Nephropathy in Northern Alberta, Canada
Bibliographic record
Abstract
OBJECTIVE: To examine whether patients with type 2 diabetes enrolled in community-based clinics uniformly benefit from interventions designed to achieve multiple risk factor targets. METHODS: Using data from community-based clinics in Alberta, Canada, we examined whether patients achieved targets for blood pressure (<130/80 mm Hg), A1c (≤7%), low-density lipoprotein (LDL) cholesterol (<2.5 mmol/L), weight reduction, exercising, smoking cessation, and meal plan management among 235 patients between 2004 to 2007 with a 1-year follow-up. The effectiveness of the clinics was assessed by the number of targets achieved by individual patients. Patients achieving different degrees of success (0-2, 3-4, and ≥5 targets) were compared. RESULTS: Mean age of patients at baseline was 62 years (standard deviation [SD], 12 years), 43% were female, 77% had a history of cardiovascular disease, and mean diabetes duration was 9 years (SD, 9 years). Overall, 47 patients achieved 0 to 2 targets (group 1), 132 achieved 3 to 4 targets (group 2), and 56 achieved ≥5 targets (group 3) out of 7 targets. More patients in group 1 were male and had longer diabetes duration and were more likely to smoke or use insulin. Despite reductions in A1c in all groups and similar use of antihypertensives, there was no improvement in weight or systolic blood pressure (which actually increased) in group 1. Successful patients (group 3) were more likely to report adherence with exercise and a meal plan. CONCLUSIONS: Despite equally intensive, target-driven pharmacotherapy, this community-based multifactorial intervention was less effective among a subset of patients who did not adhere to lifestyle changes. Strategies to effectively address lifestyle factors will be important as this intervention is refined.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".