Poor achievement of guidelines-recommended targets in type 2 diabetes: findings from a contemporary prospective cohort study
Bibliographic record
Abstract
AIMS: To prospectively evaluate diabetes management in the primary care setting and explore factors related to guideline-recommended triple target achievement [blood pressure (BP) ≤ 130/80 mmHg, A1C ≤ 7% and low-density lipoprotein (LDL)-cholesterol < 2.5 mmol/l]. METHODS: Baseline, 6 and 12 month data on clinical and laboratory parameters were measured in 3002 patients with type 2 diabetes enrolled as part of a prospective quality enhancement research initiative in Canada. A generalised estimating equation model was fitted to assess variables associated with triple target achievement. RESULTS: At baseline, 54%, 53% and 64% of patients, respectively, had BP, A1C and LDL-cholesterol at target; all three goals were met by 19% of patients. The percentage of individuals achieving these targets significantly increased during the study [60%, 57%, 76% and 26%, respectively, at the final visit, p < 0.0001 except for A1C, p = 0.27]. A much smaller proportion of patients had adequate control during the entire study period [30%, 39%, 53% and 7%, respectively]. In multivariable analysis, women, patients younger than 65 years and patients of Afro-Canadian origin were less likely to achieve the triple target. DISCUSSION: As part of a quality enhancement research initiative, we observed important improvements in the attainment of guidelines-recommended targets in patients with type 2 diabetes followed for a 12-month period in the primary care setting; however, many individuals still failed to achieve and especially maintain optimal goals for therapy, particularly the triple target. Results of the multivariable analysis reinforce the need to address barriers to improve diabetes care, particularly in more susceptible groups.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".