Compliance with Clinical Practice Guidelines for Type 2 Diabetes in Rural Patients: Treatment Gaps and Opportunities for Improvement
Bibliographic record
Abstract
The level of compliance with clinical practice guidelines for patients with type 2 diabetes was evaluated in 368 patients from two health regions in rural northern Alberta, Canada. Data were collected from patient interviews, drug histories, physical and laboratory assessments, and a self-report questionnaire to assess clinical status, indicators of diabetes management, and health care utilization. Treatment of three clinical indicators of diabetes--hemoglobin A1c (A1C), blood pressure, and low-density lipoprotein cholesterol (LDL)--has been shown to reduce the morbidity and mortality associated with type 2 diabetes. Mean +/- SD values for this cohort of patients were as follows: A1C 7.25% +/- 1.54%, blood pressure 131.7 +/- 18.2/76.2 +/- 12.7 mm Hg, and LDL 105.2 +/- 32 mg/dl. Despite these results, only 10.4% of the patients met all three recommended targets for control of glycemia: A1C below 7%, blood pressure below 130/85 mm Hg, and LDL below 100 mg/dl. Of patients not at target levels, 14.4%, 27.5%, and 86.7% reported receiving no therapy for hyperglycemia, hypertension, and dyslipidemia, respectively. Of those taking oral hypoglycemic agents who were not at target levels, only 35% were receiving combination therapy. Of patients at or above LDL target levels, 87% were not receiving any therapy. Only 22% of patients were taking aspirin, although this therapy would be recommended for the entire cohort according to clinical practice guidelines. Despite the availability of proved effective therapies, treatment gaps were present for this cohort of patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.075 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".