Prescribing patterns and adherence to medication among South‐Asian, Chinese and white people with Type 2 diabetes mellitus: a population‐based cohort study
Why this work is in the frame
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Bibliographic record
Abstract
AIM: To determine the prescribing of and adherence to oral hypoglycaemic agents, insulin, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers and statin therapy among South-Asian, Chinese and white people with newly diagnosed diabetes. METHODS: The present study was a population-based cohort study using administrative and pharmacy databases to include all South-Asian, Chinese and white people aged ≥ 35 years with diabetes living in British Columbia, Canada (1997-2006). Adherence to each class of medication was measured using proportion of days covered over 1 year with optimum adherence defined as ≥ 80%. RESULTS: The study population included 9529 South-Asian, 14 084 Chinese and 143 630 white people with diabetes. The proportion of people who were prescribed angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, statin or oral hypoglycaemic agents was ≤ 50% for all groups. South-Asian and Chinese people had significantly lower adherence for all medications than white people, with the lowest adherence to angiotensin-converting enzyme inhibitor treatment (South-Asian people: adjusted odds ratio 0.37, 95% CI 0.34-0.39; P<0.0001; Chinese people: adjusted odds ratio 0.50, 95% CI 0.47-0.54; P<0.0001) and statin therapy (South-Asian people: adjusted odds ratio 0.47, 95% CI 0.41 - 0.53, P < 0.0001; Chinese people: adjusted odds ratio 0.72, 95% CI 0.67 - 0.77; P<0.0001) compared with white people. CONCLUSION: Adherence to evidence-based pharmacotherapy was substantially worse among the South-Asian and Chinese populations. Care providers need to be alerted to the high levels of non-adherence in these groups and the underlying causes need to be investigated.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it