Rural Residence Is Associated With a Delayed Trend Away From Sulfonylurea Use for Treatment Intensification of Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE: To examine the intersection between location of residence along the rural-urban continuum (metropolitan, urban, and rural) and sulfonylurea dispensation records for the management of type 2 diabetes. RESEARCH DESIGN AND METHODS: This retrospective cohort study used administrative health records of adult new metformin users between April 2008 and March 2019 in Alberta, Canada. Multivariable logistic regression was performed to examine the association between sulfonylurea-based treatment intensification and location of residence. RESULTS: Treatment was intensified in 66,084 (38%) of 171,759 new metformin users after a mean of 1.5 years. At treatment intensification, mean age was 55 years, 62% of users were male, and 27% were rural residents. The most common antihyperglycemic drug, given to 30,297 people (46%) for treatment intensification, was a sulfonylurea. At the beginning of our observation period, the proportion of people dispensed a sulfonylurea at first treatment intensification was highest in rural (57%), compared with urban (54%) and metropolitan (52%) areas (P = 0.009). Although proportions decreased over time across the province, rural residents continued to constitute the highest proportion of sulfonylurea users (45%), compared with urban (35%) and metropolitan (37%) residents (P < 0.001), and the trend away from sulfonylurea use was delayed by ∼4 years for rural residents. Adjusting for potential sources of confounding, rural residence was associated with a significantly higher likelihood of using a sulfonylurea compared with metropolitan residence (adjusted odds ratio 1.34; 95% CI 1.29-1.39). CONCLUSIONS: Variation in sulfonylurea dispensation across the rural-urban continuum provides a basis for continued research in the differences in process of care by location.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".