Impact of the socioeconomic status on the probability of receiving formulary restricted thiazolidine (TZDs).
Bibliographic record
Abstract
BACKGROUND: In the province of Quebec, Canada, the reimbursement of thiazolidinediones (TZDs) is limited to patients who do not respond to doses of metformin and a sulfonylurea. OBJECTIVES: The objective of this research project was to study, in a real-life setting, the ârisk factorsâ for receiving these restricted drugs among patients who meet the reimbursement criteria. METHODS: Among patients eligible for drug coverage under the RAMQ between May 2000 and June 2005, we selected those who received six consecutive dispensations of high doses of both metformin and a sulfonylurea. The date of the sixth dispensation was set as the index date. The proportion of patients who received a TZD in the year following the index date was calculated and a logistic regression was used to estimate the impact of several factors on the probability of receiving a TZD. RESULTS: There were 4,836 patients in the cohort. A TZD was dispensed to 24.9% (95% CI: 23.7%;26.2%) of the patients. Compared to the oldest group of patients (65 years and more), the probability to receive a TZD was higher for patients aged 51 to 64 years (OR=1.33 95% CI: 1.11;1.59) and patients aged 19 to 50 years [OR=1.81 (95% CI: 1.40;2.33)]. Patients with the highest income were more likely to receive a TZD (OR=1.55 95% CI: 1.21;1.98) compared to patients with the lowest income. CONCLUSIONS: These findings suggest that the restricted access to TZDs probably results in social inequities, as individuals with lower incomes are less likely to receive these drugs. Key words: Restricted drugs, TZDs, diabetes.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 teacher head, 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".