Is thiazolidinediones use a factor in delaying the need for insulin therapy in type 2 patients with diabetes? A population-based cohort study
Bibliographic record
Abstract
OBJECTIVE: To understand the independent role of thiazolidinediones (TZDs) in delaying progression to parenteral insulin therapy. DESIGN: Population-based retrospective cohort study. SETTING: British Columbia, Canada. PARTICIPANTS: A total of 18 867 type 2 diabetes patients (mean age 58.9) treated with metformin as first-line therapy who then switched or added a TZD or sulphonylurea as a second-line treatment between 1 January 1998 and 31 March 2008. OUTCOME MEASURES: Multivariable Poisson regression models were used to estimate the effect of using TZD compared to sulphonylureas on time to the initiation of insulin treatment (third-line). RESULTS: The adjusted rate difference in women aged <60 showed 2.22 fewer insulin initiation events per 100 person-years (PYs) in the TZD group versus the sulphonylurea group (95% CI -3.46 to -0.99). Men in the same age group had 1.50 fewer insulin initiation events per 100 PYs in the TZD group versus the sulphonylurea group (95% CI -2.44 to -0.56). The average time in days to initiation on insulin in the sulphonylurea, rosiglitazone and pioglitazone group was 343, 252 and 339, respectively. The cumulative hazard for starting insulin for sulphonylurea patients at 12, 24, 36 and 48 months was approximately three times higher compared to TZD patients. CONCLUSIONS: Second-line TZD therapy compared to second-line sulphonylurea therapy was associated with a lower incidence of insulin initiation as third-line treatment in patients with type 2 diabetes, with a mean delay of 90 days. This duration of delay must be weighed against the absence of a proven reduction in morbidity or mortality with TZDs and their known serious cardiovascular harm.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".