Reduced cardiovascular morbidity and mortality associated with metformin use in subjects with Type 2 diabetes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIM: Metformin therapy reduces microvascular complications in Type 2 diabetes; questions remain, however, regarding its impact on macrovascular events. This study examined metformin use in relation to risk of cardiovascular-related hospitalization and mortality. METHODS: We conducted a retrospective cohort analysis, using Saskatchewan Health administrative databases to identify new users of oral antidiabetic drugs. Subject groups were defined by medication use during 1991-1999: sulphonylurea monotherapy, metformin monotherapy, or combination therapy. Deaths and non-fatal hospitalizations recorded during the study period were identified as cardiovascular-related from ICD-9 codes. The main outcome was a composite of first non-fatal hospitalization or death. Standard multivariate techniques, including propensity scores, were used to adjust for potential confounding. Multivariate Cox proportional hazard models were used to examine the relationship between metformin use and the composite endpoint. RESULTS: Metformin monotherapy was associated with a lower risk of the composite endpoint (adjusted hazard ratio 0.81; 95% confidence interval 0.68, 0.97) compared with sulphonylurea monotherapy. Combination therapy with meformin and a sulphonylurea was associated with lower mortality, but had similar hospitalization rates, to sulphonylurea monotherapy. CONCLUSIONS: Metformin monotherapy was associated with a lower risk of cardiovascular-related morbidity and mortality, and combination metformin and sulphonylurea therapy was associated with a reduced risk of fatal cardiovascular events, when compared with sulphonylurea monotherapy.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it