A Systematic Review and Meta-Analysis of Hypoglycemia and Cardiovascular Events
Bibliographic record
Abstract
OBJECTIVE: Glyburide is the most widely used sulfonylurea but has unique pharmacodynamic properties that may increase harm. We hypothesized that glyburide causes more hypoglycemia and cardiovascular events than other secretagogues or insulin. RESEARCH DESIGN AND METHODS: Data sources were Medline, Embase, Cochrane, and three other web-based clinical trial registers (1966-2005). Parallel, randomized, controlled trials in people with type 2 diabetes comparing glyburide monotherapy with monotherapy using secretagogues or insulin were selected. Outcomes were hypoglycemia, glycemic control, cardiovascular events, body weight, and death. Titles and abstracts of 1,806 publications were reviewed in duplicate and 21 relevant articles identified. Data on patient characteristics, interventions, outcomes, and validity were extracted in duplicate using predefined criteria. RESULTS: Glyburide was associated with a 52% greater risk of experiencing at least one episode of hypoglycemia compared with other secretagogues (relative risk 1.52 [95% CI 1.21-1.92]) and with 83% greater risk compared with other sulfonylureas (1.83 [1.35-2.49]). Glyburide was not associated with an increased risk of cardiovascular events (0.84 [0.56-1.26]), death (0.87 [0.70-1.07]), or end-of-trial weight (weighted mean difference 1.69 kg [95% CI -0.41 to 3.80]) compared with other secretagogues. Limitations included suboptimal reporting of original trials. Loss to follow-up exceeded 20% in some studies, and major hypoglycemia was infrequently reported. CONCLUSIONS: Glyburide caused more hypoglycemia than other secretagogues and other sulfonylureas. Glyburide was not associated with an increased risk of cardiovascular events, death, or weight gain.
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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 | 0.018 | 0.050 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.040 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".