Rosiglitazone Causes Endothelial Dysfunction in Humans
Bibliographic record
Abstract
OBJECTIVES: We explored the impact of rosiglitazone on endothelial function in normal volunteers and its interaction with glyceryl trinitrate (GTN)-induced abnormalities in endothelial function. We hypothesized that rosiglitazone would have a neutral effect on endothelial function in normal volunteers and would favorably modify endothelial dysfunction induced by GTN. METHODS: In this double-blind, randomized, placebo-controlled study, 44 participants were randomized to placebo, rosiglitazone (4 mg twice daily), transdermal GTN (0.6 mg/h), or both GTN and rosiglitazone. After 7 days of treatment, participants underwent measures of forearm blood flow during brachial artery infusion of acetylcholine (Ach). Serum glucose concentrations and insulin sensitivity were assessed. RESULTS: Unexpectedly, rosiglitazone-treated participants experienced blunted responses to endothelium-dependent responses to Ach (P < .05 vs placebo). Sustained GTN administration caused similar abnormalities in endothelial function (P < .05 vs placebo) and rosiglitazone + GTN (P < .05 vs placebo; P = ns vs rosiglitazone). Interestingly, co-infusion of the antioxidant vitamin C improved endothelial responses in those randomized to rosiglitazone and GTN alone (P = not significant [ns] compared with placebo), but it did not improve endothelial function in those treated with rosiglitazone + GTN. Neither rosiglitazone nor GTN treatment modified the measures of glucose metabolism. CONCLUSIONS: Unexpectedly, therapy with rosiglitazone caused abnormalities in endothelial function in normal volunteers. These findings have important implications with respect to drug development and surveillance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".