Paradoxically Decreased HDL-Cholesterol Levels Associated with Rosiglitazone Therapy
Bibliographic record
Abstract
OBJECTIVE: To report 2 cases of very low high-density lipoprotein cholesterol (HDL-C) levels associated with rosiglitazone therapy. CASE SUMMARY: Two patients with type 2 diabetes taking rosiglitazone for glycemic control developed paradoxically low HDL-C levels during rosiglitazone therapy. In the first patient, the HDL-C level decreased from 33 to 11.6 mg/dL after 8 months of therapy. The second patient's HDL-C level decreased from the baseline level of 44.8 mg/dL to 19.7 mg/dL after 4 months of rosiglitazone use. These abnormalities resolved on discontinuation of rosiglitazone and were not observed when the patients were treated with pioglitazone. The patients had no changes to other drug therapy or medical conditions known to affect lipid metabolism during treatment with rosiglitazone. DISCUSSION: Thiazolidinediones, insulin sensitizers widely used in the treatment of type 2 diabetes, have been reported to have beneficial effects on lipids, such as triglyceride lowering and HDL-C elevation, in addition to their glucose-lowering effects. It has been suggested that rosiglitazone and pioglitazone, the 2 currently available thiazolidinediones, may differ in their effects on lipids. As of July 2006, a total of 8 cases of paradoxical lowering of plasma HDL-C associated with rosiglitazone have now been reported. Based on use of the Naranjo probability scale, the 2 cases presented here were probably associated with rosiglitazone. The duration of therapy may be important in this paradoxical effect. CONCLUSIONS: Rosiglitazone is associated with a paradoxical decrease in HDL-C levels in patients with type 2 diabetes. In patients receiving rosiglitazone, a baseline lipid panel should be performed and lipid values should be monitored during the course of therapy.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".