Suppression of Niacin-induced Vasodilation with an Antagonist to Prostaglandin D2 Receptor Subtype 1
Bibliographic record
Abstract
Niacin (nicotinic acid) reduces cardiovascular events in patients with dyslipidemia. However, symptoms associated with niacin-induced vasodilation (e.g., flushing) have limited its use. Laropiprant is a selective antagonist of the prostaglandin D2 receptor subtype 1 (DP1), which may mediate niacin-induced vasodilation. The aim of this proof-of-concept study was to evaluate the effects of laropiprant (vs placebo) on niacin-induced cutaneous vasodilation. Coadministration of laropiprant 30, 100, and 300 mg with extended-release (ER) niacin significantly lowered flushing symptom scores (by approximately 50% or more) and also significantly reduced malar skin blood flow measured by laser Doppler perfusion imaging. Laropiprant was effective after multiple doses in reducing symptoms of flushing and attenuating the increased malar skin blood flow induced by ER niacin. In conclusion, the DP1 receptor antagonist laropiprant was effective in suppressing both subjective and objective manifestations of niacin-induced vasodilation. Clinical Pharmacology & Therapeutics (2007) 81, 849–857. doi:10.1038/sj.clpt.6100180; published online 28 March 2007 TRIAL REGISTRATION: This study has been registered at clinicaltrials.gov on 9/19/2007 (NCT00533312).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".