Drug-disease interaction:effect of rheumatoid arthritis (RA) on the pharmacodynamics (PD) and pharmacokinetics (PK) of AT1 receptor antagonists
Bibliographic record
Abstract
Inflammatory conditions decrease cardiovascular response to β and Ca2+ channel blockers despite elevated drug levels due to downregulation of the receptors by inflammatory mediators. Whether downregulation is also evident with AT1R antagonists in RA was tested. The subjects were 14 active RA, 12 controlled RA and 12 healthy. Joint swelling, NO and C-reactive protein were measured. Valsartan (VAL) or losartan (LOS) was dosed orally, with a one-week washout period. VAL, LOS and its active metabolite EXP 3174 (EXP) were analyzed from blood samples. Systolic, diastolic and mean arterial pressure were recorded. Area under the % effect-time curve (AUEC) and the maximum change from baseline (Emax) were calculated. Inflammatory mediators were significantly higher in patients with active RA as compared with controlled RA and healthy. PK parameters indicated no significant difference between the 3 groups for VAL and LOS. However AUC of EXP was significantly lower in RA indicating its reduced formation caused by the disease. Arthritis had no significant effect on AUEC or Emax. However, there was a trend towards increased response to VAL in RA as compared to healthy subjects, perhaps due to receptor upregulation. This was not observed with LOS due, possibly to reduced active metabolite concentration. Since there was no receptor downregulation, AT1R antagonists may serve as alternative antihypertensive agents to β or Ca2+ channel blockers for patients with inflammatory conditions. Clinical Pharmacology & Therapeutics (2004) 75, P82–P82; doi: 10.1016/j.clpt.2003.11.313
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".