Effect of inflammation on kidney function and pharmacokinetics of COX‐2 selective nonsteroidal anti‐inflammatory drugs rofecoxib and meloxicam
Bibliographic record
Abstract
Chronic arthritis adversely affects glomerular function and nonsteroidal anti-inflammatory drugs (NSAIDs) reduce electrolyte urinary excretion. In addition, both acute and chronic inflammations may alter clearance of drugs. We studied (a) the effects of inflammation on the renal function and pharmacokinetics of rofecoxib and meloxicam; (b) whether inflammation could exacerbate reduced electrolytes excretion changes observed with NSAIDs; and (c) the influence of inflammation on distribution of these drugs into the kidney. Single oral doses of rofecoxib (10 mg kg(-1)), meloxicam (3 mg kg(-1)) or placebo were administered to normal or pre-adjuvant arthritic rats. Blood and urine samples were collected for the measurement of plasma nitrite, BUN and creatinine. The urinary excretion of sodium and potassium was also determined. Nitrite, BUN and plasma creatinine were increased starting on day 9 in the groups with inflammation. Sodium and potassium excretion rates were not affected by inflammation. Meloxicam did not alter the electrolyte excretion in any of the groups. Rofecoxib significantly decreased sodium and potassium excretion in normal rats and potassium excretion in inflamed rats. Inflammation significantly increased plasma concentrations of rofecoxib, but not meloxicam. The ratios of the kidney:plasma concentrations were not significantly altered by inflammation following either drug. Inflammation altered kidney function, demonstrated by increases in BUN and plasma creatinine. However, it did not influence the urinary electrolytes excretion. Since we have observed similar patterns of the effect of NSAIDs on kidney under healthy and inflammatory conditions, one may conclude that inflammation does not exacerbate the adverse effect.
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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) | 0.001 | 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 | 0.000 | 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".