Effect of flurbiprofen axetil on acute pain in patients with fracture of a variety of inflammatory mediators and pain score
Bibliographic record
Abstract
Objective To observe the effect of flurbiprofen axetil on plasma prostaglandin E2,5-HT,bradykinin,three kinds of inflammatory mediators and pain score before and after fracture patients with acute pain medication.Methods A total of 30 inpatients with acute pain caused by fracture were selected as research objects.The intravenous drip of nonsteroidal anti-inflammatory drugs and analgesic efficacy of flurbiprofen axetil injection were used for analgesia.Simplified the pain degree of patients before and after with the McGill pain score evaluation.Enzyme-linked immunosorbent assay(ELISA) nethod was used to determine plasma prostaglandin E2,5-HT,bradykinin before and after treatment.Results 30 min before the treatment the concentration of prostaglandin E2,5-HT,and bradykinin,and the short-form McGill pain questionnaire(MPQ) score were significantly higher than those of 2 h and 6 h after treatment(all P0.05).After 6 h,plasma prostaglandin E2,5-HT,bradykinin concentration were significantly higher than those after administration of 2 h(all P0.05).After administration of 6 h McGill pain score was higher than that 2 h after the treatment.Conclusions Flurbiprofen axetil can inhibit the fracture caused by acute pain in patients with prostaglandin E2,5-HT,bradykinin concentration in plasma and can effectively reduce the pain of patients.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".