Single-Dose Dexamethasone Reduces Dynamic Pain After Total Hip Arthroplasty
Bibliographic record
Abstract
BACKGROUND: Preoperative glucocorticoids reduce postoperative nausea but may also improve analgesia and decrease opioid consumption. METHODS: Fifty consecutive patients undergoing elective, unilateral, primary total hip arthroplasty under spinal anesthesia with propofol sedation received in a randomized, double-blind, placebo-controlled manner either 40 mg of dexamethasone or saline placebo i.v. before the start of surgery. I.v. patient-controlled analgesia morphine, ibuprofen 400 mg p.o. q6 h and acetaminophen 650 mg p.o. q6 h were given for 48 h. Pain (0-10 numeric rating scale, NRS) at rest, side effects, and total cumulative patient-controlled analgesia morphine consumption were recorded q4 h for 48 h. Dynamic pain NRS score was recorded at 24 h. C-reactive protein levels were measured in a subgroup of 25 patients at 48 h. RESULTS: The intraoperative sedation requirement with propofol was significantly increased in the dexamethasone group (234.6 +/- 160.1 vs 138.8 +/- 122.7 mg, P = 0.02). Dynamic pain was greatly reduced in the dexamethasone group (NRS score: 2.7, 95% CI: 2.2-3.1 vs 6.8, 6.4-7.2; P < 0.0001). There was no significant effect on pain at rest or cumulative morphine consumption at any time. C-reactive protein levels at 48 h were markedly reduced by dexamethasone (52.4 mg/mL, 28.2-76.6 vs 194.2, 168.9-219.4; P < 0.0001). Seven patients in the control group, but only one in the dexamethasone group, were treated for nausea (P = 0.05). CONCLUSIONS: A single, preoperative i.v. dose of dexamethasone 40 mg has a prolonged suppressive effect on the inflammatory response and decreases dynamic pain 24 h after total hip arthroplasty.
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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 | 0.001 |
| 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".