Addition of dexamethasone to local infiltration analgesia in elective total hip arthroplasty: a double-blind, randomized control trial
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Pain following total hip arthroplasty is significant, and effective analgesia is associated with an improvement in functional outcomes. Dexamethasone may facilitate the action of local anesthesia, but its role as an additive to a local infiltration analgesia (LIA) mixture in hip arthroplasty settings has not been investigated. We hypothesized that the addition of dexamethasone to local anesthetic infiltration improves analgesic outcomes following total hip arthroplasty. METHODS: We performed a double-blind, randomized control trial of 170 patients undergoing total hip arthroplasty. Patients were randomized to receive LIA mixed with either 2 mL of saline 0.9% or 2 mL of dexamethasone 4 mg/mL. The primary outcome was 24 hours oral morphine consumption. Secondary outcomes included short-term and long-term analgesic and functional outcomes and adverse events. RESULTS: 85 patients were included in each arm. 24 hours morphine consumption was similar between saline and dexamethasone groups, with a median (IQR (range)) of 75 (45-105 (0-240)) and 62.5 (37.5-102.5 (0-210)) mg, respectively (p=0.145). However, patients receiving dexamethasone had significantly reduced opioid consumption for their total in-hospital stay, but not at any other time points examined. Functional outcomes were similar between groups. The incidence of postoperative nausea and vomiting was reduced in patients receiving dexamethasone. CONCLUSIONS: The addition of 8 mg dexamethasone to LIA did not reduce 24 hours morphine consumption but was associated with limited improvement in short-term analgesic outcomes and a reduction in postoperative nausea and vomiting. Dexamethasone had no effect on functional outcomes or long-term analgesia. TRIAL REGISTRATION NUMBER: NCT02760043.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".