Efficacy of Periarticular Multimodal Drug Injection in Total Knee Arthroplasty
Bibliographic record
Abstract
BACKGROUND: Postoperative analgesia with the use of parenteral opioids or epidural analgesia can be associated with troublesome side effects. Good perioperative analgesia facilitates rehabilitation, improves patient satisfaction, and may reduce the hospital stay. We investigated the analgesic effect of locally injected drugs around a total knee prosthesis. METHODS: Sixty-four patients undergoing total knee arthroplasty were randomized either to receive a periarticular intraoperative injection containing ropivacaine, ketorolac, epimorphine, and epinephrine or to receive no injection. The perioperative analgesic regimen was standardized. All patients in both groups received patient-controlled analgesia for twenty-four hours after the surgery, and this was followed by standard analgesia. Visual analog scores for pain, during activity and at rest, and for patient satisfaction were recorded preoperatively and postoperatively and at the six-week follow-up examination. The consumption of patient-controlled analgesia at specific postoperative time-points and the overall analgesic requirement were measured. RESULTS: The patients who had received the injection used significantly less patient-controlled analgesia at six hours, at twelve hours, and over the first twenty-four hours after the surgery. In addition, they had higher visual analog scores for patient satisfaction and lower visual analog scores for pain during activity in the post-anesthetic-care unit and four hours after the operation. No cardiac or central nervous system toxicity was observed. CONCLUSIONS: Intraoperative periarticular injection with multimodal drugs can significantly reduce the requirements for patient-controlled analgesia and improve patient satisfaction, with no apparent risks, following total knee 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".